Journal of Resources and Ecology ›› 2022, Vol. 13 ›› Issue (1): 129-141.DOI: 10.5814/j.issn.1674-764x.2022.01.015
• Industry Ecology and Regional Development • Previous Articles Next Articles
ZHANG Xianzhou1,2(), LI Meng3, WU Jianshuang4, HE Yongtao1,2, NIU Ben1,*(
)
Received:
2021-09-13
Accepted:
2021-10-13
Online:
2022-01-30
Published:
2022-01-08
Contact:
NIU Ben
About author:
ZHANG Xianzhou, E-mail: zhangxz@igsnrr.ac.cn
Supported by:
ZHANG Xianzhou, LI Meng, WU Jianshuang, HE Yongtao, NIU Ben. Alpine Grassland Aboveground Biomass and Theoretical Livestock Carrying Capacity on the Tibetan Plateau[J]. Journal of Resources and Ecology, 2022, 13(1): 129-141.
Add to citation manager EndNote|Ris|BibTeX
URL: http://www.jorae.cn/EN/10.5814/j.issn.1674-764x.2022.01.015
Time period | Study area (104 km2) | Methods | Variables considered | AGB (g m-2) | References |
---|---|---|---|---|---|
1960-2002 | 147.74 | Century | Climate and soil data | 70.00 | Zhang et al., |
2002-2004 | 139.00 | Orchidee | Climate, soil and LAI data | 119.78 | Tan et al., |
1980-1990 | 113.60 | Area-weighted average | - | 58.11 | Ni, |
- | 101.10 | Area-weighted average | - | 61.15 | Luo et al., |
2001-2004 | - | Filed observations | - | 59.30 | Yang et al., |
2001-2004 | 112.80 | Linear regression | EVI | 68.80 | Yang et al., |
1982-2006 | 129.50 | Exponential regression | NDVI | 74.11 | Ma et al., |
2005 | 122.80 | Exponential regression | NDVI | 43.33 | Xu et al., |
- | 124.00 | Exponential regression | NDVI | 78.02 | Piao et al., |
1982-2013 | 154.48 | Exponential regression | NDVI | 104.40 | Jiao et al., |
2000-2014 | 151.11 | Random forest | Climate, terrain and NDVI | 77.12 | Zeng et al., |
- | 132.00 | Random forest | Climate and NDVI | 78.40 | Xia et al., |
2000-2017 | - | Random forest | Climate, terrain and NDVI | 59.63 | Gao et al., |
Table 1 Estimated mean aboveground biomass (AGB) of alpine grassland on the Tibetan Plateau in various published studies
Time period | Study area (104 km2) | Methods | Variables considered | AGB (g m-2) | References |
---|---|---|---|---|---|
1960-2002 | 147.74 | Century | Climate and soil data | 70.00 | Zhang et al., |
2002-2004 | 139.00 | Orchidee | Climate, soil and LAI data | 119.78 | Tan et al., |
1980-1990 | 113.60 | Area-weighted average | - | 58.11 | Ni, |
- | 101.10 | Area-weighted average | - | 61.15 | Luo et al., |
2001-2004 | - | Filed observations | - | 59.30 | Yang et al., |
2001-2004 | 112.80 | Linear regression | EVI | 68.80 | Yang et al., |
1982-2006 | 129.50 | Exponential regression | NDVI | 74.11 | Ma et al., |
2005 | 122.80 | Exponential regression | NDVI | 43.33 | Xu et al., |
- | 124.00 | Exponential regression | NDVI | 78.02 | Piao et al., |
1982-2013 | 154.48 | Exponential regression | NDVI | 104.40 | Jiao et al., |
2000-2014 | 151.11 | Random forest | Climate, terrain and NDVI | 77.12 | Zeng et al., |
- | 132.00 | Random forest | Climate and NDVI | 78.40 | Xia et al., |
2000-2017 | - | Random forest | Climate, terrain and NDVI | 59.63 | Gao et al., |
Fig. 1 Spatial distribution of eco-geographical regions and the sample sites on the Tibetan Plateau Note: (a) The eco-geographical regions of TP (Zheng, 1996) are the same as those listed in Table 2. (b) Sample sites in this study are from field observations and a previous study (Fu et al., 2017), which basically included all alpine grassland ecosystems on the TP.
