Document Type : Original Article
Authors
1 Ph.D. in Desertification, Department of Natural Resources Engineering, Faculty of Agriculture & Natural Resources, University of Hormozgan, BandarAbbas, Iran.
2 PhD student of Rangeland Science, Department of Rehabilitation of Arid and Mountainous Regions, Faculty of Natural Resources, University of Tehran, Karaj, Iran.
3 Ph.D. Student in Ecosystem Restoration, Department of Range and Watershed Management Ferdowsi University of Mashhad, Iran
Abstract
Saffron (Crocus sativus L) holds a special place in the culture and economy of various countries as one of the valuable and expensive spices. This plant, resistant to drought and capable of growing in specific climatic conditions, carries significant economic importance. Its cultivation in regions with limited conditions and low water requirements is considered an excellent opportunity for sustainable agriculture in upland and water-scarce areas. In Iran, saffron is cultivated as a strategic and exportable product, especially in regions like Khorasan, Kerman, Golestan, and Markazi. The cultivation of saffron comes with challenges such as water scarcity, soil pollution, decreased genetic diversity, and climate change, especially in arid and water-scarce regions, which is a cause for concern. This article, focusing on the habitat suitability for saffron cultivation, investigates the environmental factors and their impact on the growth, yield, and quality of this product, using species distribution models. Additionally, the role of human interventions and climate changes in saffron habitat suitability and methods for increasing productivity and sustainability of saffron cultivation are discussed and examined.
Keywords
Bathaie, S. Z., & Mousavi, S. Z. (2010). New applications and mechanisms of action of saffron and its important ingredients. Critical reviews in food science and nutrition, 50(8), 761.786.
Bayat, M., Amir Niya, R., Taj Bakhsh, M., & Tanyvlach, B. (2016). Genetic Diversity of Saffron (Crocus sativus L.) using iPBS and SSR Molecular Markers. Journal of Saffron Research, 4(1), 103-119. [In Persian].
Breiner, F. T., Guisan, A., Bergamini, A., & Nobis, M. P. (2015). Overcoming limitations of modelling rare species by using ensembles of small models. Methods in Ecology and Evolution, 6(10), 1210-1218.
Chase, J. M., & Leibold, M. A. (2009). Ecological niches: linking classical and contemporary approaches. University of Chicago Press.
Chaves, P. P., Ruokolainen, K., & Tuomisto, H. (2022). Impact of spatial configuration of training data on the performance of Amazonian tree species distribution models. Forest Ecology and Management, 504.
Crimmins, S.M., Dobrowski, S.Z., Mynsberge, A.R. (2013). Evaluating ensemble forecasts of plant species distributions under climate change. Ecol. Model. 266, 126–130.
Damaneh, J. M., Ahmadi, J., Rahmanian, S., Sadeghi, S. M. M., Nasiri, V., & Borz, S. A. (2022). Prediction of wild pistachio ecological niche using machine learning models. Ecological Informatics, 72, 101907.
Damschen, E. I., Haddad, N. M., Orrock, J. L., Tewksbury, J. J., & Levey, D. J. (2006). Corridors increase plant species richness at large scales. Science, 313(5791), 1284-1286.
Dehbashi, M., Rajaei, A., & KardanMoghadam, H. (2022). Locating and recognizing of Saffron Flowers using Image Processing. Saffron Agronomy and Technology, 10(3), 227-260. [In Persian].
Elith, J., & Leathwick, J. R. (2009). Species distribution models: ecological explanation and prediction across space and time. Annual review of ecology, evolution, and systematics, 40,677-697.
Eskandari, M., Zeinadini, a., Navidi, M.N., & Salmanpour, A. (2022). Evaluating topsis method in prioritizing lands for saffron cultivation. Journal of water and soil (agricultural sciences and technology), 36(2), 237-249. [In Persian].
Fielding, A. H., & Bell, J. F. (1997). A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental conservation, 24(1), 38-49.
Galton, F. (1892). Finger prints (No. 57490-57492). Macmillan and Company.
Ghanji, M., & Khoshnoudi Far, Z. (2022). Analysis of factors affecting the willingness to accept saffron cultivation (Case study: Farmers of Farahan, Markazi Province). Saffron promotion magazine, 3(1), 1-7. [In Persian].
Ghareghan, F., Ghanbarian, G., Pourghasemi, H. R., & Safaeian, R. (2020). Prediction of habitat suitability of Morina persica L. species using artificial intelligence techniques. Ecological Indicators,112,106096.
