پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شماره‌ها | 6,532 |
| تعداد مقالات | 70,502 |
| تعداد مشاهده مقاله | 124,117,119 |
| تعداد دریافت فایل اصل مقاله | 97,222,115 |
اثر تغییرات اقلیمی بر مقادیر ذخایر کربن آلی خاک اقلیم نیمه‌خشک مشهد با استفاده از مدل RothC | ||
| تحقیقات آب و خاک ایران | ||
| دوره 53، شماره 10، دی 1401، صفحه 2349-2363 اصل مقاله (1.36 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2022.346264.669327 | ||
| نویسندگان | ||
| صبا باقریفام1؛ محمد امیر دلاور* 2؛ پیمان کشاورز3؛ پرویز کرمی4 | ||
| 1دانشجوی دوره دکتری، گروه علوم و مهندسی خاک، دنشکده کشاورزی، دانشگاه زنجان، زنجان، ایران. | ||
| 2دانشیار گروه علوم و مهندسی خاک ،دانشکده کشاورزی ،دانشگاه زنجان، زنجان، ایران. | ||
| 3دانشیار بخش تحقیقات خاک و آب خراسان رضوی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی خراسان رضوی(AREEO)، مشهد، ایران | ||
| 4استادیار گروه مهندسی مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران | ||
| چکیده | ||
| کربن آلی خاک یک جز کلیدی در تعیین کیفیت، سلامت و حاصلخیزی خاک است که با توجه به پیچیدگی ساختار و روابط ذخایر کربن آلی، بهره‌گیری از مدل‌ها در شناسایی واکنش این ذخایر نسبت به تغییر شرایط بوم نظام بسیار کارگشا است. از‌این‌رو با استفاده از مدل RothC، اثر گرمایش جهانی و تغییرات اقلیمی، بر مقادیر ذخایر کربن آلی خاک بوم نظام زراعی جنوب شرقی مشهد بررسی شد. برای این منظور ابتدا مدل با استفاده از داده‌های مطالعات پیشین و مقادیر اندازه‌گیری شده در سال 2020، مورد واسنجی و اعتبارسنجی قرار گرفت. با مقایسه بین مقادیر کل کربن آلی خاک اندازه‌گیری شده در مناطق مطالعاتی و مقادیر شبیه‌سازی‌شده به‌وسیله مدل، ضریب تبیین معادل 89/0، ریشه میانگین مربعات خطا 45/3، تفاوت میانگین 84/1، میانگین مطلق خطا 79/2 و کارایی مدل 73/0 به دست آمد. این نتایج بیانگر اعتبار و قابلیت به‌کارگیری مدل است. مدل‌سازی تغییرات اقلیمی آینده مشهد نشان داد که با کاهش بارندگی و افزایش دما و تبخیر، میزان ذخیره کل کربن آلی خاک نسبت به شرایط عدم وقوع تغییرات اقلیمی 13/1 درصد کاهش دارد. با توجه به ثابت سرعت تجزیه ذخایر چهارگانه کربن فعال مدل، هوموس با کندترین سرعت تجزیه، به میزان 96/0 درصد و بخش‌های مواد گیاهی تجزیه‌پذیر، مواد گیاهی مقاوم و زیست‌توده میکروبی به‌ترتیب 18/1، 21/2 و 10/2 درصد نسبت به شرایط اقلیمی کنونی کاهش داشتند. نتایج نشان داد که با گذشت زمان به دلیل تجزیه شدن بخش‌های فعال ماده آلی که به سهولت تجزیه می‌شوند، سرعت تجزیه کاهش می‌یابد. | ||
| کلیدواژه‌ها | ||
| تجزیه ماده آلی؛ ذخایر کربن فعال؛ مدل رتامستد؛ واسنجی و اعتبار سنجی RothC | ||
| عنوان مقاله [English] | ||
| Modeling the impact of climate change on soil organic carbon pools in the semi-arid climate of Mashhad using the RothC model | ||
| نویسندگان [English] | ||
| Saba Bagherifam1؛ Mohammad Amir Delavar2؛ Payman Keshavarz3؛ Parviz Karami4 | ||
| 1PhD student, Dept. of Soil Science, Faculty of Agriculture, University of Zanjan, Zanjan, Iran. | ||
| 2Associate professor, Dept. of soil Science, Faculty of Agriculture, University of Zanjan, Zanjan, Iran | ||
| 3Associate Professor, Dept. of Soil and Water Research, Khorasan Razavi Agricultural and Natural Resources Research Center, AREEO, Mashhad, Iran | ||
| 4Assistant Professor, Dept. of Range and Watershed Management, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran | ||
| چکیده [English] | ||
