Modelling actual and potential natural vegetation types: an approach to support the ecological restoration and conservation programmes in Jordan
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Date
07/06/2022Item status
Restricted AccessEmbargo end date
07/06/2023Author
Taifour, Hatem
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Abstract
Lying at the junction of Africa, Asia, and the Mediterranean, Jordan is home to a range
of diverse and unique vegetation. The country also boasts some of the oldest
anthropogenic landscapes in the world due to its location within the Fertile Crescent
region. In modern times, however, the area is experiencing significant change due to
increasing populations and anthropogenic threats on one hand, and a lack of
appropriate planning for the preservation and management of ecosystems on the
other. Jordan’s environmental sustainability is also threatened by climate change
which increases the vulnerability of many plant species. In the Jordanian context, the
application of concepts such as potential, climax, and pristine natural vegetation is
difficult as the region has been managed heavily for hundreds of years and mature
vegetation is now sparse. Vegetation modelling is desperately needed for agriculture,
afforestation, and rangeland management planning and to limit degradation of habitats
in Jordan.
Most of the existing studies on Jordanian vegetation are insufficient or inadequate in
that they often do not take advantage of state-of-the-art satellite imaging and fail to
include comprehensive field observations to support mapping of the regions being
investigated. Thus, the objective of this study was to model both the current and
potential vegetation in Jordan in order to help develop appropriate ecological
conservation and restoration programmes in the country. To fulfil this objective,
datasets were collected from sampling plots in various habitats and vegetation types,
and from satellite images. Then, the data were analysed and interpreted using
different state-of-the-art techniques and software.
Firstly, hierarchical cluster analysis was used to distinguish vegetation types. This
analysis enabled the classification of 16 vegetation types based on the species
composition of their perennial vegetation. A reciprocal illumination approach between
on-the-ground sampling and satellite imagery was then employed to define the types
of vegetation, with datasets obtained from 18 cloud-free Sentinel-2A images. Sentinel
remote sensing and GIS software were used to derive a land use/land cover map from
high resolution images based on spectral characteristics of the main vegetation types,
as verified from the ground data. Prior to field work, an unsupervised map classifying
18 different land use/land cover categories was derived. Based on the updated land
use/land cover map, decisions were made regarding where field sampling and ground-based verification was needed. Extensive field experience supported a supervised
classification process and the interpretation of satellite images to translate the spectral
characteristics into vegetation types. Finally, a vegetation map was produced
containing 18 vegetation types. Based on additional information collected during field
work, 10 maps were made to illustrate the spatial distribution of human threat to
vegetation and its level of impact on habitats.
Secondly, species distribution modelling (SDM) was used to predict potential natural
vegetation (PNV) in the present-day and the future. Relevant data including indicator
species occurrences, climatic data, and topographic data were selected and analysed
using presence-only distribution models implemented in the MaxEnt software. This
enabled the prediction of the present-day potential distribution of vegetation types. To
predict future potential distribution of vegetation, five future climate models were used
with three differing carbon emission scenarios for two time periods: 2041-2060 and
2081-2100. Results show a predicted increase in the suitable habitat areas in 2060
and 2100 for some vegetation types: Garrigue and Batha Vegetation, Gravel
Hammada Vegetation and Sandy Gravel Hammada Vegetation with Hammada
scoparia; Pine and Deciduous Oak Forests in the northwest; Sand Dune Vegetation;
and Saline and Thermophilous Vegetation. Conversely, there is a predicted decrease
in suitable habitat areas for the same time period for Steppe Vegetation, Juniper and
Evergreen Oak Forests, Acacia Woodland, Granite and Sandstone Shrubland, Mudflat
Vegetation, Runoff Hammada Vegetation, and Sandy Gravel Hammada Vegetation
with Vachellia gerrardii & Artemisia judaica. The ultimate goal of producing these
predictive maps was to identify the areas of priority for ecological restoration, review
the current boundaries of protected areas, and propose new reserves. The study’s
findings are vital for the management, protection, and sustainable utilisation of
vegetation in Jordan, with the overall aim of addressing the challenges associated with
climate change.
Thirdly, results of SDMs were used to identify areas where climate change likely will
have little or no impact on vegetation types; these areas are the most appropriate
locations for ecological restoration and protection. The established and proposed
protected areas network declared by the Government of Jordan were compared with
the maps of natural vegetation and potential natural vegetation in order to determine
whether the protected areas network will protect the distribution of vegetation types,
both in the present-day and in the future. To prioritise conservation areas, a
degradation map was used in order to target the most threatened areas. Lastly, the
areas that should be targeted by ecological restoration initiatives were identified and
used as the basis of a proposal to create eight new protected areas, and to expand
the boundaries of eight other existing protected areas.