Probability assessment of climate change impacts on soil organic carbon stocks in future periods: a case study in Hyrcanian forests (Northern Iran)

  • Rosa Francaviglia
  • Azam SoleimaniEmail author
  • Ali Reza Massah Bavani
  • Seyed Mohsen Hosseini
  • Mostafa Jafari
Original Paper


Simulations of soil organic carbon (SOC) stocks under climate change are partly subject to uncertainties deriving from the Global Climate Models (GCMs) used for weather projections of future climates. For this reason, SOC simulations are generally performed with a set of GCMs to avoid misleading results. SOC stocks were measured in different land covers in a forest area of Northern Iran (maple, alder, oak, cypress and a mixed natural forest), and the model RothC was used to predict SOC changes under climate change scenarios. We studied the effects on SOC stock changes deriving from an ensemble of nine GCMs and two Representative Concentration Pathways (RCPs), projected on four future periods (FPs) of 20 years between 2020 and 2099. The frequency analysis of SOC stock changes indicated a different effect of the GCMs/RCPs ensemble in the four future periods, with patterns showing more evident nonlinear probabilities of SOC changes in the 2030s and 2050s compared to the almost linear probabilities in the remaining future periods. This would imply that the effect of the GCMs/RCPs ensemble is more important in very close and intermediate future scenarios (the 2030s and 2050s) compared to fully realized climate change scenarios (the 2070s and 2090s). Results indicated the need to provide assistance in the management strategies in the reforestation sector in close and intermediate climate change scenarios. In fact, maple and quercus plantations had the highest probability of cumulated SOC change proving more sensitive to climate change. Conversely, cypress and alder plantations could limit the decrease of SOC stocks representing a good option for GHG mitigation in close and intermediate climate change scenarios and should be preferred in the afforestation of the degraded natural forest, and in mixed plantation systems within maple and oak stands.


Global Climate Models Representative Concentration Pathways RothC Soil organic carbon 



The paper is part of Azam Soleimani PhD thesis at Tarbiat Modares University.


  1. Ahmadzadeh Araji H, Wayayok A, Massah Bavani AR, Amiri E, Abdullah AF, Daneshian J, Teh CBS (2018) Impacts of climate change on soybean production under different treatments of field experiments considering the uncertainty of general circulation models. Agric Water Manag 205:63–71. CrossRefGoogle Scholar
  2. Ahmed M, Stöckle CO, Nelson R, Higgins S (2017) Assessment of climate change and atmospheric CO2 impact on winter wheat in the Pacific Northwest using a multimodel ensemble. Front Ecol Evol 5:51. CrossRefGoogle Scholar
  3. Anonymous (2008) Natural resources of Iran. Forests, Range and Watershed Management Organization, Engineering Office, Tehran (in Persian)Google Scholar
  4. Binkley D, Giardina C (1998) Why do tree species affect soils? The warp and woof of tree-soil interactions. Biogeochemistry 42:89–106CrossRefGoogle Scholar
  5. Boorman DB, Sefton CEM (1997) Recognizing the uncertainty in the quantification of the effects of climate change on hydrological response. Clim Change 35(4):415–434. CrossRefGoogle Scholar
  6. Brilli L, Bechini L, Bindi M, Carozzi M, Cavalli D, Conant R, Dorich CD, Doro L, Ehrhardt F, Farina R, Ferrise R, Fitton N, Francaviglia R, Grace P, Iocola I, Klumpp K, Léonard J, Martin R, Massad RS, Recous S, Seddaiu G, Sharp J, Smith P, Smith WN, Soussana JF, Bellocchi G (2017) Review and analysis of strengths and weaknesses of agro-ecosystem models for simulating C and N fluxes. Sci Total Environ 598:445–470. CrossRefPubMedGoogle Scholar
