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Newcastle University (2015)

Environmental determinants of the ecology and distribution of Acacia tortilis under arid conditions in Qatar

Alsafran, Mohammed Hussain S. A.

Titre : Environmental determinants of the ecology and distribution of Acacia tortilis under arid conditions in Qatar

Auteur : Alsafran, Mohammed Hussain S. A.

Université de soutenance : Newcastle University

Grade : Doctor of Philosophy (PhD) 2015

Résumé partiel
Scrub or woodland communities dominated by Acacia tortilis form one of the few tree-dominated natural ecosystems in the hyper-arid climate of Qatar, making it a very important tree species that provides an essential habitat both for native animals and domestic livestock. However, the conservation and sustainable management of this tree has so far been neglected and it is now severely impacted by overgrazing and wood fuel collection. This research investigates the main environmental, ecological and management factors affecting the growth and distribution of Acacia tortilis in Qatar, including the factors affecting its regeneration. It also aims to guide the implementation of conservation programmes and development of a strategy to forestall deforestation and prevent the extinction of Acacia tortilis in Qatar. Initially, field survey, remote sensing and GIS techniques, together with univariate and multivariate statistical modelling techniques, were used to explore environmental influences on distribution of A. tortilis in Qatar at a national scale. Different vegetation indices (VIs), normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), were derived for a time series of Landsat TM/ETM+ images for 1998 and 2010 and tested using ground-truth data to explore the temporal dynamics of Acacia-dominated ecosystems which indicated substantial reduction in vegetation greenness in 2010 than 1998. The initial approach had limited success due to difficulties of identifying Acacia tortilis communities accurately on satellite images due to the sparsity of tree cover and indicates the limitations of using remote sensing methods for tracing vegetation dynamics in Qatar and similar arid and hyper arid environments. The multinomial logistic regression model has a superior ability to predict Acacia distribution and is a suitable method in the prediction of the occurrence of different vegetation types. Phytogeographical investigations of the environmental and biotic factors that control the distribution of the Acacia tortilis at a local scale, in both areas protected and unprotected from human land use impacts, demonstrate that topographic factors and their control on soil and water conditions are fundamental determinants.

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