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ORIGINAL ARTICLE
Composition and diversity of weed communities
in Al-Jouf province, northern Saudi Arabia
Nasr H. Gomaa
*
Department of Botany, Faculty of Science, Beni-Suef University, Beni-Suef, Egypt
Department of Environmental Sciences, College of Sciences, Al-Jouf University, Sakaka, Saudi Arabia
Received 4 March 2012; revised 1 May 2012; accepted 7 May 2012
Available online 14 May 2012
KEYWORDS
Diversity;
Saudi Arabia;
Soil characteristics;
Weeds
Abstract The aim of this study was to identify the main weed communities in Al-Jouf province in
northern Saudi Arabia. Moreover, the composition and diversity of these communities were studied
in relation to soil variables and crop type. Some 54 stands representing olive orchards, date palm
orchards, wheat crop and watermelon crop were studied, using ten quadrats (1 · 1 m) per stand.
A total of 71 species belonging to 22 families and 61 genera were observed. The classification of veg-
etation using the Two Way Indicator Species Analysis (TWINSPAN) resulted in the recognition of
four vegetation groups representing wheat crop, orchards in winter season, orchards in summer sea-
son and watermelon crop. These results suggested the importance of both crop and season for the
formation of weed community. Detrended Correspondence Analysis (DCA) showed that these
groups are clearly distinguished by the first two DCA axes. The species richness was higher in both
olive and date palm orchards than in wheat and watermelon crops. This pattern of species richness
could be related to farm management practices and habitat micro-heterogeneity. Soil electrical con-
ductivity, organic carbon and soil texture showed significant correlations with species richness and
the cover values of some dominant species, suggesting the significant role of soil characteristics in
weed community structure and diversity.
ª 2012 King Saud University. Production and hosting by Elsevier B.V. All rights reserved.
1. Introduction
Weeds are plants which grow where they are not wanted. They
differ from other plants in being more aggressive, having pecu-
liar characteristics that make them more competitive. Weeds de-
crease the crop yield by competing for water, nutrients, space
and light (Qasem and Hill, 1995; Wang et al., 2007). Some weeds
are also allelopathic and adversely affect crops (Shah and Khan,
2006; Jabeen and Ahmed, 2009). Losses in crop yield and pro-
duction caused by weeds are well documented in many studies
(e.g., Aldrich, 1984; Akobundu, 1987; Swanton et al., 1993;
Khedr and Hegazy, 1998; Fayed et al., 1999). Therefore, there
is an urgent need for effective weed management programs.
*
Address: Department of Botany, Faculty of Science, Beni-Suef
University, Beni-Suef, Egypt. Tel.: +20 1287752207.
E-mail address: nhgomaa@yahoo.com
1319-562X ª 2012 King Saud University. Production and hosting by
Elsevier B.V. All rights reserved.
Peer review under responsibility of King Saud University.
http://dx.doi.org/10.1016/j.sjbs.2012.05.002
Production and hosting by Elsevier
Saudi Journal of Biological Sciences (2012) 19, 369–376
King Saud University
Saudi Journal of Biological Sciences
www.ksu.edu.sa
www.sciencedirect.com
For such programs to be visible, accurate information on the
weed flora and the distribution, abundance and phenology of
weed species and weed communities are pre-requisite (Frick
and Thomas, 1992; Ghersa and Holt, 1995). Such kind of data
may also be valuable for understanding weed communities and
for creating a higher biodiversity in arable land (Andreasen and
Skovgaard, 2009).
Weed communities are affected by many factors as farm
management practices (Derksen et al., 1994; Andersson and
Milberg, 1998; Thomas and Frick, 1993), crop type (Andersson
and Milberg, 1998; Andreasen and Skovgaard, 2009), season
(El-Demerdash et al., 1997) and soil characteristics (Fried
et al., 2008; Pinke et al., 2010). The many factors involved in
the formation of the weed community make it difficult to eval-
uate the relative importance of each individual factor (Pysek
and Leps, 1991).