  7. Brisson N, Mary B, Ripoche D, Jeuffroy MH, Ruget F, Nicoullaud B, Gate P, Devienne-Barret F, Antonioletti R, Durr C, Richard G, Beaudoin N, Recous S, Tayot X, Plenet D, Cellier P, Machet JM, Meynard JM, Delécolle R (1998) STICS: a generic model for the simulation of crops and their water and nitrogen balance. I. Theory and parameterization applied to wheat and corn. Agronomie 18:311–346. CrossRefGoogle Scholar
  8. Cammarano D, Rivington M, Matthews KB, Miller DG, Bellocchi G (2017) Implications of climate model biases and downscaling on crop model simulated climate change impacts. Eur J Agron 88:63–75. CrossRefGoogle Scholar
  9. Cerri CEP, Coleman K, Jenkinson DS, Bernoux M, Victoria R, Cerri CC (2003) Modeling soil carbon from forest and pasture ecosystems of Amazon, Brazil. Soil Sci Soc Am J 67:1879–1887. CrossRefGoogle Scholar
  10. Cerri CEP, Easter M, Paustian K, Killian K, Coleman K, Bernoux M, Falloon P, Powlson DS, Batjes N, Milne E, Cerri CC (2007) Simulating SOC changes in 11 land use change chronosequences from the Brazilian Amazon with RothC and Century models. Agric Ecosyst Environ 122:46–57. CrossRefGoogle Scholar
  11. Coleman K, Jenkinson DS (2014) RothC—a model for the turnover of carbon in soil: model description and users guide (Updated June 2014). Lawes Agricultural Trust, Harpenden, UK. Accessed 19 December 2017
  12. Dewan ML, Famouri J (1964) The soils of Iran. Food and Agriculture Organization of the United Nations, Rome, p 320Google Scholar
  13. Di Matteo G, Tunno I, Nardi P, De Angelis P, Bertini G, Fabbio G (2014) C and N concentrations in different compartments of outgrown oak coppice forests under different site conditions in Central Italy. Ann For Sci 71:885–895. CrossRefGoogle Scholar
  14. Dube F, Zagal E, Stolpe N, Espinosa M (2009) The influence of land-use change on the organic carbon distribution and microbial respiration in a volcanic soil of the Chilean Patagonia. For Ecol Manage 257:1695–1704. CrossRefGoogle Scholar
  15. Falloon P, Smith P, Coleman K, Marshall S (1998) Estimating the size of the inert organic matter pool from total soil organic carbon content for use in the Rothamsted carbon model. Soil Biol Biochem 30:1207–1211. CrossRefGoogle Scholar
  16. Farina R, Seddaiu G, Orsini R, Steglich E, Roggero PP, Francaviglia R (2011) Soil carbon dynamics and crop productivity as influenced by climate change in a rainfed cereal system under contrasting tillage using EPIC. Soil Tillage Res 112:36–46. CrossRefGoogle Scholar
  17. Farina R, Di Bene C, Piccini C, Marchetti A, Troccoli A, Francaviglia R (2018) Do crop rotations improve the adaptation of agricultural systems to climate change? A modeling approach to predict the effect of durum wheat-based rotations on soil organic carbon and nitrogen. In: Muñoz MA, Zornoza R (eds) Soil management and climate change. Effects on organic carbon, nitrogen dynamics, and greenhouse gas emissions. Academic Press, pp 221–236.
  18. Farzanmanesh R, Abdullah AM, Latif MT (2016) Modeling of soil organic carbon in the north and north-east of Iran under climate change scenarios. Sci Iran 23:2023–2032Google Scholar
  19. Fenech A, Comer N, Gough B (2007) Selecting a global climate model for understanding future projections of climate change. In: Fenech A, MacLellan J (eds) Linking climate models to policy and decision-making. Environment Canada, Toronto, pp 133–145Google Scholar
  20. Francaviglia R, Coleman K, Whitmore AP, Doro L, Urracci G, Rubino M, Ledda L (2012) Changes in soil organic carbon and climate change—application of the RothC model in agro-silvo-pastoral Mediterranean systems. Agric Syst 112:48–54. CrossRefGoogle Scholar
  21. Francaviglia R, Ledda L, Farina R (2018) Organic carbon and ecosystem services in agricultural soils of the Mediterranean basin. In: Gaba S, Smith B, Lichtfouse E (eds) Sustainable agriculture reviews, vol 28. Springer, Cham.