Classification | Abbreviation | Meaning |
---|---|---|
Eco-geographical regions | TP | Tibetan Plateau |
IB1 | Golog-Nagqu high-cold shrub-meadow zone | |
IIAB1 | Western Sichuan-eastern Tibet montane coniferous forest zone | |
IC1 | Southern Qinghai high-cold meadow steppe zone | |
IC2 | Qiangtang high-cold steppe zone | |
ID1 | Kunlun high-cold desert zone | |
IIC1 | Southern Tibet montane shrub-steppe zone | |
IIC2 | Eastern Qinghai-Qilian montane steppe zone | |
IID1 | Nagri montane desert-steppe and desert zone | |
IID2 | Qaidam montane desert zone | |
IID3 | Northern slopes of Kunlun montane desert zone | |
OA1 | Southern slopes of Himalaya montane evergreen broad-leaved forest zone | |
Grass and livestock | AGBp | (Potential, only climate-derived) Aboveground biomass of the grassland |
LCCT | Theoretical livestock carrying capacity | |
SSU | The standardized sheep unit (daily feed of 1.33 kg hay in this study) | |
Climate and soil | GSDR | Growing season (May to September in each year) diurnal temperature range |
GSP | Growing season precipitation | |
GST | Growing season temperature | |
NGSDR | Non-growing season diurnal temperature range | |
NGSP | Non-growing season precipitation | |
NGST | Non-growing season temperature | |
SOM | Soil organic matter |
Table 2 List of abbreviations used in this study
Classification | Abbreviation | Meaning |
---|---|---|
Eco-geographical regions | TP | Tibetan Plateau |
IB1 | Golog-Nagqu high-cold shrub-meadow zone | |
IIAB1 | Western Sichuan-eastern Tibet montane coniferous forest zone | |
IC1 | Southern Qinghai high-cold meadow steppe zone | |
IC2 | Qiangtang high-cold steppe zone | |
ID1 | Kunlun high-cold desert zone | |
IIC1 | Southern Tibet montane shrub-steppe zone | |
IIC2 | Eastern Qinghai-Qilian montane steppe zone | |
IID1 | Nagri montane desert-steppe and desert zone | |
IID2 | Qaidam montane desert zone | |
IID3 | Northern slopes of Kunlun montane desert zone | |
OA1 | Southern slopes of Himalaya montane evergreen broad-leaved forest zone | |
Grass and livestock | AGBp | (Potential, only climate-derived) Aboveground biomass of the grassland |
LCCT | Theoretical livestock carrying capacity | |
SSU | The standardized sheep unit (daily feed of 1.33 kg hay in this study) | |
Climate and soil | GSDR | Growing season (May to September in each year) diurnal temperature range |
GSP | Growing season precipitation | |
GST | Growing season temperature | |
NGSDR | Non-growing season diurnal temperature range | |
NGSP | Non-growing season precipitation | |
NGST | Non-growing season temperature | |
SOM | Soil organic matter |
Fig. 2 Correlation coefficients of grassland AGBp with 14 environmental factors (a) and the relationships between observed grassland AGBp and estimated AGBp on the TP based on the RF model (b)
Eco-geographical regions* | AGBp mean (g m-2) | AGBp trend (g m-2 yr-1) | ||
---|---|---|---|---|
Mean | Standard deviation (SD) | Mean | Standard deviation (SD) | |
IB1 | 181.64 | 52.87 | 0.47 | 0.80 |
ICI | 93.68 | 32.03 | 0.31 | 0.60 |
IC2 | 53.81 | 24.90 | -0.11 | 0.30 |
ID1 | 55.90 | 7.70 | 0.02 | 0.08 |
IIAB1 | 196.47 | 46.29 | -0.23 | 0.69 |
IIC2 | 167.11 | 44.29 | 1.04 | 0.59 |
IIC1 | 80.47 | 25.17 | -0.16 | 0.29 |
IID2 | 109.63 | 24.70 | 0.09 | 0.22 |
OA1 | 228.15 | 35.00 | -0.53 | 0.48 |
IID1 | 56.42 | 24.77 | 0.36 | 0.60 |
IID3 | 92.39 | 23.35 | -0.02 | 0.11 |
TP | 102.40 | 63.47 | 0.14 | 0.61 |
Table 3 The mean values and trends of grassland AGBp for each eco-region on the TP
Eco-geographical regions* | AGBp mean (g m-2) | AGBp trend (g m-2 yr-1) | ||
---|---|---|---|---|
Mean | Standard deviation (SD) | Mean | Standard deviation (SD) | |
IB1 | 181.64 | 52.87 | 0.47 | 0.80 |
ICI | 93.68 | 32.03 | 0.31 | 0.60 |
IC2 | 53.81 | 24.90 | -0.11 | 0.30 |
ID1 | 55.90 | 7.70 | 0.02 | 0.08 |
IIAB1 | 196.47 | 46.29 | -0.23 | 0.69 |
IIC2 | 167.11 | 44.29 | 1.04 | 0.59 |
IIC1 | 80.47 | 25.17 | -0.16 | 0.29 |
IID2 | 109.63 | 24.70 | 0.09 | 0.22 |
OA1 | 228.15 | 35.00 | -0.53 | 0.48 |
IID1 | 56.42 | 24.77 | 0.36 | 0.60 |
IID3 | 92.39 | 23.35 | -0.02 | 0.11 |
TP | 102.40 | 63.47 | 0.14 | 0.61 |
Fig. 3 The spatial and temporal patterns of AGBp on the TP from 2000 to 2018 Note: The eco-geographical regions of the TP are the same as indicated in Table 2.