The weed flora of Saudi Arabia was presented by Chaudhary
and Akram (1987). The weed flora of date palm orchards in Al-
Hassa Oasis in eastern Saudi Arabia was documented by El-
Halawany and Shaltout (1992), while the weed communities
of date palm orchards in the same area were identified and de-
scribed by Shaltout and El-Halawany (1992). A check list of
weeds in Al-kharj area in the central region of Saudi Arabia
was made by Al-Yemeny (1999). Recently, Sher and Al-Yemeni
(2011) prepared an ecotaxonomical inventory of weed flora in
Al-kharj area of Saudi Arabia. Moreover, Gazer (2011) studied
the floristic composition and diversity of the weed vegetation as
well as the relationships between weed assemblages and soil
characters in date palm orchards of Al-Qassim area in central
Saudi Arabia.
Studies on weed flora and weed communities in the King-
dom of Saudi Arabia are still fragmentary and incomplete
(Sher and Al-Yemeni, 2011). The lack of such information is
more obvious for Al-Jouf province in northern Saudi Arabia.
To the present author’s knowledge, the weed communities of
Al-Jouf province have not been previously studied. The pres-
ent work aims to recognize the major plant communities in
Al-Jouf province (northern Saudi Arabia) and assess their
structure, diversity and distribution in relation to crop type
and soil characters.
2. Materials and methods
2.1. Study area
Al-Jouf province is located in the northern part of Saudi
Arabia, where it is bounded from the north and east by the
Northern Borders province and from the south by Hail and
Tabuk provinces and delimited from the north and west by
Jordan (Fig. 1). It is located between latitudes 29 and 32N
and longitudes 37 and 42E. Its area is about 107,794 km
2
,
representing 4.9% of the total area of Saudi Arabia. Al-Jouf
province consists of the town of Sakaka and two governorates
(Dawmat Al-Jandal and Al-Qurayat).
Al-Jouf province is one of the important agricultural re-
gions of Saudi Arabia. The cultivated area approximates
460,000 ha. The region is characterized by the cultivation of
orchards, particularly olive and date palm in addition to other
field crops as wheat, barley, alfalfa, sorghum, and watermelon.
The study area is characterized by dry climate with hot
summer and cool winter. According to the records of Al-Jouf
Airport meteorological station for the period 2000–2010, the
mean monthly air temperature ranges between 9.8 C during
January and 33.8 C during August. The mean monthly rela-
tive humidity varies between 16% during June and 53% during
January. The average annual wind speed is 13 km/h. The
rainfall in the region is erratic and irregular and the mean an-
nual rainfall is 55 mm, with the rainy season stretching from
October to May.
2.2. Vegetation sampling
The weed vegetation were sampled in 54 stands representing
two kinds of orchards (olive and date palm) as well as a winter
(wheat) and a summer crop (watermelon). The stands were dis-
tributed in five locations (Sakaka, Dawmat Al-Jandal, Abo
Ajram, Tabarjal and Al-Qurayat, Fig. 1) in Al-Jouf province.
Each type of orchards was represented by 15 stands, while 24
stands were sampled in wheat and watermelon crops (12 stands
per crop). The area of the stand was 20 · 20 m. The orchards
were sampled during both winter (March 2011) and summer
(June 2011) seasons, while the wheat crop was sampled during
March 2011 and watermelon crop during June 2011. In each
stand, the present species were recorded and their cover was
evaluated visually as percentage of the ground surface in 10
randomly sampled quadrats (1 · 1 m each). Species identifica-
tion and nomenclature followed Chaudhary and Akram
(1987), Chaudhary (1999, 2000, 2001) and Al-Hassan (2006).
Species were categorized in terms of their life form according
to Raunkiaer (1934) into therophytes, hemicryptophytes, geo-
phytes, chamaephytes and phanerophytes.