  22. Füssel HM, van Minnen JG (2001) Climate impact response functions for terrestrial ecosystems. Integrat Ass 2(4):183–197. CrossRefGoogle Scholar
  23. Gabrielle B, Menasseri S, Houot S (1995) Analysis and field evaluation of the CERES models water balance component. Soil Sci Soc Am J 59(5):1403–1412. CrossRefGoogle Scholar
  24. Giorgi F, Mearns LO (1991) Approaches to the simulation of regional climate change: a review. Rev Geophys 29:191–216. CrossRefGoogle Scholar
  25. Giorgi F, Mearns LO (2002) Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the “reliability ensemble averaging” (REA) method. J Clim 15:1141–1158.;2 CrossRefGoogle Scholar
  26. Gottschalk P, Smith JU, Wattenbach M, Bellarby J, Stehfest E, Arnell N, Osborn T, Jones C, Smith P (2012) How will organic carbon stocks in mineral soils evolve under future climate? Global projections using RothC for a range of climate change scenarios. Biogeosciences 9:3151–3171. CrossRefGoogle Scholar
  27. Gray JM, Bishop TF (2016) Change in soil organic carbon stocks under 12 climate change projections over New South Wales, Australia. Soil Sci Soc Am J 80(5):1296–1307. CrossRefGoogle Scholar
  28. Guo L, Falloon P, Coleman K, Zhou B, Li Y, Lin E, Zhang F (2007) Application of the RothC model to the results of long-term experiments on typical upland soils in northern China. Soil Use Manag 23(1):63–70. CrossRefGoogle Scholar
  29. Haghdoost N, Akbarinia M, Hosseini SM, Kooch Y (2011) Conversion of Hyrcanian degraded forests to plantations: effects on soil C and N stocks. Ann Biol Res 50(2):385–399Google Scholar
  30. Heshmati GA (2012) Vegetation characteristics of four ecological zones of Iran. Int J Plant Prod 1(2):215–224Google Scholar
  31. Hosseini SA, Jalilvand H (2007) Marginal effect of forest road on Alder trees. Pak J Biol Sci 10:10–1766. CrossRefGoogle Scholar
  32. Huang Y (2014) Comparison of general circulation model outputs and ensemble assessment of climate change using a Bayesian approach. Global Planet Change 122:362–370. CrossRefGoogle Scholar
  33. IPCC (2007) Climate Change 2007: the physical science basis. Contribution of working group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate ChangeGoogle Scholar
  34. IPCC (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 [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, p 151Google Scholar
  35. Jebari A, del Prado A, Pardo G, Rodríguez Martín JA, Álvaro-Fuentes J (2018) Modeling regional effects of climate change on soil organic carbon in Spain. J Environ Qual 47:644–653. CrossRefPubMedGoogle Scholar
  36. Jenkinson DS, Harkness DD, Vance ED, Adams DE, Harrison AF (1992) Calculating net primary production and annual input of organic matter to soil from the amount and radiocarbon content of soil organic matter. Soil Biol Biochem 24:295–308. CrossRefGoogle Scholar
  37. Jenkinson DS, Meredith J, Kinyamario JI, Warren GP, Wong MTF, Harkness DD, Bol R, Coleman K (1999) Estimating net primary production from measurements made on soil organic matter. Ecology 80:2762–2773.;2 CrossRefGoogle Scholar
  38. Jones JW, Tsuji GY, Hoogenboom G, Hunt LA, Thornton PK, Wilkens PW, Imamura DT, Bowen WT, Singh U (1998) Decision support system for agrotechnology transfer: DSSAT v3. In: Tsuji GY, Hoogenboom G, Thornton PK (eds) Understanding options for agricultural production. Kluwer Academic Publishers, Dordrecht, the Netherlands, pp 157–177Google Scholar
  39. Kaonga ML, Coleman K (2008) Modelling soil organic carbon turnover in improved fallows in eastern Zambia using the RothC-26.3 model. For Ecol Manage 256:1160–1166. CrossRefGoogle Scholar
