Abstract
Climate change has largely affected natural ecosystems around the world, especially in arid and semi-arid regions. Rangelands have great significance in carbon cycle due to their contribution for a large part of regional net primary production (NPP). These ecosystems are vulnerable to climate change. Given the Isfahan Province, central Iran, as the study area, an attempt is made to simulate changes in the rangeland aboveground net primary production (ANPP) under three RCP (representative concentration pathways) climate change scenarios (RCP2.6, RCP4.5 and RCP8.5) for two periods (2050s and 2070s). The rangeland ANPP was estimated using a support vector machine (SVM) model with RMSE of 23.78 g C m−2 year−1 and R2 of 0.92. Changes in the mean annual precipitation and temperature due to climate change were projected by ensembling 14 General Circulation Models (GCMs) through a weighting approach. The results indicated trends towards drier and warmer conditions in future periods. The maximum decreasing precipitation and increasing temperature are projected to occur in western and eastern parts of the province, respectively. The mean annual ANPP showed different trends between bioclimatic zones. It decreased about 25.9% in the sub-humid and cold zone and increased over 120% in the hyper-arid and warm zone by 2070s. Generally, rangelands in western and southwestern parts of the province are found to be more vulnerable to future drying–warming condition. These results highlight the need of adopting proper policies to encounter various effects of climate change in this region.
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Basak D, Pal S, Patranabis DC (2007) Support vector regression. Neural Inf Process 11:203–225
Briske DD, Joyce LA, Polley HW, Brown JR, Wolter K, Morgan JA et al (2015) Climate-change adaptation on rangelands: linking regional exposure with diverse adaptive capacity. Front Ecol Environ 13(5):249–256
Costa AC, Santos JA, Pinto JG (2012) Climate change scenarios for precipitation extremes in Portugal. Theor Appl Climatol 108(1–2):217–234
Cristianini N, Shawe-Taylo J (2000) Introduction to support vector machines and other kernel-based learning methods. Cambridge University Press, Cambridge
Dai E, Wu Z, Ge Q, Xi W, Wang X (2016) Predicting the responses of forest distribution and aboveground biomass to climate change under RCP scenarios in southern China. Glob Change Biol 22(11):3642–3661
Darvishzadeh R, Skidmore AK, Mirzaie M, Atzberger C, Schlerf M (2014) Fresh biomass estimation in heterogeneous grassland using hyperspectral measurements and multivariate statistical analysis. In InAGU Fall Meeting Abstracts (Vol. 1, No. 7)
Del Grosso S, Parton W, Stohlgren T, Zheng D, Bachelet D, Prince S et al (2008) Global potential net primary production predicted from vegetation class, precipitation, and temperature. J Ecol 89(8):2117–2126
Dufresne JL, Foujols MA, Denvil S, Caubel A, Marti O, Aumont O et al (2013) Climate change projections using the IPSL-CM5 earth system model: from CMIP3 to CMIP5. Clim Dyn 40(9–10):2123–2165
Dulamsuren C, Wommelsdorf T, Zhao F, Xue Y, Zhumadilov BZ, Leuschner C, Hauck M (2013) Increased summer temperatures reduce the growth and regeneration of Larix sibirica in southern boreal forests of eastern Kazakhstan. J Ecosyst 16(8):1536–1549
Eisfelder C (2013) Modelling net primary productivity and above-ground biomass for mapping of spatial biomass distribution in Kazakhstan. Doctoral dissertation, Technische Universität Dresden
Elmahdi A, Shahkarami N, Morid S, Massah Bavani AR (2009) Assessing the impact of AOGCMs uncertainty on the risk of agricultural water demand caused by climate change. In 18th World IMACS/MODSIM Congress, Cairns, Australia, pp 13–17