Fig. 4 The dynamics of growing season and non-growing season diurnal temperature, temperature, and precipitation on the Tibetan Plateau from 2000 to 2018. Note: The six climate variables from (a) to (f) are the same as indicated in Table 2.
Fig. 5 Correlations between AGBp and climatic variables from 2000 to 2018 on the TP Note: The six climate variables are the same as indicated in Table 2.
Fig. 6 The temporal-spatial patterns of the theoretical livestock carrying capacity from 2000 to 2018 on the TP Note: The eco-geographical regions of the TP are the same as indicated in Table 2.
Fig. 7 The grassland potential aboveground biomass (AGBp) changes in different future climate change scenarios for each eco-region on the TP compared to the past two decades Note: The eco-geographical regions of the TP are the same as indicated in Table 2. The different climate change scenarios of SSP1-2.6 SSP2-4.5, SSP3-7.0, and SSP5-8.5 (a-d) are the scenarios of low radiative forcing (2.6 W m-2), moderate radiative forcing (4.5 W m-2), medium to high radiative forcing (7.0 W m-2), and high radiative forcing (8.5 W m-2) in 2100 under the different social development conditions.
Eco-geographical regions* | SSP1-2.6 | SSP2-4.5 | SSP3-7.0 | SSP5-8.5 |
---|---|---|---|---|
IB1 | -2.70±9.54 | -2.24±9.31 | -2.16±9.60 | -2.40±10.10 |
IC1 | -16.33±10.27 | -14.05±10.32 | -14.37±10.69 | -16.29±11.05 |
IC2 | -0.67±18.05 | 0.81±18.09 | 0.63±18.76 | -11.51±17.43 |
ID1 | -7.79±8.29 | -7.74±8.37 | -8.59±8.73 | -17.47±7.44 |
IIAB1 | 2.75±5.73 | 2.48±5.64 | 2.84±6.07 | 2.28±6.07 |
IIC2 | -7.11±8.8 | -8.14±8.54 | -8.43±8.28 | -6.01±9.10 |
IIC1 | -0.98±9.29 | -0.72±9.31 | -0.22±9.45 | -1.24±8.96 |
IID2 | -4.66±7.11 | -4.71±6.85 | -4.76±6.81 | -4.33±7.11 |
OA1 | 1.94±2.69 | 1.30±1.93 | 1.61±2.28 | 0.93±2.01 |
IID1 | 4.73±17.9 | 4.21±18.01 | 1.39±17.27 | -1.07±21.35 |
IID3 | -5.03±8.21 | -4.18±7.24 | -4.11±7.46 | -5.27±8.00 |
Tibetan Plateau | -3.75±13.82 | -3.05±13.7 | -3.25±14.05 | -7.96±14.14 |
Table 4 Grassland potential aboveground biomass (AGBp) changes in different future climate change scenarios for each eco-region on the TP compared to the past two decades (Unit: g m-2)
Eco-geographical regions* | SSP1-2.6 | SSP2-4.5 | SSP3-7.0 | SSP5-8.5 |
---|---|---|---|---|
IB1 | -2.70±9.54 | -2.24±9.31 | -2.16±9.60 | -2.40±10.10 |
IC1 | -16.33±10.27 | -14.05±10.32 | -14.37±10.69 | -16.29±11.05 |
IC2 | -0.67±18.05 | 0.81±18.09 | 0.63±18.76 | -11.51±17.43 |
ID1 | -7.79±8.29 | -7.74±8.37 | -8.59±8.73 | -17.47±7.44 |
IIAB1 | 2.75±5.73 | 2.48±5.64 | 2.84±6.07 | 2.28±6.07 |
IIC2 | -7.11±8.8 | -8.14±8.54 | -8.43±8.28 | -6.01±9.10 |
IIC1 | -0.98±9.29 | -0.72±9.31 | -0.22±9.45 | -1.24±8.96 |
IID2 | -4.66±7.11 | -4.71±6.85 | -4.76±6.81 | -4.33±7.11 |
OA1 | 1.94±2.69 | 1.30±1.93 | 1.61±2.28 | 0.93±2.01 |
IID1 | 4.73±17.9 | 4.21±18.01 | 1.39±17.27 | -1.07±21.35 |
IID3 | -5.03±8.21 | -4.18±7.24 | -4.11±7.46 | -5.27±8.00 |
Tibetan Plateau | -3.75±13.82 | -3.05±13.7 | -3.25±14.05 | -7.96±14.14 |
Fig. 8 The theoretical livestock carrying capacity of alpine grasslands on the TP in the past two decades (2000-2018) and in the future two decades (2021-2040) under four climate change scenarios Note: The different climate change scenarios are the same as indicated in Fig. 7.