  40. Keating BA, Carberry PS, Hammer GL, Probert ME, Robertson MJ, Holzworth D, Huth NI, Hargreaves JNG, Meinke H, Hochman Z, McLean G, Verburg K, Snow V, Dimes JP, Silburn M, Wang E, Brown S, Bristow KL, Asseng S, Chapman S, McCown RL, Freebairn DM, Smith CJ (2003) An overview of APSIM, a model designed for farming systems simulation. Eur J Agro 18:267–288. CrossRefGoogle Scholar
  41. Kooch Y, Hosseini SM, Zaccone C, Jalilvand H, Hojjati SM (2012) Soil organic carbon sequestration as affected by afforestation: the Darab Kola forest (north of Iran) case study. J Environ Monit 14:2438–2446. CrossRefPubMedGoogle Scholar
  42. Lal R, Kimble J, Levine E, Whitman C (1995) World soils and greenhouse effect: an overview. Soils and global change. Lewis Publ, Boca Raton, pp 1–7Google Scholar
  43. Li C, Frolking S, Harriss R (1994) Modeling carbon biogeochemistry in agricultural soils. Glob Biogeochem Cycles 8:237–254. CrossRefGoogle Scholar
  44. Li H, Jiang Z, Chen Z, Ren J, Liu B (2017) Assimilation of temporal-spatial leaf area index into the CERES-Wheat model with ensemble Kalman filter and uncertainty assessment for improving winter wheat yield estimation. J Integr Agric 16(10):2283–2299. CrossRefGoogle Scholar
  45. Liu DL, O’Leary GJ, Christy B, Macadam I, Wang B, Anwar MR, Weeks A (2017) Effects of different climate downscaling methods on the assessment of climate change impacts on wheat cropping systems. Clim Change 144(4):687–701. CrossRefGoogle Scholar
  46. Lozano-García B, Muñoz-Rojas M, Parras-Alcántara L (2017) Climate and land use changes effects on soil organic carbon stocks in a Mediterranean semi-natural area. Sci Total Environ 579:1249–1259. CrossRefPubMedGoogle Scholar
  47. Mao R, Zeng DH, Ai GY, Yang D, Li LJ, Liu YX (2010) Soil microbiological and chemical effects of a nitrogen-fixing shrub in poplar plantations in semi-arid region of Northeast China. Eur J Soil Biol 46:325–329. CrossRefGoogle Scholar
  48. MEA (2005) Ecosystems and human well-being: synthesis. Island Press, Washington DC, Millennium Ecosystem Assessment, p 137Google Scholar
  49. Meersmans J, Arrouays D, Van Rompaey AJ, Pagé C, De Baets S, Quine TA (2016) Future C loss in mid-latitude mineral soils: climate change exceeds land use mitigation potential in France. Sci Rep 6:35798. CrossRefPubMedPubMedCentralGoogle Scholar
  50. Mishra G, Jangir A, Francaviglia R (2019) Modeling soil organic carbon dynamics under shifting cultivation and forests using RothC model. Ecol Model 396:33–41. CrossRefGoogle Scholar
  51. Mohammadnezhad Kiasari S, Sagheb-Talebi Kh, Rahmani R, Ghasemi Chapi O (2009) Seasonal variation of earthworm abundances and biomass in natural forests and plantations (North of Iran). Caspian J Env Sci 7:87–98Google Scholar
  52. Muñoz-Rojas M, Jordán A, Zavala LM, González-Peñaloza FA, De la Rosa D, Pino-Mejias R, Anaya-Romero M (2013) Modelling soil organic carbon stocks in global change scenarios: a CarboSOIL application. Biogeosciences 10:8253–8268. CrossRefGoogle Scholar
  53. Muñoz-Rojas M, Doro L, Ledda L, Francaviglia R (2015) Application of CarboSOIL model to predict the effects of climate change on soil organic carbon stocks in agro-silvo-pastoral Mediterranean management systems. Agr Ecosyst Environ 202:8–16. CrossRefGoogle Scholar
  54. Murphy JM, Sexton DMH, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth DA (2004) Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature 430:768–772. CrossRefPubMedGoogle Scholar
  55. Palosuo T, Foereid B, Svensson M, Shurpali N, Lehtonen A, Herbst M, Linkosalo T, Ortiz C, Todorovic GR, Marcinkonis S (2012) A multi-model comparison of soil carbon assessment of a coniferous forest stand. Environ Model Softw 35:38–49. CrossRefGoogle Scholar
