The Limiting of Climatic Factors and Predicting of Suitable Habitat for Citrus Gummy Bark Disease Occurrence using GIS
Kh.A. El- Dougdoug
Gummy bark disease is a disorder of sweet orange on sour orange rootstock in Egypt. There is an importance for hot-growing temperatures to symptom development of citrus viroids. The geographical distribution of the gummy bark disease in some world countries depend on high temperatures for viroid-symptom expression. So, correlation between climatic factors and gummy bark disease through GIS is studied. We designed a satellite map for the gummy bark disease distribution all over the world using the previous registered results. Superimposed maps of BIOCLIM annual Min-temperature, Max-Temperature and the points distribution, indicated that gummy bark disease naturally occurs in the low temperature zones range from 8-18°C at winter and from 27-38°C at summer season where the altitude ranged from -351 to 1320 m. A novel method called maximum entropy distribution modeling was used for predicting potential suitable habitat for gummy bark disease in Egypt using occurrence records. The Maxent models internal jackknife test of variable importance showed that altitude and mean temperature of driest quarter are the most important predictors of citrus gummy bark disease-habitat distribution.
September 20, 2011; Accepted: October 22, 2011;
Published: December 02, 2011
Gummy bark is a disorder of trees of sweet orange on sour orange rootstock
in Egypt was described by Nour-Eldin (1956, 1959)
as phloem discoloration of sweet orange. Affected sweet orange trees are usually
stunted to varying degrees and sometimes severely reduced in size. When the
bark of affected trees is scraped, a line of reddish-brown, gum-impregnated
tissue can be seen around the circumference and especially near the bud union
(Nour-Eldin, 1956, 1959). Most
frequent occurrence of citrus gummy bark disease has been recorded in North
Africa and the Middle East countries including Egypt, Saudi Arabia, Sudan, Libya,
Iran, Morocco, Greece and Turkey on different cultivars i.e., Baladi, Aboussoura,
Valencia, Hamlin, Washington navel, Sukkary, Khalili white and Egyptian blood
(Cinar et al., 1993; Bove,
Etiology of this disease is unknown. Because of its graft-transmissibility
character, the disease was first considered to be caused by a virus. Recently,
Citrus Gummy Bark (CGB) is correlated to viroid (Onelge
et al., 2004; Sofy et al., 2010).
Geographical distribution of the gummy bark disease has only been observed in
countries where high temperatures are there to favor viroid-symptom expression
(Roistacher, 1991; Onelge et al.,
The 20th century has a significant increase of Earths average temperature,
rising sea levels and extreme weather events (IPCC, 2001).
Moreover, scientists predict that trend will continue elevating throughout the
21st century (IPCC, 2001). These changes could pose a
significant threat to global biodiversity. As early as 1924, Joseph Grinnell
noted that sudden environmental changes could lead to species extinction (Grinnell,
1924). Species distribution and changes in population structure and abundance
as well could be explained as a warming climate effect (Parmesan
and Yohe, 2003; Root et al., 2003).
This work aimed at: (1) predict suitable-habitat distribution for citrus gummy
bark disease in Egypt using a small number of occurrence records and (2) identify
the environmental factors associated with CGB habitat distribution. Different
approaches have been used (A) CGB occurrence records, (B) GIS (geographical
information system), (C) environmental layers (bioclimatic and topographic)
and (D) the maximum entropy distribution modeling (Phillips
et al., 2006) to predict potential suitable-habitat for CGB occurrence
MATERIALS AND METHODS
Mapping for locations of citrus gummy bark disease occurrence in Egypt through GIS: At each site a GPS fix was recorded in decimal degrees and datum WGS84 using Trimble Navigation ScoutM+ Edition 3.00A receiver. The fix was recorded to the fifth decimal digit. Arc View GIS 9.2 software was used to plot the study sites.