Ghoddusi, H. B., Koocheki, A., Varidi, M., & Bolandi, M. (2003). Seventy years of research on saferon (Crocus sativus L.) in Iran: a review. Iranian journal of field crops research, 1(2), 217-247. [In Persian].
Golestaneh, S.R., Karampour, F, & Farrar, N. (2012). Introduction of the destructive agents affecting wild almond (Amygdalus scoparia) forests in koh-siah dashti area in bushehr province. Forest and range protection research, 10(2), 153-164. [In Persian].
Guisan, A., & Thuiller, W. (2005). Predicting species distribution: offering more than simple habitat models. Ecology letters, 8(9), 993-1009.
Guo, Y., Li, X., Zhao, Z., Wei, H., Gao, B., & Gu, W. (2017). Prediction of the potential geographic distribution of the ectomycorrhizal mushroom Tricholoma matsutake under multiple climate change scenarios. Scientific reports,7(1),46221.
Halabian, A., Torkashvand, G., & Salehi, Z. (2021). Revelation of Climatically Capable Areas for Saffron Cultivation in Hamedan Province. Journal of Saffron Research, 9(1), 79-94. doi: 10.22077/jsr.2021.3487.1134. [In Persian].
Hao, T., Elith, J., Lahoz‐Monfort, J. J., & Guillera‐Arroita, G. (2020). Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models. Ecography, 43(4), 549-558.
Hijmans, R. J., Phillips, S., Leathwick, J., & Elith, J. (2017). dismo: Species distribution modeling. R package version, 1(4), 1-1.
Kafi, M. (Ed.). (2006). Saffron (Crocus sativus): production and processing. Science Publishers.
Kalantar, B., Ueda, N., Saeidi, V., Ahmadi, K., Halin, A. A., & Shabani, F. (2020). Landslide susceptibility mapping: Machine and ensemble learning based on remote sensing big data. Remote Sensing,12(11),1737.
Kamyabi, S., Habibi nokhandan, M, & Rouhi, A. (2014). Effect of climatic factors affecting saffron using analytic hierarchy process (AHP), (case study roshtkhar region, Iran). Saffron agronomy and technology, 2(1), 75-90. [In Persian].
Kargar, M., Jafarian, Z., Tamartash, R., & Alavi, S. J. (2018). Comparison of non-parametric and parametric species distribution models (SDM) in determining the habitat of dominant rangeland species (case study: Khetteh Riz Rangelands). Iranian Journal of Range and Desert Research, 25(3). [In Persian].
Koch, O., de Avila, A. L., Heinen, H., & Albrecht, A. T. (2022). Retreat of Major European Tree Species Distribution under Climate Change—Minor Natives to the Rescue?, Sustainability, 14(9),5213.
Kouzegaran, S., Mousavi Baygi, M., Sanaeinejad, H., & Behdani, M. A. (2013). Identification relevant areas for saffron cultivation according to precipitation and relative humidity in South Khorasan using GIS. Journal of Saffron Research, 1(2), 85-96. doi: 10.22077/jsr.2013.436. [In Persian].
Leibold, M. A., Holyoak, M., Mouquet, N., Amarasekare, P., Chase, J. M., Hoopes, M. F., ... & Gonzalez, A. (2004). The metacommunity concept: a framework for multi‐scale community ecology. Ecology letters,7(7),601-613.
Lembrechts, J. J., Lenoir, J., Roth, N., Hattab, T., Milbau, A., Haider, S., ... & Nijs, I. (2019). Comparing temperature data sources for use in species distribution models: From in‐situ logging to remote sensing. Global Ecology and Biogeography,28(11),1578-1596.
Liang, Y., Duveneck, M. J., Gustafson, E. J., Serra‐Diaz, J. M., & Thompson, J. R. (2018). How disturbance, competition, and dispersal interact to prevent tree range boundaries from keeping pace with climate change. Global Change Biology,24(1).
Momeni Damaneh, J., Esmaeilpour, Y., Gholami, H,. & Farashi, A. (2022). Prediction of potential habitats of Astracantha gossypina (Fisch.) Using the maximum entropy model in regional scale. PEC 2022; 9 (19) :217-236. [In Persian].
Momeni Damaneh, J., Esmaeilpour, Y., Gholami, H., & Farashi, A. (2021). Properly predict the growth of (Ferula assa-foetida L.) in northeastern Iran using the maximum entropy model. Iranian Journal of Range and Desert Research, 28(3), 578-592. [In Persian].
