Environmental Niche Modelling with Desktop GARP for Wild Origanum vulgare L . (Lamiaceae) in Armenia


  • Armine Abrahamyan Daugavpils University (LV)
  • Arvids Barsevskis Daugavpils University (LV)




artificial intelligence framework, bitmap, predictive distribution, realized niche


Predicting species’ distributions has became one of the significant components of conservation biology in recent years. During the study, GARP (genetic algorithm) has been identified the key modelling technique for determining Origanum vulgare L. (Oregano, Lamiaceae) environmental niche in the Republic of Armenia. For over three consecutive years, from 2010-2013 it has been created relevant environmental layers through ESRI ArcGIS programs to be used with the plant actual distribution (occurrence records) as input data of GARP. In the result of the study, it has been produced the fundamental and realized niche and predictive habitat distribution of O. vulgare L. with Bitmap under the global climate change. Produced Bitmap illustrates that Oregano distributions would decrease mostly in the central regions due to environmental deterioration and climate change. This research could provide significant data for future conservation planning of wild Oregano in the Republic of Armenia.


Download data is not yet available.


Anderson RP, Lew D, Peterson AT, Evaluating predictive models of species’ distributions: criteria for selecting optimal models. Ecol Model, 2003, 162:211–232

Guisan, A., and W. Thuiller. 2005. Predicting species distribution: Offering more than simple habitat models. Ecology Letters 8, 993- 1009http://www.treehugger.com/cars/e-cars-and-busescharge-magically-with-underground-induction.html

Huntley, B., P.M. Berry, W. Cramer, and A.P. Mcdonald. Modelling present and potential future ranges of some European higher plants using climate response surfaces. Journal of Biogeography 22, 967-1001, 1995

IUCN, WHO, WWF (1993). Guidelines on the Conservation of Medicinal Plants, IUCN, Gland, Switzerland, 50 p.

Peterson AT, Uses and requirements of ecological niche models and related distributional models.Biodiversity Informatics, 2006, 3:59–72.

Peterson A.T. & Cohoon K.P. (1999). Sensitivity of distributional prediction algorithms to geographic data completeness. Ecological Modelling, 117, 159-164.

Austin, M. P. et al. 1990. Measurement of the realized qualitative niche: environmental niches of five Eucalyptus species. _ Ecol. Monogr. 60: 161_177.

Taghtajyan A. L., Flora of Armenia, VIII sector, National Academy of Sciences of Armenia, Botanical Institute, Yerevan, 1987, Pages 418








How to Cite

A. Abrahamyan and A. Barsevskis, “Environmental Niche Modelling with Desktop GARP for Wild Origanum vulgare L . (Lamiaceae) in Armenia”, ETR, vol. 3, pp. 7–10, Aug. 2015, doi: 10.17770/etr2013vol3.869.