پیوندهای مفید
آمار
| تعداد نشریات | 31 |
| تعداد شماره‌ها | 748 |
| تعداد مقالات | 7,112 |
| تعداد مشاهده مقاله | 10,245,997 |
| تعداد دریافت فایل اصل مقاله | 6,899,757 |
Impact of climatic parameters on the extent of mangrove forests of southern Iran | ||
| Caspian Journal of Environmental Sciences | ||
| دوره 20، شماره 4، دی 2022، صفحه 671-682 اصل مقاله (1.58 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22124/cjes.2022.5719 | ||
| نویسندگان | ||
| Fariba Rostami1؛ Pedram Attarod* 1؛ Hamidreza Keshtkar2؛ Mohammad Nazeri Tahroudi3 | ||
| 1Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Karaj, Iran | ||
| 2Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Karaj, Iran | ||
| 3Department of Water Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran | ||
| چکیده | ||
| Mangrove forests play a valuable role in maintaining the coastal ecosystem. Global warming alongside human activities has caused reduced extent and health of these ecosystems in recent years. This study aimed to examine the variability of the extent of mangrove forests and the sea surface area in response to changes in climatic parameters in the south of Iran. To achieve this, the climatic data recorded at Bandar Abbas Synoptic Weather Station and Landsat series of satellite images were used. To detect the trends of meteorological parameters during 1987-2017, the modified Man-Kendall test and the Sen’s slope estimator were employed. We investigated the regression relationship between climatic parameters as well as the sea surface area and the mangrove forest extent. The results showed that mangrove forest extent was about 73.08 km2 in the first year of study (1987), which increased to 88.73 km2 (21%) in 2017. The minimum temperature (Z = 2.77, β = 0.0186), maximum temperature (Z = 2.066, β = 0.0362), and the extent of the mangrove forests (Z = 2.58, β = 0.0405) displayed significantly growing trends. In contrast, the mean temperature, precipitation, relative humidity, and the sea surface area had no significant trends during the study period. The minimum temperature presented the highest correlation coefficient with the mangrove forest extent (61%). It is expected, therefore, along with global warming and increasing minimum temperature, the extent of mangrove forests would have a growing trend in the south of Iran in the future. The results of this study can be used by natural resources and forest managers to determine the best place for afforestation in order to perform better protection of these forests. | ||
| کلیدواژه‌ها | ||
| Climate change؛ Coastal ecosystem؛ Hormozgan؛ Landsat؛ Minimum temperature | ||
| مراجع | ||
|
Ahmadi, F, Nazeri Tahroudi, M, Mirabbasi, R, Khalili, K & Jhajharia, D 2018, Spatiotemporal trend and abrupt change analysis of temperature in Iran. Meteorological Applications, 25: 314-321.
Alemi Safaval, P, Kheirkhah Zarkesh, M, Neshaei, SA & Ejlali, F 2018, Morphological changes in the southern coasts of the Caspian Sea using remote sensing and GIS. Caspian Journal of Environmental Sciences, 16: 271-285.
Almahasheer, H, Aljowair, A, Duarte, C.M & Irigoien, X 2016, Decadal stability of Red Sea mangroves. Estuarine, Coastal and Shelf Science, 169: 164-172.
Alongi, DM 2015, The impact of climate change on mangrove forests. Current Climate Change Reports, 1: 30-39.
Armitage, AR, Highfield, WE, Brody, SD & Louchouarn, P 2015, The contribution of mangrove expansion to salt marsh loss on the Texas Gulf Coast. PloS one, 10: 0125404.
Asbridge, E, Lucas, R, Ticehurst, C & Bunting, P, 2016, Mangrove response to environmental change in Australia's Gulf of Carpentaria. Ecology and Evolution, 6: 3523-3539.
Asfaw, A, Simane, B, Hassen, A & Bantider, A 2018, Variability and time series trend analysis of rainfall and temperature in northcentral Ethiopia: A case study in Woleka sub-basin. Weather and Climate Extremes, 19: 29-41.
Attafi, R, Darvishi Boloorani, A, Fadhil Al-Quraishi, AM & Amiraslani, F 2021, Comparative analysis of NDVI and CHIRPS-based SPI to assess drought impacts on crop yield in Basrah Governorate, Iraq. Caspian Journal of Environmental Sciences, 19: 547-557.
Barros, DF & Albernaz, ALM 2014, Possible impacts of climate change on wetlands and its biota in the Brazilian Amazon. Brazilian Journal of Biology, 74: 810-820.
Carney, J, Gillespie, TW & Rosomoff, R 2014, Assessing forest change in a priority West African mangrove ecosystem: 1986–2010. Geoforum, 53: 126-135.
Cavanaugh, KC, Osland, MJ, Bardou, R, Hinojosa‐Arango, G, López‐Vivas, JM, Parker, JD & Rovai, AS 2018, Sensitivity of mangrove range limits to climate variability. Global Ecology and Biogeography, 27: 925-935.
