logo

SCIENCE CHINA Life Sciences, Volume 64 , Issue 5 : 739-751(2021) https://doi.org/10.1007/s11427-020-1837-9

Global patterns and climatic drivers of above- and belowground net primary productivity in grasslands

More info
  • ReceivedOct 3, 2020
  • AcceptedOct 15, 2020
  • PublishedNov 17, 2020

Abstract


Funding

the National Natural Science Foundation of China(31988102)

the National Key Research and Development Program of China(2017YFC0503906)


Acknowledgment

We would like to express our sincere appreciation to all the principal investigators, technicians, etc. who contribute to the global dataset used in this synthesis. We thank team members from Peking University, including Yuhao Feng, Yupin Wang, Haojie Su, Suhui Ma, Chenzhi Wang, and Guoping Chen for assistance in paper writing. This work was supported by the National Natural Science Foundation of China (31988102) and the National Key Research and Development Program of China (2017YFC0503906).


Interest statement

The author(s) declare that they have no conflict of interest.


Supplementary data

SUPPORTING INFORMATION

The supporting information is available online at https://doi.org/10.1007/s11427-020-1837-9. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.


References

[1] Ahlström A., Raupach M.R., Schurgers G., Smith B., Arneth A., Jung M., Reichstein M., Canadell J.G., Friedlingstein P., Jain A.K., et al. The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink. Science, 2015, 348895-899 CrossRef PubMed ADS Google Scholar

[2] Bai Y., Wu J., Xing Q., Pan Q., Huang J., Yang D., Han X.. Primary production and rain use efficiency across a precipitation gradient on the Mongolia plateau. Ecology, 2008, 892140-2153 CrossRef PubMed Google Scholar

[3] Bai W., Wan S., Niu S., Liu W., Chen Q., Wang Q., Zhang W., Han X., Li L.. Increased temperature and precipitation interact to affect root production, mortality, and turnover in a temperate steppe: implications for ecosystem C cycling. Glob Change Biol, 2010, 161306-1316 CrossRef ADS Google Scholar

[4] Bardgett R.D., Mommer L., De Vries F.T.. Going underground: root traits as drivers of ecosystem processes. Trends Ecol Evol, 2014, 29692-699 CrossRef PubMed Google Scholar

[5] Byrne K.M., Lauenroth W.K., Adler P.B.. Contrasting effects of precipitation manipulations on production in two sites within the central grassland region, USA. Ecosystems, 2013, 161039-1051 CrossRef Google Scholar

[6] Chapin, F.S., III, Chapin, M.C., and Matson, P.A. (2011). Principles of Terrestrial Ecosystem Ecology (New York: Springer Science & Business Media), pp. 124–128. Google Scholar

[7] Davidson E.A., Janssens I.A.. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature, 2006, 440165-173 CrossRef PubMed ADS Google Scholar

[8] Del Grosso S., Parton W., Stohlgren T., Zheng D., Bachelet D., Prince S., Hibbard K., Olson R.. Global potential net primary production predicted from vegetation class, precipitation, and temperature. Ecology, 2008, 892117-2126 CrossRef PubMed Google Scholar

[9] Doetterl S., Stevens A., Six J., Merckx R., Van Oost K., Casanova Pinto M., Casanova-Katny A., Muñoz C., Boudin M., Zagal Venegas E., et al. Soil carbon storage controlled by interactions between geochemistry and climate. Nat Geosci, 2015, 8780-783 CrossRef ADS Google Scholar

[10] Esser, G. (2013). NPP Multi-Biome: Global Osnabruck Data, 1937–1981, R1. Data set. Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA. https://doi.10.3334/ORNLDAAC/214. Google Scholar

[11] Epstein, H.E., Lauenroth, W.K., Burke, I.C., and Coffin, D.P. (1997). Effects of temperature and soil texture on ANPP in the U.S. Great Plains. Ecology 78, 722–731. Google Scholar

[12] Fang, J., Liu, G., and Xu, S. (1996). Carbon storage in terrestrial ecosystem of China. In G. Wang and Y. Wen, eds. The Measurement of Greenhouse Gas and Their Release and Related Processes (Beijing: China Environmental Science Press), pp. 391–397. Google Scholar

[13] Fang J., Piao S., Zhou L., He J., Wei F., Myneni R.B., Tucker C.J., Tan K.. Precipitation patterns alter growth of temperate vegetation. Geophys Res Lett, 2005, 32L21411 CrossRef ADS Google Scholar