2.3. Soil analysis
Three soil samples were taken per stand, from a depth of 0–
50 cm. The samples were pooled together, forming one com-
posite sample for each stand. The samples were air dried and
sieved through a 2 mm sieve before analysis. For soil texture
analysis, the soil fractions were separated by sieves. Hundred
grams of each soil sample was passed through a series of sieves
Figure 1 Map of Saudi Arabia showing the study area and the
sampling locations (1, Sakaka; 2, Dawmat Al-Jandal; 3, Abo
Ajram; 4, Tabarjal; 5, Al-Qurayat).
370 N.H. Gomaa
Table 1 A list of the species recorded in the study area with their families, life form and mean cover values in the four vegetation
groups resulted from TWINSPAN classification. Th, therophytes; H, hemicryptophytes; G, geophytes; Ch, chamaephytes; Ph,
phanerophytes; +, present; , absent.
Species Family Life form Vegetation group
ABCD
Alhagi graecorum Boiss. Fabaceae H – 0.2 0.4 –
Amaranthus graecizans L. Amaranthaceae Th – – 0.2 0.5
Amaranthus lividus L. Amaranthaceae Th – – 0.2 0.3
Anagallis arvensis L. Primulaceae Th 0.5 0.3 – –
Avena fatua L. Poaceae Th – 0.2 – –
Brachiaria reptans (L.) C.A. Gardner and C.E. Hubb. Poaceae Th – – 0.1 1.8
Brassica tournefortii Gouan Brassicaceae Th 0.1 – – –
Cenchrus biflorus Roxb. Poaceae Th – – 0.7 0.4
Chenopodium album L. Chenopodiaceae Th – 0.3 – –
Chenopodium murale L. Chenopodiaceae Th 12.1 0.2 – –
Cichorium endivia L. Asteraceae Th 0.1 0.1 – –
Citrullus colocynthis (L.) Schrad. Cucurbitaceae H – 0.1 – –
Convolvulus arvensis L. Convolvulaceae G 1.0 5.7 4.7 1.4
Conyza bonariensis (L.) Cronquist. Asteraceae Th – – 6.4 –
Corchorus olitorius L. Tiliaceae Th – – 0.2 0.1
Cynodon dactylon (L.) Pers. Poaceae G 0.1 4.7 15.7 1.0
Cyperus rotundus L. Cyperaceae G – 0.3 0.7 0.1
Dactyloctenium aegyptium (L.) Willd. Poaceae Th – – 2.7 1.6
Datura stramonium L. Solanaceae Th – – 0.1 –
Desmostachya bipinnata (L.) Stapf Poaceae H – – 0.1 –
Dichanthium annulatum (Forssk.) Stapf Poaceae H – – 0.1 –
Digitaria sanguinalis (L.) Scop. Poaceae Th – – 1.6 1.5
Echinochloa colona (L.) Link. Poaceae Th – – 0.4 10.9
Emex spinosa (L.) Campd. Polygonaceae Th 4.2 0.2 – –
Eragrostis cilianensis (All.) F. T. Hubb. Poaceae Th – – 6.3 3.8
Erodium malacoides (L.) L’Her. Geraniaceae Th 0.1 – – –
Euphorbia helioscopia L. Euphorbiaceae Th – 0.2 – –
Euphorbia peplus L. Euphorbiaceae Th – 1.8 – –
Halocnemum strobilaceum (Pall.) M. Bieb Chenopodiaceae Ch – – 0.1 –
Haloxylon salicornicum (Moq.) Bunge ex Boiss. Chenopodiaceae Ch – – 0.1 –
Hibiscus trionum L. Malvaceae Th – – 0.1 0.1
Hyoscyamus muticus L. Solanaceae Ch – 0.1 – –
Imperata cylindrica (L.) Raeusch Poaceae H – 24.4 1.5 –
Juncus rigidus Desf. Juncaceae H – 0.1 – –
Lactuca serriola L. Asteraceae Th 1.8 0.1 – –
Launaea capitata (Spreng.) Dandy Asteraceae Th 0.1 – – –
Launaea nudicaulis (L.) Hook. F. Asteraceae H 1.1 0.1 – –
Lolium temulentum L. Poaceae Th 0.1 – – –
Malva parviflora L. Malvaceae Th 0.5 2.6 – –