[1] |
Bai Y F, Han X G, Wu J G, et al. 2004. Ecosystem stability and compensatory effects in the Inner Mongolia grassland. Nature, 431: 181-184.
DOI URL |
[2] |
Breiman L. 2001. Random forests. Machine Learning, 45(1): 5-32.
DOI URL |
[3] |
Cao Y N, Wu J S, Zhang X Z, et al. 2019. Dynamic forage-livestock balance analysis in alpine grasslands on the Northern Tibetan Plateau. Journal of Environmental Management, 238: 352-359.
DOI URL |
[4] |
Cao Y N, Wu J S, Zhang X Z, et al. 2020. Comparison of methods for evaluating the forage-livestock balance of alpine grasslands on the Northern Tibetan Plateau. Journal of Resources and Ecology, 11(3): 272-282.
DOI URL |
[5] |
Chen B X, Zhang X Z, Tao J, et al. 2014. The impact of climate change and anthropogenic activities on alpine grassland over the Qinghai-Tibet Plateau. Agricultural and Forest Meteorology, 189-190: 11-18.
DOI URL |
[6] |
Chen H, Zhu Q A, Peng C H, et al. 2013. The impacts of climate change and human activities on biogeochemical cycles on the Qinghai-Tibetan Plateau. Global Change Biology, 19(10): 2940-2955.
DOI URL |
[7] | Chen T X, Chen X. 2007. Variation of diurnal temperature range in China in the past 50 years. Plateau Meteorology, 26(1): 150-157. (in Chinese) |
[8] |
Dai A G, Trenberth K E, Karl T R. 1999. Effects of clouds, soil moisture, precipitation, and water vapor on diurnal temperature range. Journal of Climate, 12(8): 2451-2473.
DOI URL |
[9] | Dong S K, Li J P, Li X Y, et al. 2010. Application of design theory for restoring the “black beach” degraded rangeland at the headwater areas of the Qinghai-Tibetan Plateau. African Journal of Agricultural Research, 5(25): 3542-3552. |
[10] |
Fan J W, Shao Q Q, Liu J Y, et al. 2010. Assessment of effects of climate change and grazing activity on grassland yield in the Three Rivers Headwaters Region of Qinghai-Tibet Plateau, China. Environmental Monitoring and Assessment, 170(1-4): 571-584.
DOI URL |
[11] |
Frankenberg C, Yin Y, Byrne B, et al. 2021. Comment on “Recent global decline of CO2 fertilization effects on vegetation photosynthesis”. Science, 373(6562): eabg2947. DOI: 10.1126/science.abg2947.
DOI URL |
[12] |
Fu G, Shen Z X, Zhang X Z. 2018. Increased precipitation has stronger effects on plant production of an alpine meadow than does experimental warming in the Northern Tibetan Plateau. Agricultural and Forest Meteorology, 249: 11-21.
DOI URL |
[13] |
Fu G, Sun W, Li S W, et al. 2017. Modeling aboveground biomass using MODIS images and climatic data in grasslands on the Tibetan Plateau. Journal of Resources and Ecology, 8(1): 42-49.
DOI URL |
[14] |
Gao X X, Dong S K, Li S, et al. 2020. Using the random forest model and validated MODIS with the field spectrometer measurement promote the accuracy of estimating aboveground biomass and coverage of alpine grasslands on the Qinghai-Tibetan Plateau. Ecological Indicators, 112: 106114. DOI: 10.1016/j.ecolind.2020.106114.
DOI URL |
[15] |
Harris R B. 2010. Rangeland degradation on the Qinghai-Tibetan Plateau: A review of the evidence of its magnitude and causes. Journal of Arid Environments, 74(1): 1-12.