[14] Field C.B., Behrenfeld M.J., Rand erson J.T., Falkowski P.. Primary production of the biosphere: Integrating terrestrial and oceanic components. Science, 1998, 281237-240 CrossRef PubMed ADS Google Scholar

[15] Gaitan, J.J., Oliva, G.E., Bran, D.E., Maestre, F.T., Aguiar, M.R., Jobbagy, E.G., Buono, G.G., Ferrante, D., Nakamatsu, V.B., Ciari, G., et al. (2014). Vegetation structure is as important as climate for explaining ecosystem function across Patagonian rangelands. J Ecol 102, 1419–1428. Google Scholar

[16] Gale M.R., Grigal D.F.. Vertical root distributions of northern tree species in relation to successional status. Can J For Res, 1987, 17829-834 CrossRef Google Scholar

[17] Gilgen A.K., Buchmann N.. Response of temperate grasslands at different altitudes to simulated summer drought differed but scaled with annual precipitation. Biogeosciences, 2009, 62525-2539 CrossRef ADS Google Scholar

[18] Gill A.L., Finzi A.C.. Belowground carbon flux links biogeochemical cycles and resource-use efficiency at the global scale. Ecol Lett, 2016, 191419-1428 CrossRef PubMed Google Scholar

[19] Gill R.A., Jackson R.B.. Global patterns of root turnover for terrestrial ecosystems. New Phytol, 2000, 14713-31 CrossRef Google Scholar

[20] Gillooly J.F., Brown J.H., West G.B., Savage V.M., Charnov E.L.. Effects of size and temperature on metabolic rate. Science, 2001, 2932248-2251 CrossRef PubMed ADS Google Scholar

[21] Hsu J.S., Powell J., Adler P.B.. Sensitivity of mean annual primary production to precipitation. Glob Change Biol, 2012, 182246-2255 CrossRef ADS Google Scholar

[22] Hui D., Jackson R.B.. Geographical and interannual variability in biomass partitioning in grassland ecosystems: a synthesis of field data. New Phytol, 2006, 16985-93 CrossRef PubMed Google Scholar

[23] Huxman T.E., Smith M.D., Fay P.A., Knapp A.K., Shaw M.R., Loik M.E., Smith S.D., Tissue D.T., Zak J.C., Weltzin J.F., et al. Convergence across biomes to a common rain-use efficiency. Nature, 2004, 429651-654 CrossRef PubMed ADS Google Scholar

[24] IPCC. (2014). Climate Change 2014: Synthesis Report. In Contribution of Working Groups I, II, and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Core Writing Team, Pachauri, R.K., and Meyer, L.A., eds. IPCC, Geneva, Switzerland. pp. 1–9. Google Scholar

[25] Jackson R.B., Canadell J., Ehleringer J.R., Mooney H.A., Sala O.E., Schulze E.D.. A global analysis of root distributions for terrestrial biomes. Oecologia, 1996, 108389-411 CrossRef PubMed ADS Google Scholar

[26] Jackson R.B., Lajtha K., Crow S.E., Hugelius G., Kramer M.G., Piñeiro G.. The ecology of soil carbon: pools, vulnerabilities, and biotic and abiotic controls. Annu Rev Ecol Evol Syst, 2017, 48419-445 CrossRef Google Scholar

[27] Knapp A.K., Ciais P., Smith M.D.. Reconciling inconsistencies in precipitation-productivity relationships: implications for climate change. New Phytol, 2017, 21441-47 CrossRef PubMed Google Scholar

[28] Knapp A.K., Smith M.D.. Variation among biomes in temporal dynamics of aboveground primary production. Science, 2001, 291481-484 CrossRef PubMed ADS Google Scholar

[29] Lauenroth W.K., Sala O.E.. Long-term forage production of North American shortgrass steppe. Ecol Appl, 1992, 2397-403 CrossRef PubMed Google Scholar

[30] Li Y., Reich P.B., Schmid B., Shrestha N., Feng X., Lyu T., Maitner B.S., Xu X., Li Y., Zou D., et al. Leaf size of woody dicots predicts ecosystem primary productivity. Ecol Lett, 2020, 231003-1013 CrossRef PubMed Google Scholar