Melilotus indicus (L.) All. Fabaceae Th 6.8 1.3 – –
Panicum turgidum Forssk. Poaceae Ch – 0.1 – –
Paspalum distichum L. Poaceae H – – 0.1 –
Phalaris minor Retz. Poaceae Th 0.1 0.2 – –
Phragmites australis (Cav.) Trin.ex Steud. Poaceae G – 1.5 3.6 –
Plantago amplexicaulis Cav. Plantaginaceae Th 0.1 – – –
Plantago major L. Plantaginaceae Th – 0.1 – –
Plantago lagopus L. Plantaginaceae Th – 6.6 – –
Pluchea dioscoridis (L.) DC. Asteraceae Ph – – 0.1 –
Poa annua L. Poaceae Th – 0.2 – –
Polypogon monspeliensis
(L.) Desf. Poaceae Th – 0.3 – –
Portulaca oleracea L. Portulacaceae Th – – 0.4 5.8
Pulicaria undulata (L.) C.A. Mey. Asteraceae Ch – 0.1 – –
Reichardia tingitana (L.) Roth. Asteraceae Th 0.7 – – –
Ricinus communis L. Euphorbiaceae Ph – 0.1 – –
Rumex dentatus L. Polygonaceae Th 0.3 0.3 – –
Rumex vesicarius L. Polygonaceae Th 0.1 – – –
Schismus barbatus (L.) Thell. Poaceae Th 0.2 – – –
Setaria pumila (Poir.) Roem. and Schult. Poaceae Th – – 2.2 0.1
Setaria verticillata (L.) P. Beauv. Poaceae Th – – 0.1 0.1
Sisymbrium irio L. Brassicaceae Th 0.3 0.2 – –
Composition and diversity of weed communitiesin Al-Jouf province, northern Saudi Arabia 371
to separate gravels (>2 mm), coarse and medium sand (2–
0.25 mm), fine and very fine sand (0.25–0.05 mm), and silt
and clay (<0.05 mm). The percentage of CaCO
3
was estimated
using 1 N HCl (Jackson, 1967). Oxidizable organic carbon was
determined by modified Walkley–Black method (Jackson,
1958). Soil–water extracts of 1:5 were prepared and used for
determination of electrical conductivity (EC) and soil reaction
(pH) using a conductivity and pH meter (Jenway 4330).
2.4. Data analysis
TWINSPAN, Two Way Indicator Species Analysis (Hill,
1979a), was applied for the classification of stands into groups
based on the cover values of species. The Detrended Corre-
spondence Analysis (DCA) (Hill, 1979b) was used to ordinate
stands in two-dimensional space using the cover values of
species. Data of the soil variables of the vegetation groups
Table 1 (continued)
Species Family Life form Vegetation group
ABCD
Solanum nigrum L. Solanaceae Th – 0.1 0.1 –
Sonchus oleraceus L. Asteraceae Th 1.5 1.2 0.1 –
Spergularia marina (L.) Griseb. Caryophyllaceae Th – 0.1 – –
Tamarix nilotica (Ehrenb.) Bunge Tamaricaceae Ph – – 0.5 –
Trigonella hamosa L. Fabaceae Th – 0.2 – –
Trigonella stellata Forssk. Fabaceae Th 0.1 – – –
Vicia sativa L. Fabaceae Th – 0.1 – –
Withania somnifera (L.) Dunal. Solanaceae Ch – 0.1 – –
Zilla spinosa (L.) Prantl Brassicaceae Ch – 0.1 – –
Zygophyllum album L. F. Zygophyllaceae Ch – 0.1 – –
Zygophyllum coccineum L. Zygophyllaceae Ch – 0.1 0.1 –
AB
D
C
DAC AEG
DIG SAN
ECH COL
MEL IND
ECH COL CYN DAC
CON BON
CHE MUR
CON ARV
PLA LAG
RUM DEN
CYP ROT
SET PUM
COR OLI
Figure 2 TWINSPAN dendrogram of the 54 stands based on the cover values of species. Indicator species names are abbreviated to the
first three letters of both species and genus names. For complete names, see Table 1.