DOI URL |
[16] | He Y T, Zhang X Z, Yu C. 2016. Coupling crop farming and pastoral system for regional development and their ecological effects on the Tibetan Plateau. Bulletin of Chinese Academy of Sciences, 31(1): 112-117. (in Chinese) |
[17] | Hou X Y. 2001. Vegetation atlas of China. Beijing, China: Science Press. (in Chinese) |
[18] |
Jiao C C, Yu G R, Ge J P, et al. 2017. Analysis of spatial and temporal patterns of aboveground net primary productivity in the Eurasian steppe region from 1982 to 2013. Ecology and Evolution, 7(14): 5149-5162.
DOI URL |
[19] |
Karhu K, Fritze H, Tuomi M, et al. 2010. Temperature sensitivity of organic matter decomposition in two boreal forest soil profiles. Soil Biology and Biochemistry, 42(1): 72-82.
DOI URL |
[20] |
Knapp A K, Smith M D. 2001. Variation among biomes in temporal dynamics of aboveground primary production. Science, 291(5503): 481-484.
PMID |
[21] | Li M, He Y T, Fu G, et al. 2016. Livestock-forage balance in the Three River Headwater Region based on the terrestrial ecosystem model. Ecology and Environmental Sciences, 25(12): 1915-1921. (in Chinese) |
[22] |
Li M, Wu J S, Song C Q, et al. 2019. Temporal variability of precipitation and biomass of alpine grasslands on the Northern Tibetan Plateau. Remote Sensing, 11(3): 360. DOI: 10.3390/rs11030360.
DOI URL |
[23] | Li X H. 2013. Using “random forest” for classification and regression. Chinese Journal of Applied Entomology, 50(4): 1190-1197. (in Chinese) |
[24] |
Liu Y W, Piao S L, Gasser T, et al. 2019. Field-experiment constraints on the enhancement of the terrestrial carbon sink by CO2 fertilization. Nature Geoscience, 12(10): 809-814.
DOI URL |
[25] |
Liu Y X, Zhao W W, Hua T, et al. 2019. Slower vegetation greening faced faster social development on the landscape of the Belt and Road Region. Science of the Total Environment, 697: 134103. DOI: 10.1016/j.scitotenv.2019.134103.
DOI URL |
[26] |
Long R J, Apori S O, Castro F B, et al. 1999. Feed value of native forages of the Tibetan Plateau of China. Animal Feed Science and Technology, 80(2): 101-113.
DOI URL |
[27] | Long R J, Shang Z H, Guo X S, et al. 2009. Case study 7: Qinghai-Tibetan Plateau rangelands. Rangeland Degradation & Recovery in China’s Pastoral Lands, 25(4): 29-36. |
[28] |
Lopatin J, Dolos K, Hernández H J, et al. 2016. Comparing generalized linear models and random forest to model vascular plant species richness using LiDAR data in a natural forest in central Chile. Remote Sensing of Environment, 173(315): 200-210.
DOI URL |
[29] | Luo T X, Li W H, Leng Y F, et al. 1998. Estimation of total biomass and potential distribution of net primary productivity in the Tibetan Plateau. Geographical Research, 17(4): 2-9. (in Chinese) |
[30] |
Luo T X, Li W H, Zhu H Z. 2002. Estimated biomass and productivity of natural vegetation on the Tibetan Plateau. Ecological Applications, 12(4): 980-997.
DOI URL |
[31] | Ma W H, Fang J Y, Yang Y H, et al. 2010. Biomass carbon stocks and their changes in Northern China’s grasslands during 1982-2006. Science China (Life Sciences), 53(7): 841-850. |
[32] |
Ni J. 2004. Forage yield-based carbon storage in grasslands of China. Climatic Change, 67(2-3): 237-246.
DOI URL |
[33] |
Niu B, He Y T, Zhang X Z, et al. 2016. Tower-based validation and improvement of MODIS gross primary production in an alpine swamp meadow on the Tibetan Plateau. Remote Sensing, 8(7): 592. DOI: 10.3390/rs8070592.
DOI URL |
[34] |
Niu B, He Y T, Zhang X Z, et al. 2020. Satellite-based estimates of canopy photosynthetic parameters for an alpine meadow in Northern Tibet. Journal of Resources and Ecology, 11(3): 253-262.
DOI URL |
[35] |
Niu B, Zeng C X, Zhang X Z, et al. 2019. High below-ground productivity allocation of alpine grasslands on the Northern Tibet. Plants, 8(12): 535. DOI: 10.3390/plants8120535
DOI URL |
[36] |
Niu B, Zhang X Z, He Y T, et al. 2017. Satellite-based estimation of gross primary production in an alpine swamp meadow on the Tibetan Plateau: A multi-model comparison. Journal of Resources and Ecology, 8(1): 57-66.