| Soil organic carbon is a key element in determining soil quality, health, and fertility. Due to the complexity of the structure and relationships of soil organic carbon pools, the use of models is beneficial in identifying the reaction of these pools to the change in ecosystem conditions. So, by using the RothC model, the effect of global warming and climate change on the amount of soil organic carbon pool of the agricultural ecosystem of southeastern of Mashhad was investigated. Therefore, the model was calibrated and validated using data measured in 2020 and available long-term data. Comparing the measured values of soil organic carbon and the simulated values by the model, the coefficient of determination (R2) was 0.89. Root means square error (RMSE): 3.45, mean difference (MD): 1.84, mean absolute error (MAE): 2.79, and model efficiency (EF) was 0.73, demonstrating the validity and suitability of the model. The modeling of the future climate changes of Mashhad showed a decrease in rainfall and an increase in temperature and evaporation, leading the amount of total soil organic carbon (TOC) would decrease by 1.13% compared to the current conditions. Considering the decomposition rate constant of the model's four active carbon pools, humus exhibited the slowest decomposition rate of 0.96%. At the same time, decomposable plant materials (DPM), resistant plant materials (RPM), and microbial biomass (BIO) were decreased by 1.18%, 2.21%, and 2.10%, respectively, compared to the current climate condition. Moreover, over time, the decomposition rate decreased due to the decay of active organic matter pools that are easily decomposed. | ||
| کلیدواژه‌ها [English] | ||
| Decomposition of soil organic matter, Active carbon pools, Rothamsted carbon model, Calibration and Validation of RothC | ||
| مراجع | ||
|
Anderson, T.-H. (2003). Microbial eco-physiological indicators to asses soil quality. Agriculture, Ecosystems & Environment 98, 285-293. Azad, B., and Afzali, S. F. (2019). Evaluation of two soil carbon models performance using measured data in semi-arid rangelands of Bajgah, Fars province. Iranian Journal of Soil and Water Research 50, 819-835 (In Persian). Babaeian, I., and Kouhi, M. (2012). Agroclimatic indices assessment over some selected weather stations of Khorasan Razavi province under climate change scenarios. Journal of water and soil 26, 953-967 (In Persian). Barančíková, G., Halas, J., Guttekova, M., Makovnikova, J., Novakova, M., Skalský, R., and Tarasovičová, Z. (2010). Application of RothC model to predict soil organic carbon stock on agricultural soils of Slovakia. Soil and Water Research 5, 1-9. Bond-Lamberty, B., and Thomson, A. (2010). Temperature-associated increases in the global soil respiration record. Nature 464, 579-582. Campbell, E. E., and Paustian, K. (2015). Current developments in soil organic matter modeling and the expansion of model applications: a review. Environmental Research Letters 10, 123004. Carreiro, M., Sinsabaugh, R., Repert, D., and Parkhurst, D. (2000). Microbial enzyme shifts explain litter decay responses to simulated nitrogen deposition. Ecology 81, 2359-2365. Ciais, P., Wattenbach, M., Vuichard, N., Smith, P., Piao, S., Don, A., Luyssaert, S., Janssens, I., Bondeau, A., and Dechow, R. (2010). The European carbon balance. Part 2: croplands. Global Change Biology 16, 1409-1428. Coleman, K., and Jenkinson, D. (1996). RothC-A Model for the turnover of carbon in soil. In "Evaluation of soil organic matter models", pp. 237-246. Springer. Coleman, K., and Jenkinson, D. (2014). RothC-A Model for the Turnover of Carbon in Soil-Model description and users guide. Rothamsted Research, Harpenden, UK. Diele, F., Marangi, C., and Martiradonna, A. (2021). Non-Standard Discrete RothC