Research article |
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Grassland-type ecosystem stability in China differs under the influence of drought and wet events |
CAO Wenyu1, BAI Jianjun1,*(), YU Leshan2 |
1School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China 2International Business School, Shaanxi Normal University, Xi'an 710119, China |
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Abstract Ecological stability is a core issue in ecological research and holds significant implications for humanity. The increased frequency and intensity of drought and wet climate events resulting from climate change pose a major threat to global ecological stability. Variations in stability among different ecosystems have been confirmed, but it remains unclear whether there are differences in stability within the same terrestrial vegetation ecosystem under the influence of climate events in different directions and intensities. China's grassland ecosystem includes most grassland types and is a good choice for studying this issue. This study used the Standardized Precipitation Evapotranspiration Index-12 (SPEI-12) to identify the directions and intensities of different types of climate events, and based on Normalized Difference Vegetation Index (NDVI), calculated the resistance and resilience of different grassland types for 30 consecutive years from 1990 to 2019 (resistance and resilience are important indicators to measure stability). Based on a traditional regression model, standardized methods were integrated to analyze the impacts of the intensity and duration of drought and wet events on vegetation stability. The results showed that meadow steppe exhibited the highest stability, while alpine steppe and desert steppe had the lowest overall stability. The stability of typical steppe, alpine meadow, temperate meadow was at an intermediate level. Regarding the impact of the duration and intensity of climate events on vegetation ecosystem stability for the same grassland type, the resilience of desert steppe during drought was mainly affected by the duration. In contrast, the impact of intensity was not significant. However, alpine steppe was mainly affected by intensity in wet environments, and duration had no significant impact. Our conclusions can provide decision support for the future grassland ecosystem governance.
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Received: 16 November 2023
Published: 31 May 2024
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Corresponding Authors:
*BAI Jianjun (E-mail: bjj@snnu.edu.cn)
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|
|
[1] |
Beguería S, Vicente-Serrano S M, Reig F, et al. 2014. Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. International Journal of Climatology, 34(10): 3001-3023.
|
|
|
[2] |
Chen J J, Chi Y G, Zhou W, et al. 2021. Quantifying the dimensionalities and drivers of ecosystem stability at global scale. Journal of Geophysical Research-Biogeosciences, 126(4): e2020JG006041, doi: 10.1029/2020JG006041.
|
|
|
[3] |
Creedy T J, Asare R A, Morel A C, et al. 2022. Climate change alters impacts of extreme climate events on a tropical perennial tree crop. Scientific Reports, 12(1): 19653, doi: 10.1038/s41598-022-22967-7.
pmid: 36385148
|
|
|
[4] |
de Keersmaecker W, Lhermitte S, Tits L, et al. 2015. A model quantifying global vegetation resistance and resilience to short-term climate anomalies and their relationship with vegetation cover. Global Ecology and Biogeography, 24(5): 539-548.
|
|
|
[5] |
Easterling D R, Meehl G A, Parmesan C, et al. 2000. Climate extremes: Observations, modeling, and impacts. Science, 289(5487): 2068-2074.
doi: 10.1126/science.289.5487.2068
pmid: 11000103
|
|
|
[6] |
Editorial Board of Vegetation Map of China. 2007. Vegetation Atlas of China (1: 1000000). Beijing: Geological Publishing House.
|
|
|
[7] |
Fan X, Hao X M, Hao H C, et al. 2021. Comprehensive assessment indicator of ecosystem resilience in Central Asia. Water, 13(2): 124, doi: 10.3390/w13020124.
|
|
|
[8] |
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.
|
|
|
[9] |
García-Palacios P, Gross N, Gaitan J, et al. 2018. Climate mediates the biodiversity-ecosystem stability relationship globally. Proceedings of the National Academy of Sciences of the United States of America, 115(33): 8400-8405.
|
|
|
[10] |
Grilli J, Barabas G, Michalska-Smith M J, et al. 2017. Higher-order interactions stabilize dynamics in competitive network models. Nature, 548(7666): 210-213.
|
|
|
[11] |
Gross N, Bagousse-Pinguet Y L, Liancourt P, et al. 2017. Functional trait diversity maximizes ecosystem multifunctionality. Nature Ecology & Evolution, 1(5): 0132, doi: 10.1038/s41559-017-0132.
|
|
|
[12] |
Han F S, Yu C Q, Fu G. 2023. Non-growing/growing season non-uniform-warming increases precipitation use efficiency but reduces its temporal stability in an alpine meadow. Frontiers in Plant Science, 14: 1090204, doi: 10.3389/fpls.2023.1090204.