[31] Liu L., Greaver T.L.. A global perspective on belowground carbon dynamics under nitrogen enrichment. Ecol Lett, 2010, 13819-828 CrossRef PubMed Google Scholar

[32] Liu Y., Wang C., He N., Wen X., Gao Y., Li S., Niu S., Butterbach-Bahl K., Luo Y., Yu G.. A global synthesis of the rate and temperature sensitivity of soil nitrogen mineralization: latitudinal patterns and mechanisms. Glob Change Biol, 2017, 23455-464 CrossRef PubMed ADS Google Scholar

[33] Long S.P., Garcia Moya E., Imbamba S.K., Kamnalrut A., Piedade M.T.F., Scurlock J.M.O., Shen Y.K., Hall D.O.. Primary productivity of natural grass ecosystems of the tropics: a reappraisal. Plant Soil, 1989, 115155-166 CrossRef Google Scholar

[34] López-Mársico L., Altesor A., Oyarzabal M., Baldassini P., Paruelo J.M.. Grazing increases below-ground biomass and net primary production in a temperate grassland. Plant Soil, 2015, 392155-162 CrossRef Google Scholar

[35] Luo Y., Jiang L., Niu S., Zhou X.. Nonlinear responses of land ecosystems to variation in precipitation. New Phytol, 2017, 2145-7 CrossRef PubMed Google Scholar

[36] Luyssaert S., Inglima I., Jung M., Richardson A.D., Reichstein M., Papale D., Piao S.L., Schulze E.D., Wingate L., Matteucci G., et al. CO2 balance of boreal, temperate, and tropical forests derived from a global database. Glob Change Biol, 2007, 132509-2537 CrossRef ADS Google Scholar

[37] Ma Z., Guo D., Xu X., Lu M., Bardgett R.D., Eissenstat D.M., McCormack M.L., Hedin L.O.. Evolutionary history resolves global organization of root functional traits. Nature, 2018, 55594-97 CrossRef PubMed ADS Google Scholar

[38] Malhi Y., Doughty C., Galbraith D.. The allocation of ecosystem net primary productivity in tropical forests. Phil Trans R Soc B, 2011, 3663225-3245 CrossRef PubMed Google Scholar

[39] Michaletz S.T., Cheng D., Kerkhoff A.J., Enquist B.J.. Convergence of terrestrial plant production across global climate gradients. Nature, 2014, 51239-43 CrossRef PubMed ADS Google Scholar

[40] Morel A.C., Adu Sasu M., Adu-Bredu S., Quaye M., Moore C., Ashley Asare R., Mason J., Hirons M., McDermott C.L., Robinson E.J.Z., et al. Carbon dynamics, net primary productivity and human-appropriated net primary productivity across a forest-cocoa farm landscape in West Africa. Glob Change Biol, 2019, 252661-2677 CrossRef PubMed ADS Google Scholar

[41] Nakagawa, S., and Schielzeth, H.A. (2013). General and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol 4, 133–142. Google Scholar

[42] Nemani R.R., Keeling C.D., Hashimoto H., Jolly W.M., Piper S.C., Tucker C.J., Myneni R.B., Running S.W.. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 2003, 3001560-1563 CrossRef PubMed ADS Google Scholar

[43] Noy-Meir I.. Desert ecosystems: environment and producers. Annu Rev Ecol Syst, 1973, 425-51 CrossRef Google Scholar

[44] Olson, R.J., Scurlock, J.M.O., and Prince, S.D. (2013). NPP Multi-Biome: NPP and Driver Data for Ecosystem Model-Data Intercomparison, R2. Data set. Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA. https://doi.10.3334/ORNLDAAC/615. Google Scholar

[45] Peng Y., Guo D., Yang Y.. Global patterns of root dynamics under nitrogen enrichment. Glob Ecol Biogeogr, 2017, 26102-114 CrossRef Google Scholar

[46] Piao S., Fang J., Zhou L., Zhu B., Tan K., Tao S.. Changes in vegetation net primary productivity from 1982 to 1999 in China. Glob Biogeochem Cycle, 2005, 19GB2027 CrossRef ADS Google Scholar

[47] Campos G.E.P, Moran M.S., Huete A., Zhang Y., Bresloff C., Huxman T.E., Eamus D., Bosch D.D., Buda A.R., Gunter S.A., et al. Ecosystem resilience despite large-scale altered hydroclimatic conditions. Nature, 2013, 494349-352 CrossRef PubMed ADS Google Scholar