Middle East mapping for distribution of gummy bark disease through GIS:
The gummy bark disease was registered at (Dora and Al Mansuriya) Iraq (Muscat,
Salalah and Tanuf) Oman (Turabah, Najran and Bishah) Saudi Arabia (Al Ladhqiyah
and Ugarit) Syria (Kassala, Atbara, Nyala and Zalingei) Sudan (Tarnab) Pakistan
(Al Hamraniyah) United Arab Emirates (Mukayris, Lawdar, Mudiyah, Seiyun and
Tarim) Southern Yemen (Marib and Harib) Northern Yemen (Dörtyol, Adana,
Erzin, Mersin, Alata, Antalya, Köyceðiz and Yeþilkent) Turkey
and finally (Kalyobiya and Fayoum) Egypt (Bove, 1995;
Onelge et al., 1996; Bernad
et al., 2005; Mohamed et al., 2009;
Sofy et al., 2010). At each site a GPS fix was
recorded in decimal degrees and datum WGS84 using Google Earth Pro. software
(Ver. 4.2.0180.1134 (beta)) (http://earth.google.com/).
The fix was recorded to the fifth decimal digit. Arc View GIS 9.2 software was
used to plot the study sites.
Environmental data: Climate data were obtained from the Worldclim bioclimatic
database which include 19 variables of precipitation and temperature for the
periods at 1950-2000 (Hijmans et al., 2005, available
DIVA-GIS software: DIVA-GIS software is a free computer program for
mapping and geographic data analysis. BIOCLIM is a bioclimatic prediction system
which uses surrogate terms (bioclimatic parameters) derived from monthly mean
climate estimates, to approximate energy and water balances at a given location
(Nelson et al., 1997). The present version can
produce up to 19 bioclimatic parameters based on the climate variables i.e.
maximum and minimum temperatures, rainfall, solar radiation, pan evaporation
and altitude. If some of these climate variables are unavailable, fewer bioclimatic
parameters are produced. BIOCLIM uses monthly or weekly values of maximum and
Predicted distribution range of the gummy bark disease in Egypt: The
Maxent model software predicted a distribution range that visually matched with
the observed location. Regions of higher concentration of presence points were
accurately the areas predicted as of highest presence probability. Receiver
Operating Curve (ROC) analysis was used to evaluate how well the Maxent model
compared to random prediction. The area under the ROC function (AUC) is an index
of performance because it provides a single measure of overall accuracy of distribution
models which ranges from 0 to 1. An AUC of 0.5 indicates a model that is no
better than random prediction, while an AUC of 1 indicates a perfect model for
prediction (Phillips et al., 2004, 2006).
The accuracy is tested against the species records that were used to build the
model. In maximum entropy literature models are selected for their higher (AUC)
(Phillips et al., 2004, 2006).
Also, the jackknife test was used to indicate different variables. Jackknifing
could detect contribution of individual variables to the model.
Maxent utilizes a statistical mechanics approach, called maximum entropy to
make predictions from incomplete information. It estimates the most uniform
distribution. Detailed descriptions of the Maxents methods can be found
in (Phillips et al., 2004, 2006).
Maxents predictions are cumulative values, of probability
value% (Phillips et al., 2004, 2006).
The algorithm is implemented in a stand-alone, freely available application.
In this study, each environmental variable (linear features) and its square
(quadratic features) were used, because Maxent utilize pseudo-absence values.
Citrus gummy bark occurrence in Egypt and in the Middle East: Presence
or absence of citrus gummy bark viroid using GPS was recorded in different locations
belong to four governorates Kalyobiya (Qanater and Al-Sahel regions), Fayoum
(Sanhur tribal region), South Sinai and Behera (Ali Mubarak and Al-Shgaa (22)
regions) (Fig. 1). Occurrence records of citrus gummy bark
disease in two governorates i.e., Kalyobiya and Fayoum has been confirmed by
biological and molecular analysis.
Potential geographic factors distribution of gummy bark disease using its current
distribution and data on a range of environmental parameters has been predicted.