Momeni Damaneh, J., Tajbakhsh, S. M., Ahmadi, J., & Safdari, A. A. (2022). Comparison of species distribution models in determining the habitat landscape of Pistacia vera L. specie in Razavi Khorasan province. Water and Soil Management and Modelling, 3(4), 77-92. [In Persian].
Momeni Damaneh, J., Tajbakhsh, S. M., Ahmadi, J., & safdari, A. A. (2023). Determining The Areas Prone to The Growth of Rhume ribes L. Specie in Razavi Khorasan Province Using Vector Machine Models. Water and Soil Management and Modelling, doi: 10.22098/mmws.2023.12726.1276. [In Persian].
Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological modelling, 190(3-4),231-259.
Rahmanian, S., Pourghasemi, H. R., Pouyan, S., & Karami, S. (2021). Habitat potential modelling and mapping of Teucrium polium using machine learning techniques. Environmental Monitoring and Assessment, 193, 1-21.
Rahmanian, S., Pouyan, S., Karami, S., & Pourghasemi, H. R. (2022). Predictive habitat suitability models for Teucrium polium L. using boosted regression trees. In Computers in Earth and Environmental Sciences (pp. 245-254). Elsevier.
Seni, G., & Elder, J. (2010). Ensemble methods in data mining: improving accuracy through combining predictions. Morgan & Claypool Publishers.
Shahdost, Z. (2021). Feasibility study of saffron cultivation from farmers’ viewpoint in villages of Arsanjan County. Journal of Saffron Research, 9(1), 61-78. doi: 10.22077/jsr.2020.3270.1128. [In Persian].
Shahidi, A., & Khashei Siuki, A. (2019). Climatic Zoning Saffron(.Crocus sativus L) Cultivation using Analytical Hierarchy Process and Analytic Network Process (A Case Study: Semnan City). Journal of Saffron Research, 6(2), 283-298. doi: 10.22077/jsr.2017.626.1024. [In Persian].
Smeeton, N. C. (1985). Early history of the kappa statistic. Biometrics, 41, 795.
Swets, J. A. (1988). Measuring the accuracy of diagnostic systems. Science, 240(4857), 1285-1293.
Thuiller, W., Lafourcade, B., Engler, R., & Araújo, M. B. (2009). BIOMOD–a platform for ensemble forecasting of species distributions. Ecography,32(3),369-373.
Townsend Peterson, A., Papeş, M., & Eaton, M. (2007). Transferability and model evaluation in ecological niche modeling: a comparison of GARP and Maxent. Ecography, 30(4), 550-560.
Vandermeer, J. H. (1972). Niche theory. Annual review of Ecology and Systematics, 3(1), 107-132.
Walther, G. R., Post, E., Convey, P., Menzel, A., Parmesan, C., Beebee, T. J., ... & Bairlein, F. (2002). Ecological responses to recent climate change. Nature, 416(6879), 389-395.
Wang, D. J., Wei, H. Y., Zhang, X. H., Fang, Y. Q., & Gu, W. (2021). Habitat suitability modeling based on remote sensing to realize time synchronization of species and environmental variables. Journal of Plant Ecology, 14(2), 241-256.
Wani, I. A., Khan, S., Verma, S., Al-Misned, F. A., Shafik, H. M., & El-Serehy, H. A. (2022). Predicting habitat suitability and niche dynamics of Dactylorhiza hatagirea and Rheum webbianum in the Himalaya under projected climate change. Scientific Reports, 12(1), 13205.
Ye, X., Zhang, M., Yang, Q., Ye, L., Liu, Y., Zhang, G., ... & Liu, B. (2022). Prediction of suitable distribution of a critically endangered plant Glyptostrobus pensilis. Forests, 13(2), 257.
Zare chahouki, M. A., & Abbasi, M. (2018). Habitat prediction model medicinal species of Rheum ribes L. with maximum entropy model in chahtorsh rangeland of the Yazd province. Journal of range and watershed management (Iranian journal of natural resources), 71(2), 379-391. [In Persian].
Zare Chahouki, M.A., & Naseri Hesar, N. (2018). Habitat distribution modeling of some plant species using logistic regression in the semi-arid rangelands (Case study: Eshtehard rangelands). Journal of plant research (Iranian journal of biology), 31(1), 93-100. [In Persian].
Zarkami, R., Ahmadi, M., & Abedini, A. (2021). Modelling habitat preferences of water hyacinth (Eichhornia crassipes) in some wetlands of Guilan province. Journal of Plant Research (Iranian Journal of Biology), 34(2), 449-466. [In Persian].