Studying Spatiotemporal Changeability of Oak Forests in Zagros in Response to Rainfall Variation

Document Type : Research Paper

Authors

1 Department of Geography, Najafabad Branceh, Islamic Azad Uiversity, Najafabad, Iran

2 Research Institute of Forests and Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran

Abstract

The forests of the Zagros are one of the most important and fundamental treasures of the country, which plays a key role in providing water and soil resources in this region.The geographical distribution of different plant communities is dramatically dependent on climatic conditions. Changes in climatic elements, such as precipitation, can cause long-term and short-term reactions of various plant colonie. The main purpose of this study is to reveal the spatial changeability of Lorestan forest NDVI index in response to rainfall changes. The vegetation index of Lorestan was detected using Landsat 8 and 5 imageries during 2000-2017. The monthly and annual rainfall also has been obtained using accumulated monthly rainfall of 9 synoptic stations of Lorestan province. The Pearson correlation matrix has been used to analyze the relationship between annual variation of forest cover area and qnnual rainfall index. The results showed that the EVI> 0.4 threshold can be considered as the threshold of the province's forest cover. The correlation analysis showed that the 18-year time series of forest cover, was correlated with the spatial distribution of annual rainfall in Lorestan Province by 0.72 that is significant in 0.95 confidence level (P_value=0.05). Spatial analysis of the implementation of the greenness estimator model showed that the rainfall threshold of oak greenery (EVI> 0.4) was equal to 320 mm, above which the EVI index increased by 0.88 for each millimeter of rainfall growth of the studied oaks.
Extended Abstract
1-Introduction
The geographical distribution of different plant communities is dramatically dependent on climatic conditions. Changes in climatic elements, such as precipitation, can cause long-term and short-term reactions of various plant colonies (Wang et al., 2017). The relationship between vegetation and climatic factors is so close that many researchers, including Coupon, have classified their climate systems based on the overall structure of plant communities (Guard and Prince, 1995). Climatic conditions and vegetation in each region have a two-way, intertwined relationship. In fact, climatic conditions determine the spatial distribution of species, growth period, phenological needs and even natural selection. On the other hand, they create a vegetative cover of a balanced microclimate in the heart of the region general climate, which sometimes differs significantly from the original climate. Borhan et al., 2015).
2-Materials and Methods
In this study, two categories of data were used. The first category of data, including the monthly rainfall data of the province during the oak tree growth period (i.e. periods when the average minimum temperature did not fall below 10C is presented. The source of this data was the monthly record of stationary precipitation during the statistical period of 2000-2017 by 9 synoptic stations of the province and the networked precipitation of GPCC climate base. The second group of data used in this study is related to the vegetation index, which was obtained from three red, infrared and blue bands of LANDSAT satellite on a monthly basis for the statistical period of 2000-2018. The Pearson spatial correlation model was used at the confidence level of 0.95 (P-value = 0.05) to analyze the relationship between spatial changes in the forest cover areas of Lorestan province and spatial distribution of precipitation based on annual and monthly scales.
3-Results and Discussion
In this study, forest areas, which were obtained by using threshold (EVI> 0.4), showed that the greenery of oaks in Lorestan province was the highest in peak mode (September) on an intra-year scale with rains 3 to 5 months ago. Such a delay has been observed in many other researches, including the work of Sedighifar et al. (2019), which examined the temporal and spatial response of the Hyrcanian forests of Mazandaran province to the climatic characteristics of the region, including precipitation. Secondly, the threshold of oak greenery in Lorestan province, which has been calculated using experimental sampling, has been 320 mm of rainfall, which indicates that the experimental greenery obtained is generally observed in areas where annual rainfall is more than 320 mm per year. The fitted model indicated that on an annual precipitation scale, an increase in each millimeter of precipitation (above 320 mm at the precipitation limit) would increase the EVI index by 0.88, a ratio of 0.46 to the confidence level. 0.95 has been significant. In terms of spatial changes in precipitation, the results showed that precipitation changes in oak habitats could significantly change the area of ​​oak green thresholds, so that according to the fitted linear model, each millimeter of precipitation changes in oak habitats (320 precipitation threshold). Millimeters will lead to a change of 1724 km in the area of ​​these areas with greenery above 0.4.
4-Conclusion
In this study, it was observed that precipitation of 5 months before the September of each year, ie precipitation from April to June, is the main controller of the greenness of healthy trees in the oak forests of the province. On the other hand, it was determined that the greenery threshold of these forests is 320 mm of annual rainfall. However, in some habitats, forest ash is also seen below this precipitation level. Due to this dependence of the province oak forests on precipitation, the increasing trend of anomalies and irregularities of precipitation is increasing in the future and the temporal and spatial changes of precipitation in the province will have an increasing trend provided that the continuation of the current management process and failure to take protective measures against the oak forests of the province, the process of destruction of these forests has intensified and in the near future the level of these forests in Lorestan province will greatly reduce.         

