Did you Know?
  • The Lappet-faced Vulture, a regular winter visitor to the DDCR, has a wingspan of 2.5-3 metres (8-10 feet)

Seasonal Dynamics of Herd Structure of Re-introduced Arabian Oryx in the Dubai Desert Conservation Reserve, United Arabian Emirates

Project Summary

Arabian oryx (Oryx leucoryx, Pallas, 1777) is the largest species of antelope on the Arabian Peninsula. This magnificent animal was only saved from extinction through a captive breeding program and reintroduction to the wild. In Dubai Desert Conservation Reserve (UAE) antelope was successfully re-introduced in the 1999. Already in 2011 status of Arabian oryx according to the IUCN Red List was changed from “Extinct in the wild” to “Vulnerable”.

Until 2019, the population of Arabian oryx on the area of Conservation Reserve substantially increased (Lignereux, Alzahlawi, Al Kharusi and Pesci, 2018), however the knowledge on the dynamics in time and seasons is limited. Monitoring species abundance and distribution is a prerequisite when assessing species status and population viability. That is why the present research is needed. To describe the dynamics of Arabian oryx population around feeding points, water holes, and on natural location (untouched); to understand the herd structure and influences driven by natural or artificial factors – all these are essential for successful development of management plan of protected area.

The main goal of the project is to identify the population dynamics over a selected time in relation to seasons, climatic conditions, locations and management measures (i.e. mobile feeding and water points). The period between 2009 and 2019 will be the main focus of the research. This timescale has close connection to present condition of the animal population and will help to prognoses the future population trend.

Research Objectives

  • To identify density changes of re-introduced semi-wild population of Arabian oryx on the area of DDCR for the period 2009-2019.
  • To treat available data from DDCR archive: images from camera traps, bio expedition reports; personal observation reports; climate stations.
  • To identify the herd structure and activity patterns using the data from camera traps at different type of location within DDCR for the period 2009-2019.
  • To interpret the Arabian oryx density and herd structure in relation to climate events using the data from climate stations throughout the investigated period.
  • To analyze the continuos data from 2011 year with random camera trap distribution to determine the population dynamics. Compare population trends with discrete data from other years and locations.


  • In 2019, there are approx. 400 Arabian Oryx on the territory of DDCR. Eight of them have been equipped by GPS-collars, data from which are archived in the database of the DDCR. There is a collection of about 10,000 images from camera traps for the period from 2009 - 2019. Among these images, photos of Arabian Oryx will be identified and analyzed using custom computer based learning TensorFlow API and Python, Imagej, and CLIQS software packages. In the first stage of data processing, data from camera traps and climate station for the winter months 2019 will be mined and analyzed. Parameters such as number of individuals on the picture, their sex and age class (adult vs. calf), and activity will be recoded. The first analyze will show which approach and software design is the most suitable to reach the project goal.
  • Personal observation at feeding and water stations will verify the assumptions about the herd structure and interpretations of activities recorded on pictures. To increase personal experience and gain real practical knowledge, skills and attitudes field work will be consisting of: bio expedition experience (non-invasive monitoring of animal), weekly observation and calculation of Arabian Oryx at DDCR, study visits to local centers, where Arabian Oryx breed in captivity. To understand the terrain characteristic in real time (and as result - cover more behavioral patterns within different climatic conditions) field work will be splitted into 2 periods: summer and winter. Personal present in the office of DDCR will be helpful as well during the computing analyze of data with supervision of DDCR experts.
  • Data from climate stations will provide information about the regular climate pattern and unusual climatic events on the territory from 2009-2019. The animal density dynamics will be tested for the effects of climatic parameters using relevant statistical procedures. Finally, the results of animal density and spatial distribution of feeding and water points will be visualized using tools in ArcGIS Pro software (e.g. Space Time Cube).
  • Understanding of seasonal dynamic of herd structure and its dependence on natural, artificial factors will provide DDCR team with essential information for further managerial decisions.
  • The analyze of managerial decisions (dislocation of feeding points) in the period of 2009-2019 will help to create the map of already-used and non-used plots on the DDCR area. This map will give a base to conservation management plan for future decision.

Expected Outcomes

  • Information about seasonal dynamic of herd structure for the period 2009-2019 will be analyzed and prognosis of future population dynamic will be formulated. Effects of climate conditions on animal dynamics throughout the time period (2009-2019) will be visualized via Space Time Cube in ArcMap.
  • Data findings at completion will be presented to the research committee in the form of presentation.
  • Research results, as well as general research project outline will be organized as visual content of digital poster. Poster can be published on official website, media channels of DDCR.
  • The recommendation to Management Conservation Plan will be made, based on the information about seasonal dynamic of herd structure and its dependence on natural, artificial factors.
  • Final results of research will be presented to the academic community of Czech University of Life Science (Prague) in the form of presentation.