Two computational approaches i.e., DIVA-GIS and Maxent attempts were
used to identify the habitat that affects gummy bark disease occurrence. Data
obtained from DIVA-GIS software showed the optimum range of bioclimatic
factors in different geographical regions of four governorates which we recorded
the presence or absence of citrus gummy bark disease among the different sites
(Table 1). The superimposed maps (Fig. 2A,
B) of BIOCLIM annual Min-temperature, Max-temperature and
the points distribution indicated that, gummy bark disease incidence in Kalyobiya
and Fayoum naturally occur in the low temperature zones range from 11-14°C
at winter and from 28-31°C at summer season (Fig. 2, Table
1). Absence of gummy bark disease in Behera and South Sinai has been confirmed
by the relatively low temperature zones range from 14-17°C at winter and
from 24-28 and 28-31°C, respectively at summer season. Figure
3 indicate rainfall is very low and occurs in winter season which temperature
is low. Summer season where temperature is high has no rain. Dendrogram produced
from the cluster analysis based on the mean temperature of driest quarter which
consider the most important variable factor, present in Fig. 4.
It indicates that; studied locations for citrus gummy bark disease occurrence
have an average dissimilarity percentage of 84 and therefore, the locations
were delimited into two distinct groups (Fig. 4).
|| Location GIS map of study areas
|| The predicted climate data for the studied regions including
different phenomena satisfactorily in Egypt
The first group has two locations Al-Shgaa and Ali Mubarak, Behera governorate.
They are linked together in the same level of 50.
|Fig. 2 (A-B):
||Maps for (A) annual minimum temperature and (B) annual maximum
temperature within the study regions. Key: (1) Al-Sahel, (2) Qanater, (3)
Sanhur, (4) South Sinai, (5) Ali Mubarak and (6) Al-Shgaa (22)
|| Min., Max. temperature (°C) and rainfall values (mm)
for the 6 studied locations as habitats of citrus gummy bark disease occurrence
|| UPGMA-dendrogram based on mean temperature of driest quarter
illustrating similarity and dissimilarity percentage between the studied
regions for citrus gummy bark disease in Egypt
|| Location GIS map of gummy bark disease all over the world
The second group has South Sinai and Fayoum locations delimited at a level
of 68 in which they are linked with Al-Sahel and Qanater locations in a level
of 33. Also, last group has two Al-Sahel and Qanater locations where they are
linked together in the same level of 16 (Fig. 4).
Depending on the occurrence records of this disease; as described in the materials and methods. The GPS points were collected through the google earth software and Arc View GIS 9.2 software was used to plot sites in the Middle East (Fig. 5).
||Maps for (a) annual minimum temperature, (b) maximum temperature
and (c) altitude within the study gummy bark disease regions all over the
||Results of training data (AUC = 0.999) compared to random
prediction (AUC = 0.5) in the receiver operating characteristic (ROC) curve
for representation of the Maxent model for gummy bark disease
The superimposed maps (Fig. 6A, B) of BIOCLIM
annual Min-temperature, Max-temperature and the points distribution indicated
that gummy bark disease naturally occurs in the low temperature zones range
from 8-18°C at winter and from 27-38°C at summer season where the altitude
ranged from -351 to 1320 (Fig. 6C).
Maxent modeling for predicting suitable habitat for gummy bark disease in
Egypt: The Maxent model predicted potential suitable habitat for gummy bark
disease with high success rates of AUC (0.999) which measure the accuracy of
distribution models (Fig. 7). The Maxent models internal
jackknife test of variable importance showed that, altitude and mean temperature
of driest quarter were the two most important predictor factors of gummy bark
disease habitat distribution (Fig. 8, Table
2). These variables presented the higher gain (that contains most information)
compared to other variables (Fig. 8, Table 2).
Most suitable habitat for gummy bark disease was predicted in Egypt as shown
in Fig. 9 and its distribution is quite fragmented.
Among graft transmissible diseases in Egypt and Mediterranean countries; citrus
psorosis disease, citrus exocortis disease, citrus cachexia disease and citrus
gummy bark disease are of the most serious diseases (El-Dougdoug
et al., 1993, 1997, 2009;
Sofy et al., 2010). The geographical distribution
of the gummy bark disease, when high temperatures are favor viroid-symptom expression
has been reported by Roistacher (1991) and Onelge
et al. (1996). So, the correlation between climatic factors and gummy
bark disease through GIS are being focused on. Two computational approaches
DIVA-GIS and Maxent attempts were used to identify the habitat of the gummy
bark disease distribution. Several dimensions of the climatic, physical and
ecological variables were taken in consideration (Table 1).