Figure 3 DCA ordination of the 54 stands based on the cover
values of species with the vegetation groups resulted from
TWINSPAN superimposed.
372 N.H. Gomaa
identified by TWINSPAN were compared by one-way ANOVA
followed by Tukey’s post hoc test. The same analysis was used to
compare between the diversity indices of the vegetation groups.
Linear correlations of soil variables with diversity indices, DCA
axes and cover values of the dominant species were made to re-
late the diversity, distribution and structure of weed communi-
ties to edaphic factors. The one-way ANOVA and correlation
analyses were conducted using SPSS 12 for Windows.
Species richness and Shannon index were applied for mea-
surement of diversity in each stand (Pielou, 1975):
Species richness : S ¼ the number of species per stand
Shannon index of diversity : H
0
¼
X
S
i¼1
p
i
ln p
i
where p
i
is the relative cover of species i.
Table 2 Means ± SD of diversity and edaphic variables of the different vegetation groups.
Variable Vegetation group
AB CD
Species richness 9.8
a
± 1.5 13.5
b
± 1.4 11.7
c
± 1.0 8.1
d
± 1.3
Shannon index 1.61
a
± 0.12 1.41
a
± 0.24 1.63
a
± 0.22 1.50
a
± 0.28
CaCO
3
(%) 3.0
a
± 1.0 3.3
a
± 0.9 3.3
a
± 0.9 3.2
a
± 0.9
HCO
3
ð%Þ 0.07
a
± 0.01 0.07
a
± 0.01 0.07
a
± 0.02 0.06
a
± 0.01
pH 7.7
a
± 0.2 7.6
a
± 0.1 7.7
a
± 0.2 7.7
a
± 0.2
Electrical conductivity (mS/cm) 0.68
a
± 0.06 0.87
b
± 0.14 0.90
b
± 0.19 0.74
a
± 0.07
Organic carbon (%) 0.52
a
± 0.14 0.95
b
± 0.11 0.92
b
± 0.12 0.60
a
± 0.13
Gravels (%) 10.0
a
± 2.3 9.2
a
± 2.7 9.4
a
± 2.6 10.2
a
± 2.1
Coarse and medium sand (%) 35.8
a
± 3.9 32.5
a
± 3.0 33.0
a
± 3.0 35.7
a
± 4.1
Fine and very fine sand (%) 37.8
a
± 4.0 39.4
a
± 3.4 38.0
a
± 3.9 37.3
a
± 4.1
Silt and clay (%) 16.4
a
± 1.6 18.9
b
± 1.4 19.6
b
± 1.3 16.9
a
± 1.7
Values in a row sharing the same letter are not significantly different at the 0.05 level of probability.
Table 3 Linear correlation coefficients (r) of edaphic factors with diversity indices and the first two DCA axes.
Edaphic parameter Species richness Shannon index DCA axis 1 DCA axis 2
CaCO
3
(%) 0.057 0.240 0.092 0.175
HCO
3
ð%Þ 0.174 0.017 0.073 0.125
pH 0.064 0.012 0.006 0.024
Electrical conductivity (mS/cm) 0.367
**
0.038 0.049 0.045
Organic carbon (%) 0.615
**
0.031 0.206 0.297
*
Gravels (%) 0.173 0.007 0.010 0.090
Coarse and medium sand (%) 0.395
**
0.038 0.081 0.004
Fine and very fine sand (%) 0.223 0.066 0.028 0.106
Silt and clay (%) 0.526
**
0.064 0.195 0.085
*
P < 0.05.