  56. Pan Z, Andrade D, Segal M, Wimberley J, McKinney N, Takle E (2010) Uncertainty in future soil carbon trends at a central US site under an ensemble of GCM scenario climates. Ecol Modell 221(5):876–881. CrossRefGoogle Scholar
  57. Parsapour MK, Kooch Y, Hosseini SM, Alavi SJ (2018) C and N cycle monitoring under Quercus castaneifolia plantation. Forest Ecol Manag 427:26–36. CrossRefGoogle Scholar
  58. Parton WJ, Schimel DS, Cole C, Ojima D (1987) Analysis of factors controlling soil organic matter levels in Great Plains grasslands. Soil Sci Soc Am J 51(5):1173–1179. CrossRefGoogle Scholar
  59. Parton WJ, Ojima D, Schimel DS, Cole C (1994) A general model for soil organic matter dynamics: sensitivity to litter chemistry, texture and management. Quantitative modeling of soil forming processes, SSSA Spec. Public. No. 39. Madison, WI, USA, pp 147–167Google Scholar
  60. Paul KI, Polglase PJ, Richards GP (2003) Predicted change in soil carbon following afforestation or reforestation, and analysis of controlling factors by linking a C accounting model (CAMFor) to models of forest growth (3PG), litter decomposition (GENDEC) and soil C turnover (RothC). For Ecol Manage 177:485–501. CrossRefGoogle Scholar
  61. Peltoniemi M, Heikkinen J, Mäkipää R (2007) Stratification of regional sampling by model-predicted changes of carbon stocks in forested mineral soils. Silva Fennica 41(3):527–539. Accessed 19 Dec 2017
  62. Racsko P, Szeidl L, Semenov M (1991) A serial approach to local stochastic weather models. Ecol Modell 57:27–41. CrossRefGoogle Scholar
  63. Räisänen J (2007) How reliable are climate models? Tellus A 59:2–29. CrossRefGoogle Scholar
  64. Rampazzo Todorovic G, Lair GJ, Blum WEH (2014) Modeling and prediction of C dynamics in soil chronosequences of the critical zone observatory (CZO) Marchfeld/Austria. CATENA 121:53–67. CrossRefGoogle Scholar
  65. Resh SC, Binkley D, Parrotta JA (2002) Greater soil carbon sequestration under nitrogen-fixing trees compared with Eucalyptus species. Ecosystems 5:217–231. CrossRefGoogle Scholar
  66. Riahi K, Grübler A, Nakicenovic N (2007) Scenarios of long-term socio-economic and environmental development under climate stabilization. Technol Forecast Soc Change 74:887–935. CrossRefGoogle Scholar
  67. Riedo M, Grub A, Rosset M, Fuhrer J (1998) A pasture simulation model for dry matter production, and fluxes of carbon, nitrogen, water and energy. Ecol Model 105:141–183. CrossRefGoogle Scholar
  68. Romanya J, Cortina J, Falloon P, Coleman K, Smith P (2000) Modelling changes in soil organic matter after planting fast-growing Pinus radiata on Mediterranean agricultural soils. Eur J Soil Sci 51:627–641. CrossRefGoogle Scholar
  69. Rothe A, Cromack JK, Resh SC, Makineci E, Son Y (2002) Soil carbon and nitrogen changes under Douglas-fir with and without red alder. Soil Sci Soc Am J 66:1988–1995. CrossRefGoogle Scholar
  70. Rumpel C, Balesdent J, Grootes P, Weber E, Kögel-Knabner I (2003) Quantification of lignite- and vegetation-derived soil carbon using 14C activity measurements in a forested chronosequence. Geoderma 112:155–166. CrossRefGoogle Scholar
  71. Sándor R, Barcza Z, Acutis M, Doro L, Hidy D, Köchy M, Minet J, Lellei-Kovács E, Ma S, Perego A, Rolinski S, Ruget F, Sanna M, Seddaiu G, Wu L, Bellocchi G (2017) Multi-model simulation of soil temperature, soil water content and biomass in Euro-Mediterranean grasslands: uncertainties and ensemble performance. Eur J Agron 88:22–40. CrossRefGoogle Scholar
  72. Semenov MA, Brooks RJ, Barrow EM, Richardson CW (1998) Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates. Clim Res 10:95–107. CrossRefGoogle Scholar
  73. Shirato Y, Hakamata T, Taniyama I (2004) Modified Rothamsted carbon model for andosols and its validation: changing humus decomposition rate constant with pyrophosphate-extractable Al. Soil Sci Plant Nutr 50(1):149–158CrossRefGoogle Scholar