Models for Soil Carbon Dynamics. Axioms 10, 56. Doetterl, S., Stevens, A., Six, J., Merckx, R., Van Oost, K., Casanova Pinto, M., Casanova-Katny, A., Muñoz, C., Boudin, M., and Zagal Venegas, E. (2015). Soil carbon storage controlled by interactions between geochemistry and climate. Nature Geoscience 8, 780-783. Dondini, M., Hastings, A., Saiz, G., Jones, M. B., and Smith, P. (2009). The potential of Miscanthus to sequester carbon in soils: comparing field measurements in Carlow, Ireland to model predictions. Gcb Bioenergy 1, 413-425. Fallahi, J., Rezvani, M. P., Nassiri, M. M., and Behdani, M. (2013). Validation of RothC model for evaluation of carbon sequestration in a restorated ecosystem under two different climatic scenari. Journal of Water and Soil. 3, 656-668 (In Persian). Falloon, P., Smith, P., Coleman, K., and 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 Biology & Biochemistry 30, 1207-1211. FAO, I. (2015). Status of the World’s Soil Resources (SWSR)–technical summary. Food and Agriculture Organization of the United Nations and Intergovernmental Technical Panel on Soils, Rome, Italy. Farina, R., Coleman, K., and Whitmore, A. P. (2013). Modification of the RothC model for simulations of soil organic C dynamics in dryland regions. Geoderma 200, 18-30. Farina, R., Marchetti, A., Francaviglia, R., Napoli, R., and Di Bene, C. (2017). Modeling regional soil C stocks and CO2 emissions under Mediterranean cropping systems and soil types. Agriculture, ecosystems & environment 238, 128-141. Francaviglia, R., Baffi, C., Nassisi, A. L., Cassinari, C., and Farina, R. (2013).Use of the RothC model to simulate soil organic dynamic on a silty loam Inceptisol in northern Italy under different fertilization practices. Environmental quality 11, 17-28. Francaviglia, R., Renzi, G., Ledda, L., and Benedetti, A. (2017). Organic carbon pools and soil biological fertility are affected by land use intensity in Mediterranean ecosystems of Sardinia, Italy. Science of the Total Environment 599, 789-796. González-Molina, L., Etchevers-Barra, J., Paz-Pellat, F., Diaz-Solis, H., Fuentes-Ponce, M., Covaleda-Ocon, S., and Pando-Moreno, M. (2011). Performance of the RothC-26.3 model in short-term experiments in Mexican sites and systems. Journal of Agricultural Science 149, 415-425. Gorissen, A., Tietema, A., Joosten, N. N., Estiarte, M., Penuelas, J., Sowerby, A., Emmett, B. A., and Beier, C. (2004). Climate change affects carbon allocation to the soil in shrublands. Ecosystems 7, 650-661. Herbst, M., Welp, G., Macdonald, A., Jate, M., Hädicke, A., Scherer, H., Gaiser, T., Herrmann, F., Amelung, W., and Vanderborght, J. (2018). Correspondence of measured soil carbon fractions and RothC pools for equilibrium and non-equilibrium states. Geoderma 314, 37-46. Hobley, E., Wilson, B., Wilkie, A., Gray, J., and Koen, T. (2015). Drivers of soil organic carbon storage and vertical distribution in Eastern Australia. Plant and Soil 390, 111-127. Inubushi, K., Cheng, W., Mizuno, T., Lou, Y., Hasegawa, T., Sakai, H., and Kobayashi, K. (2011). Microbial biomass carbon and methane oxidation influenced by rice cultivars and elevated CO2 in a Japanese paddy soil. European journal of soil science 62, 69-73. IUSS Working Group WRB. (2015). World Reference Base for Soil Resources 2014, Update 2015. International soil classification system for naming soil and creating legends for soil maps. Food and Agriculture Organization of the United