Church, JA & White, NJ 2011, Sea-level rise from the late 19th to the early 21st century. Surveys in Geophysics, 32(4): 585-602.
Ellison, JC 2000, How South Pacific mangroves may respond to predicted climate change and sea-level rise. In: Climate change in the South Pacific: Impacts and responses in Australia, New Zealand, and small island states (pp. 289-300). Springer, Dordrecht.
Estoque, RC, Myint, SW, Wang, C, Ishtiaque, A, Aung, TT, Emerton, L, Ooba, M, Hijioka, Y, Mon, MS, Wang, Z & Fan, C 2018, Assessing environmental impacts and change in Myanmar's mangrove ecosystem service value due to deforestation (2000–2014). Global Change Biology, 24: 5391-5410.
Etemadi, H, Smoak, JM Sanders, C.J 2018, Forest migration and carbon sources to Iranian mangrove soils. Journal of Arid Environments, 157: 57-65.
Food and Agriculture Organization of the United Nations 2007, The world's mangroves, 1980-2005. FAO Forestry paper, 153 p.
Friess, DA, Krauss, KW, Horstman, EM, Balke, T, Bouma, TJ, Galli, D & Webb, EL, 2012, Are all intertidal wetlands naturally created equal? Bottlenecks, thresholds and knowledge gaps to mangrove and saltmarsh ecosystems. Biological Reviews, 87: 346-366.
Giri, S, Mukhopadhyay, A, Hazra, S, Mukherjee, S, Roy, D, Ghosh, S, Ghosh, T & Mitra, D 2014, A study on abundance and distribution of mangrove species in Indian Sundarban using remote sensing technique. Journal of Coastal Conservation, 18: 359-367.
Gomariz-Castillo, F, Alonso-Sarría, F & Cánovas-García, F 2017, Improving classification accuracy of multi-temporal Landsat Images by Assessing the Use of different algorithms, textural and ancillary information for a Mediterranean semiarid area from 2000 to 2015. Remote Sensing, 9: 1058.
Guo, H, Zhang, Y, Lan, Z & Pennings, SC 2013, Biotic interactions mediate the expansion of black mangrove (Avicennia germinans) into salt marshes under climate change. Global change biology, 19: 2765-2774.
Hamed, KH & Rao, AR 1998 A modified Mann-Kendall trend test for autocorrelated data. Journal of Hydrology, 204: 182-196.
Hamilton, SE & Casey, D 2016 Creation of a high spatio-temporal resolution global database of continuous mangrove forest cover for the 21st century (CGMFC‐21). Global Ecology and Biogeography, 25: 729-738.
Hu, L, Li, W & Xu, B 2018, Monitoring mangrove forest change in China from 1990 to 2015 using Landsat-derived spectral-temporal variability metrics. International Journal of Applied Earth Observation and Geoinformation, 73: 88-98.
Huang, J, Islam, AT, Zhang, F & Hu, Z 2017, Spatiotemporal analysis the precipitation extremes affecting rice yield in Jiangsu province, southeast China. International Journal of Biometeorology, 61: 1863-1872.
Jayanthi, M, Thirumurthy, S, Nagaraj, G, Muralidhar, M & Ravichandran, P 2018, Spatial and temporal changes in mangrove cover across the protected and unprotected forests of India. Estuarine, Coastal and Shelf Science, 213: 81-91.
Jennerjahn, TC, Gilman, E, Krauss, KW, Lacerda, LD, Nordhaus, I & Wolanski, E 2017, Mangrove ecosystems under climate change. In Mangrove ecosystems: a global biogeographic perspective (pp. 211-244). Springer, Cham.
Kendall, MG 1975, Rank correlation methods, Charles Griffin, Landon, UK.
Khoorani, A, Biniaz, M & Amiri, HR 2015, Investigating the changes of mangrove forests between Khamir Port and Gheshm Iseland and its correlation with climatic elements. Journal of Aquatic Ecology, 5: 100-111.
Lee, CKF, Duncan, C, Owen, HJF & Pettorelli, N 2018, A new framework to assess relative ecosystem vulnerability to climate change. Conservation Letters, 11: 12372.
López-Angarita, J, Roberts, CM, Tilley, A, Hawkins, JP & Cooke, RG 2016, Mangroves and people: Lessons from a history of use and abuse in four Latin American countries. Forest Ecology and Management, 368: 151-162.
Lovelock, CE, Feller, IC, Reef, R, Hickey, S & Ball, MC 2017, Mangrove dieback during fluctuating sea levels. Scientific Reports, 7: 1-8.
Mafi-Gholami, D, Mahmoudi, B & Zenner, EK 2017, An analysis of the relationship between drought events and mangrove changes along the northern coasts of the Persian Gulf and Oman Sea. Estuarine, Coastal and Shelf Science, 199: 141-151.