Engel EC, Weltzin JF, Norby RJ, Classen AT (2009) Responses of an old-field plant community to interacting factors of elevated [CO2], warming, and soil moisture. J Plant Ecol 2(1):1–11
Field CB (2012) Managing the risks of extreme events and disasters to advance climate change adaptation: special report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
Gang C, Wang Z, Zhou W, Chen Y, Li J, Cheng J et al (2015) Projecting the dynamics of terrestrial net primary productivity in response to future climate change under the RCP2. 6 scenario. Environ Earth Sci 74(7):5949–5959
Gao QZ, Wan YF, Li Y, Qin XB, Jiangcun W, Xu HM (2010) Spatial and temporal pattern of alpine grassland condition and its response to human activities in Northern Tibet, China. Rangeland J 32(2):165–173
Gao Q, Guo Y, Xu H, Ganjurjav H, Li Y, Wan Y et al (2016) Climate change and its impacts on vegetation distribution and net primary productivity of the alpine ecosystem in the Qinghai-Tibetan Plateau. Sci Total Environ 554:34–41
Gohari A, Eslamian S, Abedi-Koupaei J, Bavani AM, Wang D, Madani K (2013) Climate change impacts on crop production in Iran’s Zayandeh-Rud River Basin. Sci Total Environ 442:405–419
Han F, Zhang Q, Buyantuev A, Niu J, Liu P, Li X et al (2015) Effects of climate change on phenology and primary productivity in the desert steppe of Inner Mongolia. J Arid Land 7(2):251–263
Hsu CW, Chang CC, Lin CJ (2015) A practical guide to support vector classification. https://www.csie.ntu.edu.tw
Imbach PA, Locatelli B, Molina LG, Ciais P, Leadley PW (2013) Climate change and plant dispersal along corridors in fragmented landscapes of Mesoamerica. Ecol Evol 3(9):2917–2932
Jaberalansar Z, Tarkesh M, Bassiri M, Pourmanafi S (2017) Modelling the impact of climate change on rangeland forage production using a generalized regression neural network: a case study in Isfahan Province, Central Iran. J Arid Land 9(4):489–503
Jerez S, Montavez JP, Gomez-Navarro JJ, Lorente-Plazas R, Garcia-Valero JA, Jimenez-Guerrero P (2013) A multi-physics ensemble of regional climate change projections over the Iberian Peninsula. Clim Dyn 41(7–8):1749–1768
Kardol P, Cregger MA, Campany CE, Classen AT (2010) Soil ecosystem functioning under climate change: plant species and community effects. J Ecol 91(3):767–781
Karl TR (2009) Global climate change impacts in the United States, Cambridge University Press, Cambridge
Kerns BK, Powell DC, Mellmann-Brown S, Carnwath G, Kim JB (2018) Effects of projected climate change on vegetation in the Blue Mountains ecoregion, USA. Clim Serv 10:33–43
Kloster S, Dentener F, Feichter J, Raes F, Lohmann U, Roeckner E, Fischer-Bruns I (2010) A GCM study of future climate response to aerosol pollution reductions. Clim Dyn 34(7–8):1177–1194
Knapp AK, Fay PA, Blair JM, Collins SL, Smith MD, Carlisle JD et al (2002) Rainfall variability, carbon cycling, and plant species diversity in a mesic grassland. Science 298(5601):2202–2205
Kunkel KE, Bromirski PD, Brooks HE et al (2008) Observed changes in weather and climate extremes. In: Karl TR, Meehl GA, Miller CD, Hassol SJ, Waple AM, Murray WL (eds) Weather and climate extremes in a changing climate. Regions of focus: North America, Hawaii, Caribbean, and U.S. Pacific Islands. A report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research, Washington, DC
Lauenroth WK, Sala OE (1992) Long-term forage production of North American shortgrass steppe. Ecol Appl 2(4):397–403
Lehodey P, Senina I, Calmettes B, Hampton J, Nicol S (2013) Modelling the impact of climate change on Pacific skipjack tuna population and fisheries. Clim Chang 119(1):95–109