Nations, Rome, Italy. Jobbágy, E. G., and Jackson, R. B. (2000). The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecological applications 10, 423-436. Jones, C., McConnell, C., Coleman, K., Cox, P., Falloon, P., Jenkinson, D., and Powlson, D. (2005). Global climate change and soil carbon stocks; predictions from two contrasting models for the turnover of organic carbon in soil. Global Change Biology 11, 154-166. Kaczynski, R., Siebielec, G., Hanegraaf, M. C., and Korevaar, H. (2017). Modelling soil carbon trends for agriculture development scenarios at regional level. Geoderma 286, 104-115. Kaonga, M., and Coleman, K. (2008). Modelling soil organic carbon turnover in improved fallows in eastern Zambia using the RothC-26.3 model. Forest Ecology and Management 256, 1160-1166. Koven, C. D., Hugelius, G., Lawrence, D. M., and Wieder, W. R. (2017). Higher climatological temperature sensitivity of soil carbon in cold than warm climates. Nature Climate Change 7, 817-822. Lal, R. (2004). Soil carbon sequestration impacts on global climate change and food security. Science 304, 1623-1627. Lefèvre, C., Rekik, F., Alcantara, V., and Wiese, L. (2017). Soil organic carbon: the hidden potential, Food and Agriculture Organization of the United Nations (FAO), Rome, Italy. Leifeld, J., Reiser, R., and Oberholzer, H. R. (2009). Consequences of conventional versus organic farming on soil carbon: results from a 27‐year field experiment. Agronomy Journal. 1, 1204-1218. Ludwig, B., Hu, K., Niu, L., and Liu, X. (2010). Modelling the dynamics of organic carbon in fertilization and tillage experiments in the North China Plain using the Rothamsted Carbon Model—initialization and calculation of C inputs. Plant and Soil 332, 193-206. Ludwig, B., Schulz, E., Rethemeyer, J., Merbach, I., and Flessa, H. (2007). Predictive modelling of C dynamics in the long‐term fertilization experiment at Bad Lauchstädt with the Rothamsted Carbon Model. European Journal of Soil Science 58, 1155-1163. Luxmoore, R. J., Tharp, M. L., and Post, W. M. (2008). Simulated biomass and soil carbon of loblolly pine and cottonwood plantations across a thermal gradient in southeastern United States. Forest ecology and management 254, 291-299. Mondini, C., Coleman, K., and Whitmore, A. (2012). Spatially explicit modelling of changes in soil organic C in agricultural soils in Italy, 2001–2100: Potential for compost amendment. Agriculture, ecosystems & environment 153, 24-32. Muñoz-Rojas, M., Abd-Elmabod, S. K., Zavala, L. M., De la Rosa, D., and Jordán, A. (2017). Climate change impacts on soil organic carbon stocks of Mediterranean agricultural areas: a case study in Northern Egypt. Agriculture, ecosystems & environment 238, 142-152. Nielsen, M. N., Winding, A., Binnerup, S., and Hansen, B. (2002). Microorganisms as indicators of soil health. Niklińska, M., Maryański, M., and Laskowski, R. (1999). Effect of temperature on humus respiration rate and nitrogen mineralization: Implications for global climate change. Biogeochemistry 44, 239-257. Paul, K., Polglase, P., and Richards, G. (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). Forest Ecology and Management 177, 485-501. Sakurai, G., Jomura, M., Yonemura, S., Iizumi, T., Shirato, Y., and Yokozawa, M. (2012). Inversely estimating temperature sensitivity of soil carbon decomposition by assimilating a turnover model and long-term field data. Soil Biology and Biochemistry 46, 191-199. Semi-detailed soil survey of