Skip to main content

Advertisement

SpringerLink
Log in

A scenario-based modeling of climate change impacts on the aboveground net primary production in rangelands of central Iran

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Basak D, Pal S, Patranabis DC (2007) Support vector regression. Neural Inf Process 11:203–225

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Costa AC, Santos JA, Pinto JG (2012) Climate change scenarios for precipitation extremes in Portugal. Theor Appl Climatol 108(1–2):217–234

    Article  Google Scholar 

  • Cristianini N, Shawe-Taylo J (2000) Introduction to support vector machines and other kernel-based learning methods. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Book  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Karl TR (2009) Global climate change impacts in the United States, Cambridge University Press, Cambridge

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Lauenroth WK, Sala OE (1992) Long-term forage production of North American shortgrass steppe. Ecol Appl 2(4):397–403

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Liu L, Zhao X, Chang X, Lian J (2016) Impact of precipitation fluctuation on desert-grassland ANPP. Sustainability 8(12):1245

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Rosenzweig ML (1968) Net primary productivity of terrestrial communities: prediction from climatological data. Am Nat 102(923):67–74

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Suykens JAK, Van Gestel T, De Brabanter J, De Moor B, Vandewalle J (2002) Least squares support vector machines. World Scientific Publishing, Singapore

    Book  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93(4):485–498

    Article  Google Scholar 

  • Vapink VP (1995) The nature of statistical learning theory. Springer, New York

    Book  Google Scholar 

  • 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

    Article  Google Scholar 

  • Walther GR (2010) Community and ecosystem responses to recent climate change. Philos Trans R Soc B: Int J Biol Sci 365(1549):2019–2024

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Yaghmaei L, Soltani S, Khodagholi M (2009) Bioclimatic classification of Isfahan province using multivariate statistical methods. Int J Climatol 29(12):1850–1861

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Zhang GP (2003) Time series forecasting using a hybrid ARIMA and neural network model. Neurocomputing 50(2003):159–175

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • 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

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Natural resources, Isfahan University of Technology, Isfahan, 8415683111, Iran

    Marjan Saki, Mostafa Tarkesh Esfahani & Saeid Soltani

Authors
  1. Marjan Saki
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mostafa Tarkesh Esfahani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Saeid Soltani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marjan Saki.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-018-7864-x

Keywords

Search

Navigation