[48] Poulter B., Frank D., Ciais P., Myneni R.B., Andela N., Bi J., Broquet G., Canadell J.G., Chevallier F., Liu Y.Y., et al. Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature, 2014, 509600-603 CrossRef PubMed ADS Google Scholar

[49] R Development Core Team. (2017). R: A Languange and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. Google Scholar

[50] Sajedi T., Prescott C.E., Seely B., Lavkulich L.M.. Relationships among soil moisture, aeration and plant communities in natural and harvested coniferous forests in coastal British Columbia, Canada. J Ecol, 2012, 100605-618 CrossRef Google Scholar

[51] Sala O.E., Gherardi L.A., Reichmann L., Jobbágy E., Peters D.. Legacies of precipitation fluctuations on primary production: theory and data synthesis. Phil Trans R Soc B, 2012, 3673135-3144 CrossRef PubMed Google Scholar

[52] Scandellari F., Ventura M., Gioacchini P., Vittori Antisari L., Tagliavini M.. Seasonal pattern of net nitrogen rhizodeposition from peach (Prunus persica (L.) Batsch) trees in soils with different textures. Agr Ecosyst Environ, 2010, 136162-168 CrossRef Google Scholar

[53] Schuur E.A.G.. The effect of water on decomposition dynamics in mesic to wet Hawaiian montane forests. Ecosystems, 2001, 4259-273 CrossRef Google Scholar

[54] Schuur E.A.G.. Productivity and global climate revisited: the sensitivity of tropical forest growth to precipitation. Ecology, 2003, 841165-1170 CrossRef Google Scholar

[55] Scurlock J.M.O., Johnson K., Olson R.J.. Estimating net primary productivity from grassland biomass dynamics measurements. Glob Change Biol, 2002, 8736-753 CrossRef ADS Google Scholar

[56] Scurlock, J.M.O., Johnson, K.R., and Olson, R.J. (2015). NPP Grassland: NPP Estimates from Biomass Dynamics for 31 Sites, 1948–1994, R1. Data set. Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA. Google Scholar

[57] Slessarev E.W., Lin Y., Bingham N.L., Johnson J.E., Dai Y., Schimel J.P., Chadwick O.A.. Water balance creates a threshold in soil pH at the global scale. Nature, 2016, 540567-569 CrossRef PubMed ADS Google Scholar

[58] Stegen J.C., Ferriere R., Enquist B.J.. Evolving ecological networks and the emergence of biodiversity patterns across temperature gradients. Proc R Soc B, 2012, 2791051-1060 CrossRef PubMed Google Scholar

[59] Sultan S.E.. Plant developmental responses to the environment: eco-devo insights. Curr Opin Plant Biol, 2010, 1396-101 CrossRef PubMed Google Scholar

[60] Tian D., Yan Z., Niklas K.J., Han W., Kattge J., Reich P.B., Luo Y., Chen Y., Tang Z., Hu H., et al. Global leaf nitrogen and phosphorus stoichiometry and their scaling exponent. Natl Sci Rev, 2018, 5728-739 CrossRef Google Scholar

[61] Valentine H.T., Mäkelä A.. Modeling forest stand dynamics from optimal balances of carbon and nitrogen. New Phytol, 2012, 194961-971 CrossRef PubMed Google Scholar

[62] Vogt K.A., Vogt D.J., Bloomfield J.. Analysis of some direct and indirect methods for estimating root biomass and production of forest at an ecosystem level. Plant Soil, 1998, 20071-89 CrossRef Google Scholar

[63] Wang N., Quesada B., Xia L., Butterbach-Bahl K., Goodale C.L., Kiese R.. Effects of climate warming on carbon fluxes in grasslands—A global meta-analysis. Glob Change Biol, 2019a, 251839-1851 CrossRef PubMed ADS Google Scholar

[64] Wang, J., Sun, J., Yu, Z., Li, Y., Tian, D., Wang, B., Li, Z., and Niu, S. (2019b). Vegetation type controls root turnover in global grasslands. Glob Ecol Biogeogr 28, 442–455. Google Scholar

[65] White, R., Murray, S., and Rohweder, M. (2000). Pilot analysis of global ecosystems: grassland ecosystems technical report. World Resources Institute, Washington DC, USA. Google Scholar