  74. Six J, Paustian K (2014) Aggregate-associated soil organic matter as an ecosystem property and a measurement tool. Soil Biol Biochem 68:A4–A9. CrossRefGoogle Scholar
  75. Skjemstad JO, Spouncer LR, Cowie B, Swift RS (2004) Calibration of the Rothamsted organic carbon turnover model (RothC ver. 26.3), using measurable soil organic carbon pools. Aust J Soil Res 42:79–88. CrossRefGoogle Scholar
  76. Soleimani A, Hosseini SM, Massah Bavani AR, Jafari M, Francaviglia R (2017) Simulating soil organic carbon stock as affected by land cover change and climate change, Hyrcanian forests (northern Iran). Sci Total Environ 599–600:1646–1657. CrossRefPubMedGoogle Scholar
  77. Sperna Weiland FC, van Beek LPH, Kwadijk JCJ, Bierkens MFP (2010) The ability of a GCM-forced hydrological model to reproduce global discharge variability. Hydrol Earth Syst Sci 14:1595–1621. CrossRefGoogle Scholar
  78. Sperna Weiland FC, van Beek LPH, Weerts AH, Bierkens MFP (2012) Extracting information from an ensemble of GCMs to reliably assess future global runoff change. J Hydrol 412:66–75. CrossRefGoogle Scholar
  79. Tebaldi D, Knutti R (2007) The use of the multi-model ensemble in probabilistic climate projections. Philos Trans R Soc A 365:2053–2075. CrossRefGoogle Scholar
  80. Thornthwaite CW, Mather JR (1955) The water balance. Publ Climatol 8:1–104Google Scholar
  81. Turner J, Lambert MJ, Johnson DW (2005) Experience with patterns of change in soil carbon resulting from forest plantation establishment in eastern Australia. For Ecol Manage 220:259–269. CrossRefGoogle Scholar
  82. van Huijgevoort MHJ, Van Lanen HAJ, Teuling AJ, Uijlenhoet R (2014) Identification of changes in hydrological drought characteristics from a multi-GCM driven ensemble constrained by observed discharge. J Hydrol 512:421–434. CrossRefGoogle Scholar
  83. van Vuuren DP, Den Elzen MGJ, Lucas PL, Eickhout B, Strengers BJ, Van Ruijven B, Wonink S, Van Houdt R (2007) Stabilizing greenhouse gas concentrations at low levels: an assessment of reduction strategies and costs. Clim Change 81:119–159. CrossRefGoogle Scholar
  84. Viner D, Hulme M (1994) The climate impacts LINK project: providing climate change scenarios for impacts assessment in the UK. DoE/CRU Report, NorwichGoogle Scholar
  85. Wiesmeier M, Poeplau C, Sierra CA, Maier H, Frühauf C, Hübner R, Kühnel A, Spörlein P, Geuß U, Hangen E, Schilling B, von Lützow M, Kögel-Knabner I (2016) Projected loss of soil organic carbon in temperate agricultural soils in the 21st century: effects of climate change and carbon input trends. Sci Rep 6:32525. CrossRefPubMedPubMedCentralGoogle Scholar
  86. Williams JR, Jones CA, Kiniry JR, Spanel DA (1989) The EPIC crop growth model. Trans ASAE 32(2):497–511CrossRefGoogle Scholar
  87. Yigini Y, Panagos P (2016) Assessment of soil organic carbon stocks under future climate and land cover changes in Europe. Sci Total Environ 557:838–850. CrossRefPubMedGoogle Scholar
  88. Zhang C, Liu G, Xue S, Sun C (2013) Soil organic carbon and total nitrogen storage as affected by land use in a small watershed of the Loess Plateau, China. Eur J Soil Biol 54:16–24. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Research Centre for Agriculture and EnvironmentCREA, Council for Agricultural Research and EconomicsRomeItaly
  2. 2.Faculty of Natural Resources and Marine SciencesTarbiat Modares UniversityNoorIran
  3. 3.Department of Irrigation and Drainage Engineering, College of AbouraihanUniversity of TehranTehranIran
  4. 4.Research Institute of Forests and RangelandsAgricultural Research Education and Extension Organization (AREEO)TehranIran

Personalised recommendations