DOI URL |
[37] |
Niu B, Zhang X Z, Piao S L, et al. 2021. Warming homogenizes apparent temperature sensitivity of ecosystem respiration. Science Advances, 7(15): eabc7358. DOI: 10.1126/sciadv.abc7358.
DOI URL |
[38] |
Phillips C L, Gregg J W, Wilson J K. 2011. Reduced diurnal temperature range does not change warming impacts on ecosystem carbon balance of Mediterranean grassland mesocosms. Global Change Biology, 17(11): 3263-3273.
DOI URL |
[39] | Piao S L, Fang J Y, He J S, et al. 2004. Spatial distribution of grassland biomass in China. Acta Phytoecologica Sinica, 4: 491-498. (in Chinese) |
[40] | Piao S L, Zhang X Z, Wang T, et al. 2019. Responses and feedback of the Tibetan Plateau’s alpine ecosystem to climate change. Chinese Science Bulletin, 64(27): 2842-2855. (in Chinese) |
[41] |
Sang Y X, Huang L, Wang X H, et al. 2021. Comment on “Recent global decline of CO2 fertilization effects on vegetation photosynthesis”. Science, 373(6562): eabg4420. DOI: 10.1126/science.abg4420.
DOI URL |
[42] |
Scurlock J M O, Hall D O. 1998. The global carbon sink: A grassland perspective. Global Change Biology, 4(2): 229-233.
DOI URL |
[43] | Shang Z H, Gibb M J, Leiber F, et al. 2014. The sustainable development of grassland-livestock systems on the Tibetan Plateau: Problems, strategies and prospects. The Rangeland Journal, 36(3): 267-296. |
[44] |
Shen M G, Piao S L, Cong N, et al. 2015. Precipitation impacts on vegetation spring phenology on the Tibetan Plateau. Global Change Biology, 21(10): 3647-3656.
DOI URL |
[45] |
Shi P L, Zhang X Z. 2020. Towards regional synergy: Reconciling rangeland ecological functioning with forage production of cultivated pasture. Journal of Resources and Ecology, 11(3): 247-252.
DOI URL |
[46] | Si S, Bi X, Kong X, et al. 2020. Spatial-temporal characteristics of the emission intensities of several major greenhouse gases and aerosols under CMIP6 scenarios. Climatic and Environmental Research, 25(4): 366-384. (in Chinese) |
[47] |
Song J, Wan S Q, Piao S L, et al. Elevated CO2 does not stimulate carbon sink in a semi-arid grassland. Ecology Letters, 22(3): 458-468.
DOI URL |
[48] |
Tan K, Ciais P, Piao S L, et al. 2010. Application of the ORCHIDEE global vegetation model to evaluate biomass and soil carbon stocks of Qinghai-Tibetan grasslands. Global Biogeochemical Cycles, 24(1): GB1013. DOI: 10.1029/2009GB003530.
DOI |
[49] |
Tin K H. 1998. The random subspace method for constructing decision forests. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(8): 832-844.
DOI URL |
[50] |
Wang S H, Zhang Y G, Ju W M, et al. 2020. Recent global decline of CO2 fertilization effects on vegetation photosynthesis. Science, 370(6522): 1295-1300.
DOI URL |
[51] |
Wang S H, Zhang Y G, Ju W M, et al. 2021. Response to comments on “Recent global decline of CO2 fertilization effects on vegetation photosynthesis”. Science, 373(6562): eabg7484. DOI: 10.1126/science.abg7484.
DOI URL |
[52] |
Wang S Y, Zhang B, Yang Q C, et al. 2017. Responses of net primary productivity to phenological dynamics in the Tibetan Plateau, China. Agricultural and Forest Meteorology, 232: 235-246.
DOI URL |
[53] |
Winkler A J, Myneni R B, Hannart A, et al. 2021. Slowdown of the greening trend in natural vegetation with further rise in atmospheric CO2. Biogeosciences, 18(17): 4985-5010.
DOI URL |
[54] |
Wu J S, Feng Y F, Zhang X Z, et al. 2017. Grazing exclusion by fencing non-linearly restored the degraded alpine grasslands on the Tibetan Plateau. Scientific Reports, 7(1): 15202. DOI: 10.1038/s41598-017-15530-2.