Mafi-Gholami, D, Zenner, EK, Jaafari, A & Ward, RD 2019, Modeling multi-decadal mangrove leaf area index in response to drought along the semi-arid southern coasts of Iran. Science of the Total Environment, 656: 1326-1336.
Mann, HB 1945, Nonparametric tests against trend. Econometrica, 13: 245-259.
Moazed, H, Salarijazi, M, Moradzadeh, M & Soleymani, S 2012, Changes in rainfall characteristics in Southwestern Iran. African Journal of Agricultural Research, 7: 2835-2843.
Murdiyarso, D, Purbopuspito, J, Kauffman, JB, Warren, MW, Sasmito, SD, Donato, DC, Manuri, S, Krisnawati, H, Taberima, S & Kurnianto, S 2015, The potential of Indonesian mangrove forests for global climate change mitigation. Nature Climate Change, 5: 1089-1092.
Osland, MJ, Feher, LC, Griffith, KT, Cavanaugh, KC, Enwright, NM, Day, RH, Stagg, CL, Krauss, KW, Howard, RJ, Grace, JB & Rogers, K 2017, Climatic controls on the global distribution, abundance, and species richness of mangrove forests. Ecological Monographs, 87: 341-359.
Pachauri, RK, Allen, MR, Barros, VR, Broome, J, Cramer, W, Christ, R, et al., 2014, Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC), p. 151.
Parida, AK, Tiwari, V & Jha, B 2014, Impacts of climate change on Asian mangrove forests. In: Mangrove ecosystems of Asia, Springer, New York, NY, p. 233-256.
Pham, LT, Vo, TQ, Dang, TD & Nguyen, UT 2019, Monitoring mangrove association changes in the Can Gio Biosphere Reserve and implications for management. Remote Sensing Applications: Society and Environment, 13: 298-305.
Richards, DR & Friess, DA 2016, Rates and drivers of mangrove deforestation in Southeast Asia, 2000–2012. Proceedings of the National Academy of Sciences, 113(2): 344-349.
Sen, PK 1968, Estimates of the regression coefficient based on Kendall's tau. Journal of the American Statistical Association, 63(324): 1379-1389.
Sippo, JZ, Lovelock, CE, Santos, IR, Sanders, CJ & Maher, DT 2018, Mangrove mortality in a changing climate: An overview. Estuarine, Coastal and Shelf Science, 215: 241-249.
Soltaninejad, M, Jafari, M, Noroozi, A & Javadi, SA 2020, Evaluation of vegetation changes in desertification projects using remote sensing techniques in Bam, Shahdad and Garmsar regions, Iran. Caspian Journal of Environmental Sciences, 19: 47-51.
Srivastava, PK, Mehta, A, Gupta, M, Singh, SK & Islam, T 2015, Assessing impact of climate change on Mundra mangrove forest ecosystem, Gulf of Kutch, western coast of India: A synergistic evaluation using remote sensing. Theoretical and Applied Climatology, 120: 685-700.
Thakkar, AK, Desai, VR, Patel, A & Potdar, MB 2017, Post-classification corrections in improving the classification of Land Use/Land Cover of arid region using RS and GIS: The case of Arjuni watershed, Gujarat, India. The Egyptian Journal of Remote Sensing and Space Science, 20: 79-89.
Theil, H 1992, A Rank-Invariant Method of Linear and Polynomial Regression Analysis. In: B, Raj & J, Koerts (Eds.), Henri Theil’s Contributions to Economics and Econometrics: Econometric Theory and Methodology. Springer, Dordrecht Netherlands, pp. 345-381
Toosi, NB, Soffianian, AR, Fakheran, S, Pourmanafi, S, Ginzler, C & Waser, LT 2019, Comparing different classification algorithms for monitoring mangrove cover changes in southern Iran. Global Ecology and Conservation, 19: 00662.
Uddin, MS, Shah, MAR, Khanom, S & Nesha, MK 2013, Climate change impacts on the Sundarbans mangrove ecosystem services and dependent livelihoods in Bangladesh. Asian Journal of Conservation Biology, 2(2): 152-156.
Ward, RD, Friess, DA, Day, RH & MacKenzie, RA 2016, Impacts of climate change on mangrove ecosystems: a region by region overview. Ecosystem Health and Sustainability, 2: 01211.
Wolanski, E & Elliott, M 2015, Estuarine ecohydrology: an introduction. Elsevier.
Yevenes, MA, Figueroa, R, Parra, O & Research, P 2018, Seasonal drought effects on the water quality of the Biobío River, Central Chile. Environmental Science and Pollution Research 25(14): 13844-13856.
Zahed, MA, Rouhani, F, Mohajeri, S, Bateni, F & Mohajeri, L 2010, An overview of Iranian mangrove ecosystems, northern part of the Persian Gulf and Oman Sea. Acta Ecologica Sinica, 30: 240-244. | ||
|
آمار تعداد مشاهده مقاله: 841 تعداد دریافت فایل اصل مقاله: 1,025 |
||