Ganeshaiah et al. (2003) reported the predictions
of potential distribution of the sugarcane woolly aphid. This report could help
in developing strategies for monitoring and managing other pests and/or diseases.
|| Results of jackknife evaluations of relative importance of
predictor variables for gummy bark disease Maxent model
|| Selected environmental variables and their percent contribution
in Maxent model for gummy bark disease in Egypt
BIOCLIM annual Min-temperature, Max-temperature and the points distribution
of gummy bark disease in Egypt indicated that, gummy bark disease naturally
occurs in the low temperature zones range from 11-14°C at winter and from
28-31°C at summer season (Fig. 2). To ensure the BIOCLIM
data, a map for the gummy bark disease distribution all over the Middle East
region where registered by Bove (1995), Onelge
et al. (1996), Bernad et al. (2005),
Mohamed et al. (2009) and Sofy
et al. (2010).
|| Predicted potential suitable habitat for gummy bark disease
Following are the locations mapped: In Iraq (Dora and Al Mansuriya), Oman (Muscat,
Salalah and Tanuf), Saudi Arabia (Turabah, Najran and Bishah), Syria (Al Ladhqiyah
and Ugarit), Sudan (Kassala, Atbara, Nyala and Zalingei), Pakistan (Tarnab),
United Arab Emirates (Al Hamraniyah), Southern Yemen (Mukayris, Lawdar, Mudiyah,
Seiyun and Tarim), Northern Yemen (Marib and Harib), Turkey (Dörtyol, Adana,
Erzin, Mersin, Alata, Antalya, Köyceðiz and Yeþilkent) as well
as Egypt (Kalyobiya and Fayoum). Previous data shows, BIOCLIM annual Min-temperature,
Max-Temperature and the points distribution of the gummy bark disease in the
Middle East region occurs naturally in the low temperature zones range from
8-18°C at winter and from 27-38°C at summer season where the altitude
ranged from -351 to 1320 m according to Nelson et al.
Ecological niche modeling has been used to predict current and future species
distributions and to provide recommendations of habitat conservation (Graham
et al., 2004). Such models can correlate species-presence data with
environmental variables i.e., temperature, precipitation and elevation. Beaumont
and Hughes (2002) has used for models comparing current and future distributions
of Australian butterflies and also to identify species most vulnerable to climate
change. Similarly, Berry et al. (2002) has explored
the impacts of climate change on 54 species and 15 habitats in the United Kingdom
using a niche modeling technique. These models have been used to identify habitats
of climate change and prediction of butterfly, Erebia epiphron Knoch.
MAXENT, a machine-learning method based on the principle of maximum entropy,
are used to predict distribution for each species of butterfly under current
and future climates. Data from this model is used to test the efficiency of
the modeling program through the evaluation of the area under the Receiving
Operator Curve (AUC) (Elith et al., 2006; Phillips
et al., 2004, 2006). MAXENT was used, here
in, to create gummy bark disease distribution models. Model was made with both
1950-2000 averaged bioclimatic data. The Maxent model predicted potential suitable
habitat for gummy bark disease distribution in Egypt with high success rates
of AUC (0.999) which measures the accuracy of distribution models. The Maxent
models internal jackknife test of variable importance showed that altitude
and mean temperature of driest quarter were the two most important factors in
prediction of citrus gummy bark disease habitat distribution (Hijmans
et al., 2005). This study provides the first predicted potential
habitat distribution map for citrus gummy bark disease in Egypt. The potential
habitat distribution map for citrus gummy bark disease can help in A) planning
management around its existing disease, B) identify top-priority survey sites,
or set priorities to restore its natural habitat for more effective conservation.
More research is needed to determine whether the existing protected areas adequately
cover suitable habitat for citrus gummy bark disease. The methodology presented
here in could be used for quantifying habitat distribution patterns for other
threatened and endangered plant pathogens and/or plant pests (Kumar
and Stohlgren, 2009).
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