DOI |
[55] |
Wu J S, Fu G. 2018. Modelling aboveground biomass using MODIS FPAR/LAI data in alpine grasslands of the Northern Tibetan Plateau. Remote Sensing Letters, 9(2): 150-159.
DOI URL |
[56] |
Wu J S, Wurst S, Zhang X Z. 2016. Plant functional trait diversity regulates the nonlinear response of productivity to regional climate change in a)Tibetan alpine grasslands. Scientific Reports, 6: 35649. DOI: 10.1038/s41598-017-15530-2.
DOI |
[57] |
Xia J Z, Ma M N, Liang T G, et al. 2018. Estimates of grassland biomass and turnover time on the Tibetan Plateau. Environmental Research Letters, 13(1): 014020. DOI: 10.1038/s41598-017-15530-2.
DOI URL |
[58] |
Xu L L, Niu B, Zhang X Z, et al. 2021. Dynamic threshold of carbon phenology in two cold temperate grasslands in China. Remote Sensing, 13(4): 574. DOI: 10.3390/rs13040574.
DOI URL |
[59] |
Xu W H, Xiao Y, Zhang J J, et al. 2017. Strengthening protected areas for biodiversity and ecosystem services in China. Proceedings of the National Academy of Sciences of the USA, 114(7): 1601-1606.
DOI URL |
[60] |
Yang G, Peng C H, Chen H, et al. 2017. Qinghai-Tibetan Plateau peatland sustainable utilization under anthropogenic disturbances and climate change. Ecosystem Health and Sustainability, 3(3): e01263. DOI: 10.1002/ehs2.1263.
DOI URL |
[61] |
Yang Y H, Fang J Y, Ma W H, et al. 2010. Large-scale pattern of biomass partitioning across China’s grasslands. Global Ecology and Biogeography, 19(2): 268-277.
DOI URL |
[62] |
Yang Y H, Fang J Y, Pan Y D, et al. 2009. Aboveground biomass in Tibetan grasslands. Journal of Arid Environments, 73(1): 91-95.
DOI URL |
[63] |
Yao T D, Thompson L G, Mosbrugger V, et al. 2012. Third pole environment (TPE). Environmental Development, 3: 52-64.
DOI URL |
[64] |
Yao Y T, Wang X H, Li Y, et al. 2018. Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years. Global Change Biology, 24(1): 184-196.
DOI URL |
[65] |
Zeng N, Ren X L, He H L, et al. 2019. Estimating grassland aboveground biomass on the Tibetan Plateau using a random forest algorithm. Ecological Indicators, 102: 479-487.
DOI |
[66] | Zhang X Z, He Y T, Shen Z X, et al. 2015a. Frontier of the ecological construction support the sustainable development in Tibet Autonomous Region. Bulletin of the Chinese Academy of Sciences, 30(3): 306-312. (in Chinese) |
[67] | Zhang X Z, Wang X, Gao Q, et al. 2016. Research in ecological restoration and reconstruction technology for degraded alpine ecosystem, boosting the protection and construction of ecological security barrier in Tibet. Acta Ecologica Sinica, 36(22): 7083-7087. (in Chinese) |
[68] | Zhang X Z, Yang Y, Piao S, et al. 2015b. Ecological change on the Tibetan Plateau. Chinese Science Bulletin, 60(32): 3048-3056. (in Chinese) |
[69] |
Zhang Y, Gao Q Z, Dong S K, et al. 2015c. Effects of grazing and climate warming on plant diversity, productivity and living state in the alpine rangelands and cultivated grasslands of the Qinghai-Tibetan Plateau. The Rangeland Journal, 37(1): 57-65.
DOI URL |
[70] | Zhang Y, Li B, Zheng D. 2002. A discussion on the boundary and area of the Tibetan Plateau in China. Geographical Research, 21(1): 1-8. (in Chinese) |
[71] |
Zhang Y Q, Tang Y H, Jiang J, et al. 2007. Characterizing the dynamics of soil organic carbon in grasslands on the Qinghai-Tibetan Plateau. Science in China (Series D), 50(1): 113-120.
DOI URL |
[72] | Zheng D. 1996. Natural region system research of Tibetan Plateau. Science in China (Series D), 26(4): 336-341. (in Chinese) |
[73] |
Zhu Z C, Zeng H, Myneni R B, et al. 2021. Comment on “Recent global decline of CO2 fertilization effects on vegetation photosynthesis”. Science, 373(6562): eabg5673. DOI: 10.1126/science.abg5673.