 
 
 

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Main Subjects


احسانی، علی؛ ارزانی، حسین؛ فرحپور، مهدی؛ احمدی، حسن؛ جعفری، محمد؛ جلیلی، عادل؛ میرداودی، حمیدرضا؛ عباسی، حمیدرضا؛ عظیمی، مژگان السادات (1386). تأثیر شرایط اقلیمی بر تولید علوفه مراتع در منطقة استپی اخترآباد ساوه. تحقیقات مرتع و بیابان ایران، 14(2)، 249-260.
علیرضایی، زهرا؛ گندمکار، امیر؛ خداقلی، مرتضی؛ عباسی، علیرضا (1398). آشکارسازی تأثیر خشکسالی بر پویایی زمانی - مکانی جنگل‌های بلوط زاگرس (نمونة موردی: جنگل‌های بلوط لرستان). تحقیقات حمایت و حفاظت جنگل‌ها و مراتع ایران، 17(1)، 107-123.
فرج­زاده، منوچهر؛ فتح­نیا، امان­اله؛ علیجانی، بهلول؛ ضیائیان، پرویز (1390). ارزیابی تأثیر عوامل اقلیمی بر رشد پوشش گیاهی در مراتع متراکم ایران با استفاده از تصاویر AVHRR. پژوهش­های جغرافیای طبیعی، 44(75)، 1-14.
فرخ­زاده، بهنوش؛ منصوری، شهروز؛ سپهری، عادل (1396). تعیین میزان همبستگی بین شاخص‌های پوشش گیاهی NDVI و EVI با شاخص خشکسالی هواشناسی (مطالعة موردی: مراتع دشتی استان گلستان). هواشناسی کشاورزی، 5 (2)، 55-65.
هادیان، فاطمه؛ جعفری، رضا؛ بشری، حسین؛ سلطانی، سعید (1392). پایش تأثیر بارش در تغییرات پوشش گیاهی با استفاده از تکنیک­های سنجش از دور در یک دورة 21 ساله (مطالعة موردی: سمیرم و لردگان). نشریة مرتع و آبخیزداری، 66 (4)، 621-632.
References
Alirezaee, Z., Gandomkar, A., Khodagholi, M. & Abasi, A. R. (2019). Spatiotemporal Dynamics of Oak Forest of Zagros in Responce to Drought Case Study: Oak Forest of Lorestan. Iranian Journal of Foret and Range Protection Research, 17 (1), 107-123. doi 10.22092/IJFRPR. 2019.119997. (In Persian)
Anyamba, A., Eastman, J. R. (1996). Interannual variability of NDVI over Africa and its relation to El Nino/Southern Oscillation. International Journal Remote Sens, 17 (3), 2533-2548. https://doi.org/10.1080/01431169608949091.
Berhan, G., Tadesse, T. & Atnafu, S. (2015). Drought Spatial Object Prediction Approach Using Artificial Neural Network. Geoinfor Geostat: An Overview, 3 (2), 1-7. doi:10.4172/2327-4581.1000132.
Choudhury, B. J., Tucker, C. J., Golus, R. E. & Newcomb, W. W. (1987). Monitoring vegetation using Nimbus-7 scanning multichannel microwave radiometer’s data. International Journal of Remote Sensing, 8 (3), 533-538. https://doi.org/10.1080/01431168708948660.
Denman, S., Barrett, G., Kirk, S. A., McDonald, J. E. & Coetzee, M. P. A. (2017). Identification of Armillaria species on declined oak in Britain: Implications for oak health. Forestry, 90 (2), 148-161. DOI: 10.1093/forestry/cpw054.