Li J, Lin S, Taube F, Pan Q, Dittert K (2011) Above and belowground net primary productivity of grassland influenced by supplemental water and nitrogen in Inner Mongolia. Plant Soil 340(1–2):253–264
Liang W, Yang Y, Fan D, Guan H, Zhang T, Long D et al (2015) Analysis of spatial and temporal patterns of net primary production and their climate controls in China from 1982 to 2010. Agric For Meteorol 204:22–36
Liu GQ (2011) Comparison of Regression and ARIMA models with Neural Network models to forecast the daily stream flow. PhD thesis, University of Delaware, p 545
Liu J, Fritz S, Van Wesenbeeck CFA, Fuchs M, You L, Obersteiner M, Yang H (2008) A spatially explicit assessment of current and future hotspots of hunger in Sub-Saharan Africa in the context of global change. Glob Planet Chang 64(3–4):222–235
Liu C, Dong X, Liu Y (2015) Changes of NPP and their relationship to climate factors based on the transformation of different scales in Gansu, China. J Catena 125:190–199
Liu L, Zhao X, Chang X, Lian J (2016) Impact of precipitation fluctuation on desert-grassland ANPP. Sustainability 8(12):1245
Lyra A, Imbach P, Rodriguez D, Chou SC, Georgiou S, Garofolo L (2017) Projections of climate change impacts on central America tropical rainforest. Clim Change 141(1):93–105
Mirik M, Chaudhuri S, Surber B, Ale S, Ansley RJ (2013) Evaluating biomass of juniper trees (Juniperus pinchotii) from imagery-derived canopy area using the support vector machine classifier. Adv Remote Sens 2(02):181–192
Morgan JA, Milchunas DG, LeCain DR, West M, Mosier AR (2007) Carbon dioxide enrichment alters plant community structure and accelerates shrub growth in the shortgrass steppe. Proc Natl Acad Sci USA 104(37):14724–14729
Morid S, Bavani ARM (2010) Exploration of potential adaptation strategies to climate change in the Zayandeh Rud irrigation system, Iran. J Irrig Drain Eng-ASCE 59(2):226–238
Mowll W, Blumenthal DM, Cherwin K, Smith A, Symstad AJ, Vermeire LT et al (2015) Climatic controls of aboveground net primary production in semi-arid grasslands along a latitudinal gradient portend low sensitivity to warming. Oecologia 177(4):959–969
Nemani RR, Keeling CD, Hashimoto H, Jolly WM, Piper SC, Tucker CJ et al (2003) Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science 300(5625):1560–1563
Panagoulia D, Vlahogianni EI (2014) Nonlinear dynamics and recurrence analysis of extreme precipitation for observed and general circulation model generated climates. Hydrol Process 28(4):2281–2292
Panagoulia D, Vlahogianni EI (2018) Recurrence quantification analysis of extremes of maximum and minimum temperature patterns for different climate scenarios in the Mesochora catchment in Central-Western Greece. Atmos Res 205:33–47
Panagoulia D, Bárdossy A, Lourmas G (2008) Multivariate stochastic downscaling models for generating precipitation and temperature scenarios of climate change based on atmospheric circulation. Global Nest J 10(2):263–272
Panagoulia D, Tsekouras GJ, Kousiouris G (2017) A multi-stage methodology for selecting input variables in ANN forecasting of river flows. Glob NEST J 19:49–57
Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, Hanson CE (2007) Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
Polley HW, Briske DD, Morgan JA, Wolter K, Bailey DW, Brown JR (2013) Climate change and North American rangelands: trends, projections, and implications. Rangel Ecol Manage 66(5):493–511
Rashid I, Romshoo SA, Chaturvedi RK, Ravindranath NH, Sukumar R, Jayaraman M (2015) Projected climate change impacts on vegetation distribution over Kashmir Himalayas. Clim Change 132(4):601–613
