Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/27386
Title: Modelling of Dubas Bug (Ommatissus lybicus) Habitat and Population Density in Oman Based on Association with Environmental, Climatological and Human Practices Factors
Contributor(s): Al-Kindi, Khalifa Mohammed (author); Kwan, Paul  (supervisor); Andrew, Nigel  (supervisor)orcid ; Welch, Mitchell  (supervisor)orcid 
Conferred Date: 2019-05-09
Copyright Date: 2019-01
Open Access: Yes
Related DOI: https://dx.doi.org/http://dx.doi.org/10.7717/peerj.3752
Handle Link: https://hdl.handle.net/1959.11/27386
Abstract: The Dubas bug (Ommatissus lybicus de Bergevin) is a type of pest that spends its entire life cycle on date palms (Phoenix dactylifera L), thereby causing serious damage and reducing both the growth and the yield of the date palms. The overall aims of this study were (1) to develop and model the habitat, population density and presence or absence of Dubas bug (DB) in Oman based on the associations of those factors with various environmental, climatological and human variables and (2) to predict the potential geographical distribution of parasitic natural enemies of the DB using spatial techniques. The investigations conducted in order to achieve these aims focused on four key research areas, namely (a) the spatial patterns of DBs on the date palms in the study area, (b) the impact of environmental variables on the DB infestation rate (i.e. the impact of human-related practices on DB infestations of date palms), (c) the potential effects of climate-related factors on the absence/presence of DBs and their infestation rate, and (d) the potential of parasitic natural enemies of the DB. These key research areas were studied by means of extensive field investigations, sampling and laboratory testing, as well as detailed analyses.
The results of the first investigation, which took place over the ten-year period from 2006–2015, showed varying degrees of DB infestation, with some regions or conditions having more or fewer hotspots and coldspots than others. The hotspots indicated the sites of potential outbreaks and also revealed the underlying causes of infestation. The distribution patterns of the hotspots varied considerably over time.
In the second investigation, the results of modelling the spatial relationships based on the environmental determinants of DB infestation indicated that three environmental variables, namely elevation, geology and distance from drainage pathways, all had a significant positive effect on the level of DB infestation. In contrast, significant negative relationships were found between the hillshade and aspect variables and the level of DB infestation.
During the third investigation, the analysis of the impact of human-related practices on the degree of DB infestation of date palms indicated strong correlation between the level of DB infestation and several human-related parameters (R2 = 0.70). We found that palm density, flood irrigation and greater use of pesticides increased the number of DB populations on the studied date palms; however, the row spacing, farm maintenance, offshoot removal, education level of employees and use of fertilisers all had significant negative relationships with the number of DB populations.
In the first part of the fourth investigation, a logistic regression (LR) analysis was used to model the relationships between the presence and absence of DBs and the annual averages for various weather and microclimate data in both short-term (spring and autumn of 2017) and long-term (2005–2015) scenarios. In the second part of this investigation, the ordinary least squares (OLS) and geographically weighted regression (GWR) techniques were used to explore the relationships between the DB infestation levels (hotspots and coldspots) and various climate-related variables. The results of three model analyses showed that certain variables positively (e.g. elevation, wind direction, temperature and humidity) or negatively (e.g. wind speed) impacted on the rate of DB survival and the density of the DB populations. It was further found that spatial analytical techniques are useful for detecting and modelling correlations between the presence, absence and density of DBs in response to climatological, environmental and human factors.
During the fifth investigation, the results of the spatial pattern analysis indicated the presence of clustered distributions of parasitic natural enemies of the DB in the study area. The results derived via the spatial regression method revealed models that confidently predicted the influence of DB infestation levels, as well as climatological and environmental variables, on the presence of P. babylonica, A. nr. Beatus and B. hyalinus with a 63%, 89% and 94% confidence level, respectively. The distribution of each species was found to be influenced by distinct and geographically associated climatological features, environmental factors and habitat characteristics.
Overall, this study reveals that spatial analysis and modelling can prove highly useful in terms of studying the distribution and the presence/absence of DBs, as well as their natural enemies. The results are anticipated to contribute to a reduction in both the extent and the cost of the aerial and ground spraying of insecticide required by date palm plantations. Furthermore, this study makes recommendations for future studies, and it offers suggestions concerning monitoring and surveillance methods in relation to the design of both local- and regional-level integrated pest management strategies for palm trees and other affected cultivated crops.
Publication Type: Thesis Doctoral
Field of Research Codes: 070308 Crop and Pasture Protection (Pests, Diseases and Weeds)
090903 Geospatial Information Systems
090905 Photogrammetry and Remote Sensing
Socio-Economic Outcome Codes: 960504 Ecosystem Assessment and Management of Farmland, Arable Cropland and Permanent Cropland Environments
HERDC Category Description: T2 Thesis - Doctorate by Research
Appears in Collections:School of Environmental and Rural Science
School of Science and Technology
Thesis Doctoral

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