**
P < 0.01.
Table 4 Linear correlation coefficients (r) between edaphic factors and the cover values of the dominant species.
Species Edaphic variable
CaCO
3
HCO
3
pH Electrical
conductivity
Organic
carbon
Gravels Coarse and
medium sand
Fine and very
fine sand
Silt and clay
Chenopodium murale 0.014 0.044 0.139 0.293
*
0.541
**
0.139 0.143 0.044 0.356
**
Convolvulus arvensis 0.230 0.179 0.111 0.055 0.377
**
0.081 0.003 0.093 0.075
Conyza bonariensis 0.238 0.081 0.187 0.164 0.327
*
0.031 0.257 0.002 0.452
**
Cynodon dactylon 0.063 0.001 0.266 0.202 0.390
**
0.048 0.354
**
0.122 0.375
**
Echinochloa colona 0.034 0.186 0.088 0.285
*
0.304
*
0.122 0.142 0.065 0.292
*
Eragrostis cilianensis 0.036 0.133 0.270
*
0.039 0.121 0.049 0.073 0.082 0.079
Imperata cylindrica 0.242 0.124 0.189 0.154 0.369
**
0.173 0.272
*
0.264 0.213
Melilotus indicus 0.290
*
0.083 0.008 0.155 0.297
*
0.089 0.214 0.100 0.320
*
Plantago lagopus 0.060 0.033 0.052 0.211 0.356
**
0.125 0.069 0.006 0.294
*
Portulaca oleracea 0.118 0.048 0.010 0.247 0.240 0.095 0.110 0.071 0.186
*
P < 0.05.
**
P < 0.01.
Composition and diversity of weed communitiesin Al-Jouf province, northern Saudi Arabia 373
3. Results
3.1. Floristic composition
In total, 71 plant species belonging to 22 families and 61 genera
were observed. The largest family was Poaceae (21 species),
followed by Asteraceae (9 species), Fabaceae (5 species),
Chenopodiaceae and Solanaceae (4 species for each) (Table
1). The life form spectrum exhibited a wide range of variation
(Table 1). Therophytes were the predominant life form and
constituted 66.2% of the total flora, followed by chamaephytes
(12.7%), hemicryptophytes (11.3%), geophytes (5.6%), and
phanerophytes (4.2%).
3.2. Vegetation classification
The application of TWINSPAN classification technique on the
cover values of the recorded species in the 54 stands leads to
the separation of four vegetation groups (A–D, Fig. 2). Each
vegetation group comprises a set of stands which are similar
in their vegetation.
Group A represents the stands of wheat. The dominant spe-
cies of this vegetation group are Chenopodium murale and
Melilotus indicus. The common associated species are Emex
spinosa, Lactuca serriola and Sonchus oleraceus. C. murale is
the indicator species of this group.
Group B includes the stands of olive and date palm orch-
ards in winter season. Imperata cylindrica, Plantago lagopus
and Convolvulus arvensis are the dominant species in this
group, while the common species are Cynodon dactylon, Malva
parviflora, Euphorbia peplus and Phragmites australis.
Stands of Group C represent the olive and date palm orch-
ards in summer season and are dominated by C. dactylon,
Conyza bonariensis and Eragrostis cilianensis. The common
species are C. arvensis, Dactyloctenium aegyptium, Digitaria
sanguinalis, I. cylindrica, P. australis and Setaria pumila, while
the indicator species of this group are C. dactylon and C.
bonariensis.
Group D includes the stands sampled in watermelon crop
and are dominated by Echinochloa colona and Portulaca oler-
acea. E. colona is the indicator species of the group, whereas
Brachiaria reptans, D. aegyptium, D. sanguinalis and E. cilian-
ensis are the important common species.
