Presenting an Early Warning System to Supply the Protected Areas with Ecological Security (Case Study: Darmiyan Protected Area, East of Iran)

Document Type : Research Article

Authors

1 College of Environment

2 College of Enviroment

Abstract

Introduction

Protected areas (PAs) are the basis of biodiversity protection. Societies invest in utilizing, managing, and protecting the primary roles of the PAs. Thus, performing management plans need much time, cost, and workforce by the increase in number and area of the PAs in recent years. In this research, the early warning system (EWS) is proposed as a solution to decrease the management cost of PAs and other significant and inaccessible areas. EWS is a general idea that can be used as a useful and cheap tool to ease the access to primary global strategic goals of protection of stable development. In some studies, it is attempted to utilize the EWS to describe biological mobility, environmental elements related to ecological security, to prevent the loss of resources in environmental disasters, and to decrease the flood damage. This study is based on research RS_GIS research and the pressure-status-response (P-S-R) model on the ecological security status in Darmiyan PA, located in the eastern part of Iran. The primary goal of this paper is to present the EWS for in time and appropriate monitoring, maintaining the mobility in relations, and preserving the health of the ecosystem of PAs.

Materials and methods

 In this study, it is attempted to determine the ecological security index (ESI) of Darmiyan PA according to the P-S-R model to propose the EWS with the aid of this index for the study area. In this approach, 12 environmental indicators in three categories of pressure (the average annual temperature, annual precipitation, fragmentation, the hunter presence risk), status (distance from human-made areas, distance from farms, cover vegetation status, soil brightness, finite rate of increase wildlife), and response (the increment rate of governmental financing in the region, the Incompatibility percentage of the region with protection use, utilization and development of technology in protection) were chosen. These indicators were measured by the images of TM and OLI sensors of the LANDSAT satellite, DEM Aster, thermal data of Modis from the earth surface, and statistics and information of the environmental and meteorology organizations of South Khorasan. The ESI for each of the 30-meter pixels of the study area was determined by the Multivariate Composite Estimator (MCE) method using Weighted Linear Combination (WLC). According to the defined features for the EWS indicators, the leading and final indicators to act on the EWS system were chosen using decomposition to main components and multivariate regression. Finally, with the calculation of the thirty-year average of the mentioned indicators in the study area, the confidence interval for each of these indicators with the confidence factor of %95 was achieved.

Results and Discussion

The results declared that the average ESI changed from 0/315 in the year 2000 to 0/518 in the year 2014. Checking the variance plot of the standard value of the useful indicators in ESI declared that except three indicators of distance from human-made areas, distance from farms, and the incompatibility percentage of the region with protection use, the other indicators held a better status in 2014 in comparison to the year 2000. These results represent the practical impact of protection and management in the region. However, the decrease in the standardized value of the three mentioned indicators declares the lack of attention to the exceptions of the PA and the increasing trend of land tenure in the study area.
Location changes in the ESI of a particular year have a close relation to the land shape. In the under study area, as we move from the flat areas to the heights, the ESI increases. Studying the categorized map of the sensitivity of the study area in 2014 indicated that 95 percent of the study area is located in medium and high sensitivity categories. The living locations of urials wild sheep in this map indicated that this species had chosen areas with medium and low sensitivity where are hilly with high ecological security to live.
Three indicators, including annual precipitation, cover vegetation status, and soil brightness, were chosen as the appropriate indicators to be utilized in the EWS of Darmiyan PA. While monitoring, the warning areas in the study area were determined by studying the status of these three indicators. This EWS was utilized in the study area in 2014. Based on the results, some parts of south-west and east of the area have been subject to danger. After determining the vulnerable areas, the operation accuracy of the proposed EWS was assessed using the field visit. This system had good accuracy. With the presented approach, one can have regular monitoring of the critical and inaccessible areas. This approach is practical with its minimum cost in optimum and oriented managing of Pas even though the choice of general and useful indicators in ecological security remains the most crucial part of this approach.

Conclusions

In this research, one can see a reduction in managing expenses through the use of technology. The effective indicators on the ecological security of an area with a semi-arid climate are proposed. This research helps the ecosystem existence of the areas where they are the habitat to international species. In this study, the minimum number of indicators was used for a warning system even though the necessity for research on a warning system with more indicators and comparison with the presented results remains considerable. We believe this research is an appropriate starting point for discussion on the use of the warning system for essential and inaccessible areas of all around the world.

