Current research projects
Modelling of Dubas Bug Habitat and Population Density in Oman Based on Associations with Human, Environmental and Climatological Factors
Funded by Oman Research Council, $690,000.
This research will use tools and techniques available in modern spatial analysis packages, such as Geographic Information Systems and Remote Sensing, to model and develop spatial links and correlations between presence/absence/density of Dubas bugs with climatological, environmental and human factors and conditions. It will develop GIS layers that give the density and distribution of the bug infestation levels and the stress observed in the date palms, and link them with rainfall patterns, humidity, wind direction, temperature, soil salinity, irrigation practices, farming practices, etc. to investigate correlates. It will also investigate whether soil types, geology, aspect, slope, elevation and available solar radiation play any part in enhancing the development, survival and spread of the Dubas bug. The project will also use combinations of some of these variables, such as the humid-thermal index (HTI) to gain an understanding of preferred environments of the Dubas bug. This research will start off by using single variables to develop correlations and then move onto more complicated predictive models and regression analysis where we incorporate all factors to investigate what combinations of factors are the most conducive to the survival and spread of the bugs.
The project will use modern geostatistical techniques and statistics to look at hot spots and clustering of the bugs and investigate why they are clustered in certain regions/conditions. These techniques will help to identify the most important variables or combinations of variables that help the Dubas bug develop, prosper and migrate.
The project will also use remote sensing tools and satellite images to develop early detection techniques for the Dubas Bug at broad scales. It will use satellite images to map the spatial distribution of the bug, and possibly do this on a temporal scale as well to see the directions and speed of spread. The output, especially the spatial distribution and spread images, will be used as inputs to the GIS-based predictive models.
This project will also look at issues such as:
1. Human-related factors, such as aerial spraying. It will be of value to gather aerial and ground insecticide spraying data for the past 10 to 20 years and correlate these with current bug densities and densities of key natural enemies.
2. Cultural practices such as planting distance, irrigation, fertilization, pruning and sanitation should be also considered in any model to explain distribution and density of the Dubas Bug.
3. Biotic factors such as species and densities of natural enemies (predators, parasitoids, parasites, and pathogens). Even if the environment and climate is conducive, but there is significant mortality due to natural enemies then Dubas bug densities will effectively be lower.
4. It will use modern geostatistical techniques and statistics such as Geary’s Index, Morans I, Getis- Ord Gi*, Ripley’s K-Function, etc. to look at hot spots and clustering of the bugs and investigate why they are clustered in certain regions/conditions. These techniques will help to identify the most important variables or combinations of variables that help the Dubas bug develop, prosper and migrate. Once the factors and combinations of factors have been identified it will then use these to develop predictive models that will be able to give the probability of occurrence, spatial distribution and densities under different environmental, climatological and resource availability conditions.
These models then could be used to forecast the spatial distribution and densities of the bugs under prevailing conditions at the beginning of each bug season. These results in-turn could be used for management purposes and for decision making as to where to direct resources for preventive action. A second, but linked, part of this project will use remote sensing tools and satellite images to develop early detection techniques for Dubas bug at broad scales. We will use images such as Quickbird (both panchromatic and multispectral) and/or the new 8-band WorldView images to map the spatial distribution of the bug, and possibly do this on a temporal scale as well to see the directions and speed of spread. We intend to use the new hyperspectral remote sensing techniques to develop early pre-visual detection of the Dubas bug. The output, especially the spatial distribution and spread images, will be used as inputs to the GIS-based predictive models.
More information about this project can be found in the following links and documents.
Preliminary Literature Review can be found at the following link:
Al Shidi, R.A., Kumar, L., Al Khatri, S.A.H., Albahri, M.M., Alaufi, M.S. (2018) Relationship of Date Palm Tree Density to Dubas Bug Ommatissus lybicus Infestation in Omani Orchards. Agriculture 2018, 8(5), 64; https://doi.org/10.3390/agriculture8050064
Al Shidi, R.A., Kumar, L., Al Khatri, S.A.H., Alaufi, M.S., Albahri, M.M. (2018) Does solar radiation affect the distribution of Dubas bug, Ommatissus lybicus de Bergevin, infestation in Oman. Agriculture 2018, 8(7), 107; https://doi.org/10.3390/agriculture8070107
Shabani, F., Kumar, L., Al Shidi, R.A., (2018) Impacts of climate change on infestations of Dubas bug (Ommatissus lybicus Bergevin) on date palms in Oman. PeerJ 6:e5545 https://doi.org/10.7717/peerj.5545
Al Shidi, R.A., Kumar, L., Al Khatri, S.A.H. (2019) Detecting Dubas Bug Infestations using High Resolution Multispectral Satellite Data in Oman. Computers in Electronics and Agriculture, 157(2019): 1-11. https://doi.org/10.1016/j.compag.2018.12.037
Al Shidi, R.A., Kumar, L., Al Khatri, S.A.H., Al-Ajmi, N. (2019) Ommatissus lybicus Infestation in Relation to Spatial Characteristics of Date Palm Plantations in Oman. Agriculture, 9(3), 50; https://doi.org/10.3390/agriculture9030050
Al Shidi, R., Kumar, L., Al-Khatri, S. (2019). Humid-Thermal Index for a New Management Approach of Ommatissus lybicus. Pest Management Science, https://doi.org/10.1002/ps.5422
Regional Coastal Susceptibility Assessment for the Pacific Islands
Funded by the Commonwealth of Australia
Collaborators: Professor Patrick Nunn, Professor Roger McLean, Dr Ian Eliot
More information about this project can be found in the following links and documents.