DOI URL |
[1] | SHI Peili, ZHENG Lili, ZHOU Tiancai, HOU Ge, ZHAO Guangshuai. Considerations of Forest Distribution and Native Tree Species for Afforestation in the High Altitudes on the Eastern Tibetan Plateau [J]. Journal of Resources and Ecology, 2022, 13(1): 100-106. |
[2] | HE Yuchuan, XIONG Junnan, CHENG Weiming, YE Chongchong, HE Wen, YONG Zhiwei, TIAN Jie. Spatiotemporal Pattern and Driving Force Analysis of Vegetation Variation in Altay Prefecture based on Google Earth Engine [J]. Journal of Resources and Ecology, 2021, 12(6): 729-742. |
[3] | TIAN Jie, XIONG Junnan, ZHANG Yichi, CHENG Weiming, HE Yuchuan, YE Chongchong, HE Wen. Quantitative Assessment of the Effects of Climate Change and Human Activities on Grassland NPP in Altay Prefecture [J]. Journal of Resources and Ecology, 2021, 12(6): 743-756. |
[4] | ZHAO Xuanlan, WANG Junbang, YE Hui, MUHAMMAD Amir, WANG Shaoqiang. The Bowen Ratio of an Alpine Grassland in Three-River Headwaters, Qinghai-Tibet Plateau, from 2001 to 2018 [J]. Journal of Resources and Ecology, 2021, 12(3): 305-318. |
[5] | Sydney M. GREENFIELD, Aliana C. NORRIS, Joseph P. LAMBERT, Wu liji, Se yongjun, ZHAN Jinqi, MA Bing, LI Deng, SHI Kun, Philip RIORDAN. Ungulate Mortality due to Fencing and Perceptions of Pasture Fences in Part of the Future Qilianshan National Park [J]. Journal of Resources and Ecology, 2021, 12(1): 99-109. |
[6] | SHI Peili, WU Ning, Gopal S. RAWAT. The Distribution Patterns of Timberline and Its Response to Climate Change in the Himalayas [J]. Journal of Resources and Ecology, 2020, 11(4): 342-348. |
[7] | NIU Ben, HE Yongtao, ZHANG Xianzhou, SHI Peili, DU Mingyuan. Satellite-based Estimates of Canopy Photosynthetic Parameters for an Alpine Meadow in Northern [J]. Journal of Resources and Ecology, 2020, 11(3): 253-262. |
[8] | SONG Minghua, LI Meng, HUO Jiajuan, WU Liang, ZHANG Xianzhou. Multifunctionality and Thresholds of Alpine Grassland on the Tibetan Plateau [J]. Journal of Resources and Ecology, 2020, 11(3): 263-271. |
[9] | CAO Yanan, ZHANG Xianzhou, NIU Ben, HE Yongtao. Comparison of Methods for Evaluating the Forage-livestock Balance of Alpine Grasslands on the Northern Tibetan Plateau [J]. Journal of Resources and Ecology, 2020, 11(3): 272-282. |
[10] | FENG Yunfei, DI Yingwei, ZHANG Jing, ZHANG Xianzhou, SHI Peili, Niu Ben. Impact of Grazing Exclusion on the Surface Heat Balance in North Tibet [J]. Journal of Resources and Ecology, 2020, 11(3): 283-289. |
[11] | WANG Xiangtao, ZHANG Xianzhou, WANG Junhao, NIU Ben. Variations in the Drought Severity Index in Response to Climate Change on the Tibetan Plateau [J]. Journal of Resources and Ecology, 2020, 11(3): 304-314. |
[12] | XIANG Ling, GAO Xiang, PENG Yuhui, LIANG Jie. Coupling the Occurrence of Correlative Plant Species to Predict the Habitat Suitability for Lesser White-fronted Goose (Anser erythropus) under Climate Change: A Case Study in the Middle and Lower Reaches of the Yangtze River [J]. Journal of Resources and Ecology, 2020, 11(2): 140-149. |
[13] | QIN Qin, SUN Youhai. A Study of China’s Air Pollution Prevention and Control Policy Framework from a Policy Instrument Perspective [J]. Journal of Resources and Ecology, 2020, 11(2): 182-190. |
[14] | Raju RAI, Basanta PAUDEL, GU Changjun, Narendra Raj KHANAL. Change in the Distribution of National Bird (Himalayan Monal) Habitat in Gandaki River Basin, Central Himalayas [J]. Journal of Resources and Ecology, 2020, 11(2): 223-231. |
[15] | LIU Yuanzhe, SONG Wei, ZHAO Dongsheng, GAO Jiangbo. Progress in Research on the Influences of Climatic Changes on the Industrial Economy in China [J]. Journal of Resources and Ecology, 2020, 11(1): 1-12. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||