3.3. DCA ordination
Ordination of the 54 stands given by DCA (Fig. 3) indicates
that the vegetation groups produced by TWINSPAN classifi-
cation are markedly distinguishable and show a clear pattern
of segregation on the ordination planes. The vegetation groups
are clearly distinguished and distributed mainly along axis 1
from left to right in the order: groups D, C, B and A. The
eigenvalues for the first two DCA axes are 0.851 and 0.345,
respectively. The high eigenvalue for DCA axis 1 indicates that
it explains the major variation in species composition of the
vegetation groups.
3.4. Species diversity
Species richness varies significantly among vegetation groups
(P < 0.05). Vegetation group B has the highest species rich-
ness (13.5 species/stand), followed by vegetation group C
(11.7 species/stand), vegetation group A (9.8 species/stand)
and vegetation group D (8.1 species/stand). On the other hand,
the vegetation groups do not show significant differences in the
values of Shannon index (Table 2).
3.5. Vegetation–soil relationships
Edaphic characteristics of the four vegetation groups are sum-
marized in Table 2. Of the measured soil parameters, electrical
conductivity, organic carbon, silt and clay show significant dif-
ferences (P < 0.05) among vegetation groups. Electrical con-
ductivity is significantly higher in groups B and C (0.87 and
0.90 mS/cm, respectively) than in groups A and D (0.68 and
0.74 mS/cm, respectively). Vegetation groups B and C show
values of organic carbon (0.95 and 0.92%, respectively) which
are significantly higher than in groups A and D (0.52 and
0.60%, respectively). Likewise, the percentages of silt and clay
are significantly higher in groups B and C (18.9 and 19.6%,
respectively) compared to groups A and D (16.4 and 16.9%,
respectively).
Species richness shows significant correlations with electri-
cal conductivity (r = 0.367, P < 0.01), organic carbon
(r = 0.615, P < 0.01), coarse and medium sand (r = 0.395,
P < 0.01) and silt and clay (r = 0.526, P < 0.01). Shannon in-
dex and DCA axis 1 do not show any significant correlations
with the measured soil parameters. DCA axis 2 is significantly
correlated with only soil organic carbon (r = 0.297,
P < 0.05) (Table 3).
Correlations of edaphic variables with the cover values of
the dominant species are shown in Table 4. Electrical conduc-
tivity exhibits significant correlations with C. murale
(r = 0.293, P < 0.05) and E. colona (r = 0.285,
P < 0.05). With the exception of E. cilianensis and P. oleracea,
all the tested dominant species show significant correlations
with organic carbon. Coarse and medium sand are correlated
significantly with C. dactylon (r = 0.354, P
< 0.01) and I.
cylindrica (r = 0.272, P < 0.05). Silt and clay correlate sig-
nificantly with all the tested dominant species except C. arven-
sis, E. cilianensis, I. cylindrica and P. oleracea.
4. Discussion
The weed vegetation in the study area comprises 71 plant spe-
cies, including 47 annuals (66.2%) and 24 perennials (33.8%).
The high contribution of annuals can be attributed to their
short life cycle that enables them to resist the instability of
the agro-ecosystem. Moreover, they are generally character-
ized by high allocation of resources to the reproductive organs
(Harper, 1977) and the production of flowers early in their life-
span to ensure some seed production even in a year when the
growing season is cut short (Sans and Masalles, 1995).
The application of TWINSPAN resulted in the classifica-
tion of weed vegetation in the study area into four vegetation
groups, representing wheat crop, orchards in winter season,
orchards in summer season and watermelon crop. Such classi-
fication indicates the significant effects of both crop and season
on the weed community composition and structure. The vege-
tation groups, resulted from TWINSPAN classification, are
clearly distinguished by the first two DCA axes. Thus, the
DCA analysis also strengthens the importance of crop and
374 N.H. Gomaa
season for the formation of weed community. These results
agree with those of El-Demerdash et al. (1997) and Andersson
and Milberg (1998), who pointed out that season and crop
type, contribute to the composition of weed community. The
effect of crop may be indirect. For example, fertilization re-
gimes, soil management practices, application of herbicides
and weed management may vary depending on the crop type,
and these factors influence weed community composition
(Hume, 1982; Le
´
gere and Samson, 1999; Leeson et al., 2000).