Keywords


میرزا قادری، قادر. مرادی، محمد. فلاح، افشین؛ 1389. مقدمه‌ای بر آمار و احتمال. چاپ. سنندج: انتشارات دانشگاه کردستان
Badji, M., & Dautrebande, S., 1997. Characterization of flood inundated areas and delineation of poor drainage soil using ERS-1 SAR imagery. Hydrological Processes, 11(10), 1441–1450. https://doi.org/10.1002/(SICI)1099-1085(199708) 11:10<1441::AID-HYP527>3.0.CO;2-Y.
Barlindhaug, S., Holm-olsen, I. M., & Tòmmervik, H., 2007. Monitoring archaeological sites in a changing landscape-using multitemporal satellite remote sensing as an “Early Warning” method for detecting regrowth processes. Archeological Prospection, 244(May), 231–244. https://doi.org/10.1002/arp.
Clarke, G. M., 1995. Relationships between developmental stability and fitness: Application for conservation biology. Conservation Biology, 9(1), 18–24. https://doi.org/10.1046/j.1523-1739.1995.09010018.x.
EarthExplorer., n.d.. Retrieved April 17, 2015, from https://earthexplorer.usgs.gov/. Forleo, M. B., & Palmieri, N., 2018. A framework for assessing the relational accessibility of protected areas. Journal of Cleaner Production, 194, 594–606. https://doi.org/10. 1016/j.jclepro.2018.05.149.
Giulio, M. Di, Holderegger, R. & Tobias, S. )2009(. Effects of habitat and landscape fragmentation on humans and biodiversity in densely populated landscapes. Journal of Environmental Management, 90(10), 2959–2968. http:// dx.doi.org/ 10.1016/ j.jenvman. 2009.05.002.
Haji-kazemi, S., Andersen, B., Eleftheriadis, R., & Capellan, A., 2015. The early warning procedure in an international context. Procedia - Social and Behavioral Sciences, 194(1877), 85–95. https://doi.org/10.1016/j.sbspro.2015.06.122. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A., 2005. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25(15), 1965–1978.
Hockey, P. A. R., & Curtis, O. E., 2009. Use of basic biological information for rapid prediction of the response of species to habitat loss. Conservation Biology, 23(1), 64–71. https://doi.org/10.1111/j.1523-1739.2008.01028.x.
Hua, Y.E., Yan, M.A., & Limin, D., 2011. Land ecological security assessment for Bai autonomous Prefecture of Dali based using PSR model-with data in 2009 as Case, 5, 2172–2177.
Iverson, L. R., & Prasad, A. M., 2007. Using landscape analysis to assess and model tsunami damage in Aceh province, Sumatra. Landscape Ecology, 22(3), 323–331. https://doi.org/10.1007/s10980-006-9062-6.
LAADs DAAC., n.d.. Retrieved July 8, 2015, from https://ladsweb.modaps.eosdis.nasa. gov/Leverington, F., Costa, K. L., Courrau, J., Pavese, H., Nolte, C., Marr, M., et al., 2010.Management effectiveness evaluation in protected areas – A global study. 87. https://doi.org/10.1007/s00267-010-9564-5.
Li, X., Lao, C., Liu, Y., Liu, X., Chen, Y., Li, S., et al., 2013. Early warning of illegal development for protected areas by integrating cellular automata with neural networks. Journal of Environmental Management, 130, 106–116. https://doi.org/10. 1016 /j.jenvman. 2013. 08.055.
Li, Y., Sun, X., Zhu, X., & Cao, H., 2010. An early warning method of landscape ecological security in rapid urbanizing coastal areas and its application in Xiamen, China. Ecological Modelling, 221(19), 2251–2260. https://doi.org/10.1016/j.ecolmodel. 2010.04.016.
Saadat, H., Adamowski, J., Tayefi, V., Namdar, M., Sharifi, F., & Ale-Ebrahim, S., 2014. A new approach for regional scale interrill and rill erosion intensity mapping using brightness index assessments from medium resolution satellite images. Catena, 113, 306–313. https://doi.org/10.1016/j.catena.2013.08.012.
Sinclair, A. R. E., Fryxell, J. M., & Caughley, G., 2006. Wildlife Ecology, Conservation, and Management. Management.
Tegler, B., Sharp, M., & Johnson, M. A., 2001. Ecological monitoring and assessment network's proposed core monitoring variables: An early warning of environmental change. Environmental Monitoring and Assessment, 67(1–2), 29–56. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-0035075092& partnerID=40&md5=fdf2a7670c7620e7f07fc7d883982890.
Wang, H., Long, H., Li, X., & Yu, F., 2014. Evaluation of changes in ecological security in China’s Qinghai Lake Basin from 2000 to 2013 and the relationship to land use and climate change. Environmental Earth Sciences, 72(2), 341–354. https://doi.org/10. 1007/s12665-013-2955-1
Williams, D.G., Evans, R.D., West, J.B., & Ehleringer, J.R., 2007. Applications of stable isotope measurements for early [hyphen(true graphic)] warning detection of ecological change,383–398.
Xiuping, Z., Shaofeng, C., & Qingwen, Q., 2000. A research on the assessment of regional ecological security. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.
Yu, G., Zhang, S., Yu, Q., Fan, Y., Zeng, Q., Wu, L., et al., 2014. Assessing ecological security at the watershed scale based on RS/GIS: A case study from the Hanjiang River Basin. Stochastic Environmental Research and Risk Assessment, 28(2), 307–318. https://doi.org/10.1007/s00477-013-0750-x.
Zhao, Y. Z., Zou, X. Y., Cheng, H., Jia, H. K., Wu, Y. Q., Wang, G. Y., et al., 2006. Assessing the ecological security of the Tibetan plateau: Methodology and a case study for Lhaze County. Journal of Environmental Management, 80(2), 120–131. https:// doi.org/ 10.1016/ j.jenvman.2005.08.019.
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