Reeves MC, Moreno AL, Bagne KE, Running SW (2014) Estimating climate change effects on net primary production of rangelands in the United States. Clim Change 126(3–4):429–442
Rosenzweig ML (1968) Net primary productivity of terrestrial communities: prediction from climatological data. Am Nat 102(923):67–74
Rustad LEJL, Campbell J, Marion G, Norby R, Mitchell M, Hartley A (2001) A meta-analysis of the response of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming. J Oecol 126(4):543–562
Sala OE, Parton WJ, Joyce LA, Lauenroth WK (1988) Primary production of the central grassland region of the United States. J Ecol 69(1):40–45
Sitch S, Huntingford C, Gedney N, Levy PE, Lomas M, Piao SL et al (2008) Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five dynamic global vegetation models (DGVMs). Glob Chang Biol 14(9):2015–2039
Solomon S (2007) Climate change 2007—the physical science basis: Working group I contribution to the fourth assessment report of the IPCC (Vol. 4). Cambridge University Press, Cambridge
Sung S, Forsell N, Kindermann G, Lee DK (2016) Estimating net primary productivity under climate change by application of global forest model (G4M). J Korean Soc People Plant Environ 19(6):549–558
Suykens JAK, Van Gestel T, De Brabanter J, De Moor B, Vandewalle J (2002) Least squares support vector machines. World Scientific Publishing, Singapore
Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93(4):485–498
Vapink VP (1995) The nature of statistical learning theory. Springer, New York
Vermeire LT, Heitschmidt RK, Rinella MJ (2009) Primary productivity and precipitation-use efficiency in mixed-grass prairie: a comparison of northern and southern US sites. Rangel Ecol Manag 62(3):230–239
Walther GR (2010) Community and ecosystem responses to recent climate change. Philos Trans R Soc B: Int J Biol Sci 365(1549):2019–2024
Wang B, Kim HJ, Kikuchi K, Kitoh A (2011) Diagnostic metrics for evaluation of annual and diurnal cycles. Clim Dyn 37(5–6):941–955
Xu X, Sherry RA, Niu S, Li D, Luo Y (2013) Net primary productivity and rain-use efficiency as affected by warming, altered precipitation, and clipping in a mixed-grass prairie. Glob Change Biol 19(9):2753–2764
Yaghmaei L, Soltani S, Khodagholi M (2009) Bioclimatic classification of Isfahan province using multivariate statistical methods. Int J Climatol 29(12):1850–1861
Zaehle S, Sitch S, Smith B, Hatterman F (2005) Effects of parameter uncertainties on the modeling of terrestrial biosphere dynamics. Glob Biogeochem Cy 19(3):1–16
Zareian MJ, Eslamian S, Safavi HR (2015) A modified regionalization weighting approach for climate change impact assessment at watershed scale. Theor Appl Climatol 122(3–4):497–516
Zhang GP (2003) Time series forecasting using a hybrid ARIMA and neural network model. Neurocomputing 50(2003):159–175
Zhang Q, Xu CY, Tao H, Jiang T, Chen YD (2010) Climate changes and their impacts on water resources in the arid regions: a case study of the Tarim River basin, China. Stoch Env Res Risk A 24(3):349–358
Zhang CH, Wang MJ, Zhang L et al (2013) Responses of aboveground net primary productivity to climate change in hulunbel meadow grassland. Acta Prataculturae Sinica 22(3):41–50
Zhang B, Zhang L, Xie D, Yin X, Liu C, Liu G (2015) Application of synthetic NDVI time series blended from Landsat and MODIS data for grassland biomass estimation. Rem Sens 8(1):10
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Saki, M., Tarkesh Esfahani, M. & Soltani, S. A scenario-based modeling of climate change impacts on the aboveground net primary production in rangelands of central Iran. Environ Earth Sci 77, 670 (2018). https://doi.org/10.1007/s12665-018-7864-x
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DOI: https://doi.org/10.1007/s12665-018-7864-x