The weed vegetation in wheat crop is dominated by C. murale
and M. indicus. These two species were reported by Shaltout and
El-Halawany (1992) to dominate some weed communities of
date palm orchards in eastern Saudi Arabia. Moreover, they also
dominate weed communities of winter crops in Egypt (Hegazy
et al., 2004). The dominant species of weed vegetation of olive
and date palm orchards in the study area during winter season
are I. cylindrica, P. lagopus and C. arvensis. These species were
recorded by Shaltout and El-Halawany (1992) as dominant
weeds in eastern Saudi Arabia. Moreover, C. arvensis was listed
as a co-dominant species in the date palm orchards of Central
Saudi Arabia (Gazer, 2011). The weed vegetation in olive and
date palm orchards in summer season is dominated by C. dact-
ylon, C. bonariensis and E. cilianensis. C. dactylon was reported
as a dominant or co-dominant weed in orchards and field crops
in Saudi Arabia and the surrounding countries (Chaudhary
et al., 1981; Gazer, 2011). C. bonariensis was reported by Al-
Yemeny (1999) as a serious weed causing very severe infestations
in field crops and orchards in Saudi Arabia. E. colona and P.
oleracea are the dominant weeds in watermelon crop in the study
area. These two species were listed by Chaudhary et al. (1981)
among weeds that cause severe infestation in agricultural areas
in the central, southern and eastern Arabian Peninsula.
The weed vegetation in the study area includes, in addition
to arable weeds, some desert species that grow in the surround-
ing natural habitats as Citrullus colocynthis, Haloxylon sali-
cornicum, Panicum turgidum, Zilla spinosa and Zygophyllum
coccineum. Similar observations were documented by Gazer
(2011).
The species richness is higher in both olive and date palm
orchards than in wheat and watermelon crops. The environ-
ment of weeds in orchards is influenced by the protection given
by the tree foliage. Two kinds of light conditions occur in orch-
ards, the shaded microhabitat present below the crowns of
trees and the relatively sunny microhabitat present between
trees. The high species richness in orchards may be related to
this environmental micro-heterogeneity that promotes diver-
sity ( Palmer and Maurer, 1997). The difference in field
management practices may also be a factor that explains dif-
ferences in weed species richness (Stevenson et al., 1997; Sher
and Al-Yemeni, 2011). The low species richness in wheat and
watermelon crops compared to orchards can be attributed to
the fact that the land of field crops is generally plowed each
season before the sowing of crops, a practice that reduces
the richness of weeds compared to the orchards that are rarely
plowed.
With the exception of organic carbon, none of the mea-
sured soil variables show significant correlations with DCA
axes. This indicates that soil characters are not the major fac-
tors that contribute to the distribution of communities along
DCA axes. Other factors as crop type and season may contrib-
ute more importantly to the distribution of weed communities
along DCA axes.
Soil electrical conductivity, organic carbon, coarse and
medium sand, silt and clay showed significant correlations with
species richness and the cover values of some dominant spe-
cies. Moreover, electrical conductivity, organic carbon, silt
and clay exhibited significant differences between orchards
and field crops. These results suggest the effective role of these
soil parameters in the weed community structure and diversity.
The present findings agree with those of Fried et al. (2008),
Andreasen and Skovgaard (2009) and Pinke et al. (2010) that
indicated the importance of soil texture, salinity and organic
carbon for the composition and species richness of weed com-
munities. Organic matter content as a pivotal soil fertility fac-
tor can affect phytodiversity (Zhang et al., 2010). Moreover,
soil texture may affect soil or productivity via influence on
the soil water holding capacity, infiltration rate, moisture
availability for plants and consequently plant nutrition (Sperry
and Hacke, 2002).
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