Ehsani, A., Hosein Arzani, M., Farahpoor, H., Ahmadi, M., Jafari, A., Jalili, H. R., Mirdavodi, H. & Abbasi, M. (2007). The effect of climatic conditions on range forage production in steppe ranglands, Akhtarabad of Saveh. Iranian journal of Range and Desert Research, 14 (2), 249-260. (In Persian)

Farajzadeh, M., Fathnia, A., Alijani, B. & Zeaiean, P. (2011). Assessment of the Effect of Climatic Factors on the Growth of Dense Pastures of Iran, Using AVHRR Images. Physical Geography Research, 43 (75), 1-14. (In Persian)

Farrokhzadeh, B., Mansouri, S. & Sepehri, A. (2018). Determining the correlation between NDVI and EVI vegetation indices and SPI drought index (Case Study: Golestan rangelands).­ Journal of Agricultural Meteorology, 5 (2), 56-65. (In Persian)

Goward, S. N., Prince, S . D. (1995). Transient Effects of Climate on Vegetation Dynamics Satellite Observations. Journal Biogeogr, 22 (5), 549-563. DOI: 10.2307/2845953 https://www.jstor. org/stable/2845953.
Guli, J., Shunlin, L., Qiuxiang, Yi. & Jinping, L. (2015).Vegetation dynamics and responses to recent climate change in Xinjiang using leaf area index as an indicator. Ecological Indicators, 58 (2), 64-76. DOI10.1016/j.ecolind.2015.05.036.
Hadian, F., Jafari, R., Bashari, H. & Soltani, S. (2014). Monitoring the Effects of Precipitation on Vegetation Cover Changes Using Remote Sensing Techniques in 12 Years Period (Case study: Semirom Isfahan). Journal of Range and Watershed Management, 66 (4), 621-632, doi 10.22059/JRWM.2014.50035. (In Persian)
Potter, C. S., Brooks, V. (1998). Global analysis of empirical relations between annual climate and seasonality of NDVI. International Journal Remote Sens, 15 (1), 2921-2948. https://doi.org/ 10.1080/014311698214352.
Schultz, P. A. & Halpert, M. S. (1995). Global Analysis of the Relationships Among a Vegetation Index, Precipitation, and Land Surface Temperature. International Journal of Remote Sensing, 16 (3), 2755-2777. https://doi.org/10.1080/01431169508954590.
Sedighifar, Z., Motlagh, M. G. & Halimi, M .(2019). Investigating spatiotemporal relationship between EVI of the MODIS and climate variables in northern Iran. International Journal of Environmental Science and Technology, 16 (4), 1-12.
Shifaw, E., Sha, J., Xiaomei, L., Zhongcong, B., Jianwan, J. & Bingchu, C. (2018). Spatiotemporal analysis of vegetation cover (1984-2017) and modelling of its change drivers, the case of Pingtan Island, China. Modeling Earth Systems and Environment, 4 (1), 899-917. DOI: 10.1007/s40808-018-0473-6.
Tong, S., Zhang, J., Bao, Y. (2017). Spatial and temporal variations of vegetation cover and the relationships with climate factors in inner Mongolia based on GIMMS NDVI3g data. Journal of Arid Land, 9 (3), 394-407.
Tucker, C. J., Holben, B. N. & Goff, T. E. (1984). Intensive forest clearing in Rondonia, Brazil, as detected by satellite remote sensing. Remote Sensing of Environment, 15 (3), 255-261.
Wang T., Luo Y., Zhong, M. (2017). Comparison of recent precipitation tendency between Northwest and North China. Journal of China Hydrology, 37 (1), 56-63. https://doi.org/10. 1155/2017/8282353.