Scholarly record
MODELING OF RANGELAND ECOSYSTEMS IN NORTHERN JORDAN
Abstract
Grasslands is globally important vegetation type for providing feed resources for grazing animals. An improved understanding of the factors affecting the long-term productivity of the ecosystems will be beneficial, as well as to developing a better understanding of the role these ecosystems play in global environmental change. Arid and semi-arid Mediterranean grasslands provide valuable forage for grazing animals in the eastern part of the Mediterranean area and have been subjected to long-term unsustainable grazing practices, leading to degeneration of productivity and impacts plant community structure. The present study aimed to discover the validity of using Phytomass Growth Simulator Model (Phygrow) to simulate arid grassland ecosystems. The purpose is to build a Phygrow simulation model that can accurately estimate important eco-hydrological processes in arid grassland ecosystems. The weather parameter was taken from the NASA (National Aeronautics and Space Administration). Important vegetation parameters and other key processes were simulated during the period 1981-2021 using the Phygrow model. The simulation was conducted for a grassland community within the Jordan University of Science and Technology JUST Campus. The model was able to reproduce all the general trends found in the study area, where peak growth is reached during the spring and ceased during the summer for annual spring growing species. The model has been successfully able to simulate leaf area index, evapotranspiration, soil moisture, leaf water storage, water stress, and temperature stress from 1981 to 2021.
Publication Impact Profile
Publication details
References13
Alhamad, M. N., & Alrababah, M. A., 2013. The impacts of biologically induced micro-environments on biodiversity in a dry Mediterranean grassland. Plant Ecology & Diversity, 6(2), 279-288. DOI: 10.1080/17550874.2013.773105
Alhamad, M., Stuth, J., & Vannucci, M., 2007. Biophysical modelling and NDVI time series to project near-term forage supply: spectral analysis aided by wavelet denoising and ARIMA modelling. Int. J. of Remote Sensing, 28(11), 2513-2548. DOI: 10.1080/01431160600954670
Alhamad, M.N. 2020. Life forms interactions in semiarid Mediterranean annual grassland community. Flora Mediterranea, 30, 197-205. DOI: 10.7320/flmedit30.195
Angerer, J., 2018. Phytomass Growth Model PHYGROW Blackland Research & Extension Center, 2. Doi:blackland.tamu.edu
Borner, K., Boyack, K.W., Milojevic, S. and Morris, S., 2012. An introduction to modeling science: Basic model types, key definitions, and a general framework for the comparison of process models. In Models of science dynamics (pp. 3-22). Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-23068-4_1
Fakhimi E., Arzani, H. and Soltani, M., 2019. Evaluation of Water Balance Model Performance in Estimation of Long Range Rangeland Production (Case Study: Steppe Rangelands of Yazd Mountain Basin). Journal of Rangeland, 12(4), 519-530.
Gaber, N., Foley, G., Pascual, P., Stiber, N., Sunderland, E., Cope, B., Nold, A. and Zaleem, Z., 2009. Guidance on the development, evaluation, and application of environmental models. Doi:www.epa.gov/crem
GLEWS [Global Livestock Early Warning System]. 2013. GLEWS home page. http://glews. tamu.edu. Accessed 21 August 2013.
Maria, A., 1997. Introduction to modeling and simulation. Paper presented at the Proceedings of the 29th conference on Winter simulation (pp. 7-13). DOI: 10.1145/268437.268440
Matere, J., Simpkin, P., Angerer, J., Olesambu, E., Ramasamy, S., & Fasina, F., 2020. Predictive Livestock Early Warning System (PLEWS): Monitoring forage condition and implications for animal production in Kenya. Weather and Climate Extremes, 27, p. 100209. DOI: 10.1016/j.wace.2019.100209
Strohmeier, S., Fukai, S., Haddad, M., AlNsour, M., Mudabber, M., Akimoto, K., Yamamoto, S., Evett, S. and Oweis, T., 2021. Rehabilitation of degraded rangelands in Jordan: The effects of mechanized micro water harvesting on hill-slope scale soil water and vegetation dynamics. Journal of Arid Environments, 185, p.104338. DOI: 10.1016/j.jaridenv.2020.104338
Stuth, J.W., D. Schmitt, R.C. Rowan, J.P. Angerer, and K. Zander., 2003. Phygrow user�s guide and technical documentation. Texas A&M University, College Station, USA. Accessed 13 June 2014.
Suleiman, A., Al-Bakri, J., Duqqah, M. and Crago, R., 2008. Intercomparison of evapotranspiration estimates at the different ecological zones in Jordan. Journal of Hydrometeorology, 9(5), pp.903-919 DOI: 10.1175/2008jhm920.1
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.