[66] Wilcox K.R., Blair J.M., Smith M.D., Knapp A.K.. Does ecosystem sensitivity to precipitation at the site-level conform to regional-scale predictions?. Ecology, 2016, 97561-568 CrossRef Google Scholar

[67] Wilcox K.R., Shi Z., Gherardi L.A., Lemoine N.P., Koerner S.E., Hoover D.L., Bork E., Byrne K.M., Cahill Jr. J., Collins S.L., et al. Asymmetric responses of primary productivity to precipitation extremes: A synthesis of grassland precipitation manipulation experiments. Glob Change Biol, 2017, 234376-4385 CrossRef PubMed Google Scholar

[68] Wright I.J., Dong N., Maire V., Prentice I.C., Westoby M., Díaz S., Gallagher R.V., Jacobs B.F., Kooyman R., Law E.A., et al. Global climatic drivers of leaf size. Science, 2017, 357917-921 CrossRef PubMed ADS Google Scholar

[69] Wu Z., Dijkstra P., Koch G.W., Peñuelas J., Hungate B.A.. Responses of terrestrial ecosystems to temperature and precipitation change: a meta-analysis of experimental manipulation. Glob Change Biol, 2011, 17927-942 CrossRef ADS Google Scholar

[70] Xia J., Niu S., Ciais P., Janssens I.A., Chen J., Ammann C., Arain A., Blanken P.D., Cescatti A., Bonal D., et al. Joint control of terrestrial gross primary productivity by plant phenology and physiology. Proc Natl Acad Sci USA, 2015, 1122788-2793 CrossRef PubMed ADS Google Scholar

[71] Xu B., Yang Y., Li P., Shen H., Fang J.. Global patterns of ecosystem carbon flux in forests: A biometric data-based synthesis. Glob Biogeochem Cycle, 2014, 28962-973 CrossRef ADS Google Scholar

[72] Xu X., Sherry R.A., Niu S., Li D., Luo Y.. Net primary productivity and rain-use efficiency as affected by warming, altered precipitation, and clipping in a mixed-grass prairie. Glob Change Biol, 2013, 192753-2764 CrossRef PubMed ADS Google Scholar

[73] Yang Y., Fang J., Ji C., Han W.. Above- and belowground biomass allocation in Tibetan grasslands. J Vegetat Sci, 2009, 20177-184 CrossRef Google Scholar

[74] Yang Y., Fang J., Ma W., Guo D., Mohammat A.. Large-scale pattern of biomass partitioning across China’s grasslands. Glob Ecol Biogeogr, 2010, 19268-277 CrossRef Google Scholar

[75] Yang Y., Fang J., Ma W., Wang W.. Relationship between variability in aboveground net primary production and precipitation in global grasslands. Geophys Res Lett, 2008, 35L23710 CrossRef ADS Google Scholar

[76] Zhang C., Kellomäki S., Zhong Q., Wang K., Gong J., Qiao Y., Zhou X., Gao W.. Seasonal biomass allocation in a boreal perennial grass (Phalaris arundinacea L.) under elevated temperature and CO2 with varying water regimes. Plant Growth Regul, 2014, 74153-164 CrossRef Google Scholar

[77] Zhang, S., Zhang, Y., and Ma, K. (2016). Latitudinal variation in herbivory: hemispheric asymmetries and the role of climatic drivers. J Ecol 104, 1089–1095. Google Scholar

[78] Zhao L., Li Y., Xu S., Zhou H., Gu S., Yu G., Zhao X.. Diurnal, seasonal and annual variation in net ecosystem CO2 exchange of an alpine shrubland on Qinghai-Tibetan plateau. Glob Change Biol, 2006, 121940-1953 CrossRef ADS Google Scholar

[79] Zhou X., Ge Z.M., Kellomäki S., Wang K.Y., Peltola H., Martikainen P.. Effects of elevated CO2 and temperature on leaf characteristics, photosynthesis and carbon storage in aboveground biomass of a boreal bioenergy crop (Phalaris arundinacea L.) under varying water regimes. GCB Bioenergy, 2011, 3223-234 CrossRef Google Scholar

[80] Zhou X., Talley M., Luo Y.. Biomass, litter, and soil respiration along a precipitation gradient in southern Great Plains, USA. Ecosystems, 2009, 121369-1380 CrossRef Google Scholar

  • Figure 1

    Geographical distribution of sites collected in this study (A) and frequency distributions of productivity variables in global grasslands. B, Aboveground net primary productivity (ANPP). C, Belowground net primary productivity (BNPP). D, Total net primary productivity (TNPP). E, The fraction of BNPP to TNPP (fBNPP). AGM, alpine grassland & meadow; TGM, temperate grassland & meadow; TGS, tropical grassland & savanna.