Astan Quds Razavi farm, Mashhad. (1970) Technical report No 245 (In Persian). Scharlemann, J. P., Tanner, E. V., Hiederer, R., and Kapos, V. (2014). Global soil carbon: understanding and managing the largest terrestrial carbon pool. Carbon Management 5, 81-91. Shirato, Y., and Yokozawa, M. (2006). Acid hydrolysis to partition plant material into decomposable and resistant fractions for use in the Rothamsted carbon model. Soil Biology and Biochemistry 38, 812-816. Skjemstad, J., Spouncer, L., Cowie, B., and Swift, R. (2004). Calibration of the Rothamsted organic carbon turnover model (RothC ver. 26.3), using measurable soil organic carbon pools. Soil Research 42, 79-88. Sleutel, S., De Neve, S., Singier, B., and Hofman, G. (2007). Quantification of organic carbon in soils: a comparison of methodologies and assessment of the carbon content of organic matter. Communications in soil science and plant analysis 38, 2647-2657. Smith, J., and Smith, P. (2007). Environmental modelling: an introduction," Oxford University Press. Smith, J., Smith, P., Wattenbach, M., Zaehle, S., Hiederer, R., Jones, R. J., Montanarella, L., Rounsevell, M. D., Reginster, I., and Ewert, F. (2005). Projected changes in mineral soil carbon of European croplands and grasslands, 1990–2080. Global Change Biology 11, 2141-2152. Smith, J. U., Smith, P., Monaghan, R., and MacDonald, A. (2002). When is a measured soil organic matter fraction equivalent to a model pool? European Journal of Soil Science 53, 405-416. Smith, P., Fang, C., Dawson, J. J., and Moncrieff, J. B. (2008). Impact of global warming on soil organic carbon. Advances in agronomy 97, 1-43. Soil Survey Manual. (2014). Kellogg soil survey laboratory methods manual. Soil survey investigations report No 51, version 2 R Burt and soil survey staff (ed), U. S. Department of Agriculture Natural Resources conservation Service. Soil Survey Staff. (2014). Keys to Soil Taxonomy, 12th ed. USDA Natural Resources Conservation Service, Washington, DC. Stevenson, F. J. (1994). "Humus chemistry: genesis, composition, reactions," John Wiley & Sons. Stockmann, U., Adams, M. A., Crawford, J. W., Field, D. J., Henakaarchchi, N., Jenkins, M., Minasny, B., McBratney, A. B., De Courcelles, V. d. R., and Singh, K. (2013). The knowns, known unknowns and unknowns of sequestration of soil organic carbon. Agriculture, Ecosystems & Environment 164, 80-99. Thornthwaite, C. W. (1948). An approach toward a rational classification of climate. Geographical review 38, 55-94. Wan, Y., Lin, E., Xiong, W., and Guo, L. (2011). Modeling the impact of climate change on soil organic carbon stock in upland soils in the 21st century in China. Agriculture, ecosystems & environment 141, 23-31. Weihermüller, L., Graf, A., Herbst, M., and Vereecken, H. (2013). Simple pedotransfer functions to initialize reactive carbon pools of the RothC model. European Journal of Soil Science 6. 4, 567-575. Xu, X., Liu, W., and Kiely, G. (2011). Modeling the change in soil organic carbon of grassland in response to climate change: Effects of measured versus modelled carbon pools for initializing the Rothamsted Carbon model. Agriculture, ecosystems & environment 140, 372-381. Zimmermann, M., Leifeld, J., Schmidt, M., Smith, P., and Fuhrer, J. (2007). Measured soil organic matter fractions can be related to pools in the RothC model. European Journal of Soil Science 58, 658-667. | ||
|
آمار تعداد مشاهده مقاله: 291 تعداد دریافت فایل اصل مقاله: 282 |
||