Nunn, P.D., Kumar, L., Eliot, I., McLean, R.F. (2016) Classifying Pacific islands. Geoscience Letters. 3: 7. DOI: 10.1186/s40562-016-0041-8
Kumar, L., Eliot, I., Nunn, P., Stul, T., McLean, R. (2018) An indicative index of physical susceptibility of small islands to coastal erosion induced by climate change: An application to the Pacific Islands. Geomatics, Natural Hazards and Risk, 9:1, 691-702. DOI:10.1080/19475705.2018.1455749. https://doi.org/10.1080/19475705.2018.1455749
Exposure of Coastal Assets to Climate Risks – Rapid Assessment
Funded by the Commonwealth of Australia
The results of the analysis indicate that 57% of all assessed built infrastructure is within 500m of the coast for the Pacific island countries. Nine percent, 11%, 16% and 21% fall within the 0-50 m, 50-100 m, 100- 200m and 200-500m intervals. The total replacement value of all built infrastructure assessed was US$27.7 billion, of which 79% by value fall within 500mof the coast.
More information about this project can be found in the following links and documents.
Kumar, L., Taylor, S. (2015) Exposure of coastal built assets in the South Pacific to climate risks. Nature Climate Change, 5: 992-996. DOI: 10.1038/NCLIMATE2702.
Climate Change Impacts on the Himalayan Region of Nepal
Collaborators: Pramod Lamsal, Dr Kishor Atreya
More information about this project can be found in the following links and documents.
Lamsal, P., Kumar, L., Shabani, F., Atreya, K. (2017) The greening of the Himalayas and Tibetan Plateau under climate change. Global and Planetary Change, 159(2017): 77-92. http://dx.doi.org/10.1016/j.gloplacha.2017.09.010
Lamsal, P., Kumar, L., Atreya, K., Pant, K. (2017) Vulnerability and impacts of climate change on forest and freshwater wetland ecosystems in Nepal: A review. Ambio, DOI 10.1007/s13280-017-0923-9
Lamsal, P., Kumar, L., Atreya, K. (2017) Historical evidence of climatic variability and changes, and its effect on high altitude regions: insights from Rara and Langtang, Nepal. International Journal of Sustainable Development & World Ecology, http://dx.doi.org/10.1080/13504509.2016.1198939
Lamsal, P., Kumar, L., Aryal, A., Atreya, K. (2018) Invasive alien plant species dynamics in the Himalayan region under climate change. Ambio, DOI: 10.1007/s13280-018-1017-z http://link.springer.com/article/10.1007/s13280-018-1017-z
Lamsal, P., Kumar, L., Aryal, A. Atreya, K. (2018) Future climate and habitat distribution of Himalayan Musk Deer (Moschus chrysogaster). Ecological Informatics, 44: 101-108. https://doi.org/10.1016/j.ecoinf.2018.02.004.
Lamsal, P., Kumar, L., Atreya, K. and Pant, K.P. (2018) Forest ecosystem services in Nepal: a review of research status, and predictions in the context of climate change. International Forestry Review, 20(4):506-537. https://doi.org/10.1505/146554818825240647
Mapping and Evaluating Long-Term Changes in Mangrove Species Composition and Distribution in the Sundarbans, Bangladesh
Collaborators: Manoj Kumar Ghosh, Dr Chandan Roy
More information about this project can be found in the following links and documents.
Ghosh, M.K., Kumar, L., Roy, C. (2017) Climate Variability and Mangrove Cover Dynamics at Species Level in the Sundarbans, Bangladesh. Sustainability, 9, 805; doi:10.3390/su9050805.
Ghosh, M., Kumar, L., Roy, C. (2016) Mapping long term changes in the mangrove species composition and distribution in the Sundarbans. Forests, 7, 305. doi:10.3390/f7120305
Ghosh, M., Kumar, L., Roy, C. (2015) Monitoring the Coastline Change of Hatiya Island in Bangladesh using Remote Sensing Techniques. ISPRS Journal of Photogrammetry and Remote Sensing, 101: 137-144. http://dx.doi.org/10.1016/j.isprsjprs.2014.12.009
Ghosh, M.K., Kumar, L., Langat, P. (2018) Mapping Tidal Channel Dynamics in the Sundarbans, Bangladesh, between 1974 and 2017, and Implications for the Sustainability of the Sundarbans Mangrove Forest. Environmental Monitoring and Assessment, 190(10):582. https://doi.org/10.1007/s10661-018-6944-4
Ghosh, M.K., Kumar, L., Langat, P.K. (2019) Geospatial modelling of the inundation levels in the Sundarbans mangrove forests due to the impact of sea level rise and identification of affected species and regions. Geomatics, Natural Hazards and Risk, 10(1): 1028-1046. https://doi.org/10.1080/19475705.2018.1564373
Impacts of climate change on farming systems and farm management in coastal areas of Bangladesh
Collaborators: Md Kamrul Hasan
Climate projections indicate a remarkable change in atmospheric conditions in the 21st century which will be largely unfriendly to agriculture. A more pressing warning is that future climate change may extend beyond the range of farmers’ experience. However, climate change impact assessment on individual crops alone cannot provide a clear picture of the impacts on farming systems. Accordingly, this research project addresses the following questions:
• What are the changes that have taken place in farming systems and farm management due to climate change?
• What could be the future farming systems and farm management strategies to a changing climate?
More information about this project can be found in the following links and documents.
Hasan, K., Kumar, L. (2019) Comparison between meteorological data and farmer perceptions of climate change and vulnerability in relation to adaptation. Journal of Environmental Management, 237(2019): 54-62. https://doi.org/10.1016/j.jenvman.2019.02.028
Hasan, M.K., Kumar, L., Desiere, S., D’Haese, M. (2018) Impact of climate-smart agriculture adoption on food security of coastal farmers in Bangladesh. Food Security, 10(4): 1073-1088. https://link.springer.com/article/10.1007%2Fs12571-018-0824-1