  • Figure 2

    Comparison of productivity variables among grassland types in global grasslands. A, ANPP, aboveground primary productivity. B, BNPP, belowground net primary productivity. C, TNPP, total net primary productivity. D, fBNPP, the fraction of BNPP to TNPP. AGM, alpine grassland & meadow; TGM, temperate grassland & meadow; TGS, tropical grassland & savanna. Different lower-case letters indicate significant differences (P<0.05) between types based on a linear mixed effects model (generated using the “lmer” function in R) with sites included as a random effect. ANPP, BNPP, and TNPP were first log10-transformed to correct for non-normality.

  • Figure 3

    Relationships between productivity variables and mean annual temperature (MAT) and mean annual precipitation (MAP) in global grasslands. A and B, ANPP, aboveground primary productivity. C and D, BNPP, belowground net primary productivity. E and F, TNPP, total net primary productivity. G and H, fBNPP, the fraction of BNPP to TNPP. ANPP, BNPP, and TNPP were log10-transformed for normalization. Solid and dashed red lines represent regression fitted by mixed linear models. For details, see Table S1 in Supporting Information.

  • Figure 4

    Relationships between productivity variables and mean annual actual evapotranspiration (AET) and mean annual aridity index (AI) in global grasslands. A and B, ANPP, aboveground primary productivity. C and D, BNPP, belowground net primary productivity. E and F, TNPP, total net primary productivity. G and H, fBNPP, the fraction of BNPP to TNPP. ANPP, BNPP, and TNPP were log10-transformed for normalization. Solid and dashed red lines represent regression fitted by mixed linear models. For details, see Table S1 in Supporting Information.

  • Figure 5

    Comparison of spatial models (red lines) and long-term temporal models (black lines) for ANPP and BNPP in global grasslands. A, ANPP vs. temperature. B, ANPP vs. precipitation. C, BNPP vs. temperature. D, BNPP vs. precipitation. Spatial models were equal to those in Figure 3A–D and were constructed based on 1,171 sites of ANPP and 376 sites of BNPP. Temporal models were constructed based on long-term series data for each site. ANPP and BNPP were log10-transformed for normalization. The study duration of ANPP for most sites was more than 10 years, except for TOL, HIB, and KLN (4, 5, and 6 years, respectively), because long-term observation data of ANPP in alpine or humid grasslands and tundra were still scarce to date. The study duration of BNPP was 5 years or more. Details on site information and site-specific relationships using linear regression are presented in Tables S2 and S3 in Supporting Information.

  • Table 1   Changes in ANPP, BNPP, TNPP, and fBNPP for different grassland typesa)

    Grassland types

    ANPP (g m–2 a–1)

    BNPP (g m–2 a–1)

    TNPP (g m–2 a–1)

    fBNPP

    n

    Mean

    SE

    n

    Mean

    SE

    n

    Mean

    SE

    n

    Mean

    SE

    AGM

    260

    129.6

    7.3

    50

    672.0

    89.9

    49

    902.8

    103.0

    48

    0.71

    0.02

    Desert

    69

    115.7

    13.5

    31

    525.2

    123.6

    38

    574.5

    117.1

    28

    0.65

    0.03

    TGM

    574

    240.6

    8.8

    126

    593.4

    53.6

    103

    935.8

    78.2

    94

    0.61

    0.02

    TGS

    235

    592.3

    29.0

    157

    614.2

    38.2

    142

    1320.7

    79.9

    135

    0.47

    0.01

    Tundra

    33

    82.0

    10.6

    12

    118.8

    12.0

    18

    169.2

    25.9

    10

    0.73

    0.02

    Total

    1171

    274.7

    8.9

    376

    591.8

    28.9

    350

    1008.7

    47.1

    315

    0.57

    0.01

    Abbreviation: ANPP, aboveground primary productivity; BNPP, belowground net primary productivity; TNPP, total net primary productivity; fBNPP, the fraction of BNPP to TNPP. AGM, alpine grassland & meadow; TGM, temperate grassland & meadow; TGS, tropical grassland & savanna.

qqqq

Contact and support