|
|
|
[13] |
Hansen B B, Gamelon M, Albon S D, et al. 2019. More frequent extreme climate events stabilize reindeer population dynamics. Nature Communications, 10: 1616, doi: 10.1038/s41467-019-09332-5.
pmid: 30962419
|
|
|
[14] |
Hossain M L, Li J F, Hoffmann S, et al. 2022. Biodiversity showed positive effects on resistance but mixed effects on resilience to climatic extremes in a long-term grassland experiment. Science of the Total Environment, 827: 154322, doi: 10.1016/j.scitotenv.2022.154322.
|
|
|
[15] |
Hu Y Z, Ding R S, Kang S Z, et al. 2022. The trade-offs between resistance and resilience of forage stay robust with varied growth potentials under different soil water and salt stress. Science of the Total Environment, 846: 157421, doi: 10.1016/j.scitotenv.2022.157421.
|
|
|
[16] |
Huang K, Xia J Y. 2019. High ecosystem stability of evergreen broadleaf forests under severe droughts. Global Change Biology, 25(10): 3494-3503.
doi: 10.1111/gcb.14748
pmid: 31276270
|
|
|
[17] |
Huang W J, Wang W, Cao M, et al. 2021. Local climate and biodiversity affect the stability of China's grasslands in response to drought. Science of the Total Environment, 768: 145482, doi: 10.1016/j.scitotenv.2021.145482.
|
|
|
[18] |
Isbell F, Craven D, Connolly J, et al. 2015. Biodiversity increases the resistance of ecosystem productivity to climate extremes. Nature, 526(7574): 574-577.
|
|
|
[19] |
Ives A R, Carpenter S R. 2007. Stability and diversity of ecosystems. Science, 317(5834): 58-62.
doi: 10.1126/science.1133258
pmid: 17615333
|
|
|
[20] |
Jiao W Z, Wang L X, Wang H L, et al. 2022. Comprehensive quantification of the responses of ecosystem production and respiration to drought time scale, intensity and timing in humid environments: A FLUXNET synthesis. Journal of Geophysical Research-Biogeosciences, 127(5): e2021JG006431, doi: 10.1029/2021JG006431.
|
|
|
[21] |
King A D, Donat M G, Fischer E M, et al. 2015. The timing of anthropogenic emergence in simulated climate extremes. Environmental Research Letters, 10(9): 094015, doi: 10.1088/1748-9326/10/9/094015.
|
|
|
[22] |
Lavery M R, Acharya P, Sivo S A, et al. 2019. Number of predictors and multicollinearity: What are their effects on error and bias in regression? Communications in Statistics-Simulation and Computation, 48(1): 27-38.
|
|
|
[23] |
Li M, Wu J S, He Y T, et al. 2020a. Dimensionality of grassland stability shifts along with altitudes on the Tibetan Plateau. Agricultural and Forest Meteorology, 291: 108080, doi: 10.1016/j.agrformet.2020.108080.
|
|
|
[24] |
Li X Y, Piao S L, Wang K, et al. 2020b. Temporal trade-off between gymnosperm resistance and resilience increases forest sensitivity to extreme drought. Nature Ecology & Evolution, 4(8): 1075-1083.
|
|
|
[25] |
Liu Y, Ren H, Hu T, et al. 2022. Spatiotemporal dynamics of NDVI of grassland and its response to multi-scale drought in China. Research of Soil and Water Conservation, 29(1): 153-161. (in Chinese)
|
|
|
[26] |
Liu Y J, You C H, Zhang Y G, et al. 2021. Resistance and resilience of grasslands to drought detected by SIF in Inner Mongolia, China. Agricultural and Forest Meteorology, 308-309: 108567, doi: 10.1016/j.agrformet.2021.108567.
|
|
|
[27] |
Schwalm C R, Anderegg W R L, Michalak A M, et al. 2017. Global patterns of drought recovery. Nature, 548(7666): 202-205.
|
|
|
[28] |
Scornet E. 2016. Random forests and kernel methods. IEEE Transactions on Information Theory, 62(3): 1485-1500.
|
|
|
[29] |
Si Y F, Li H, Li Z H, et al. 2023. Response of functional traits of key species in meadow steppe to long-term grazing and grazing exclusion. Agricultural Sciences in China, 56(18): 3693-3708. (in Chinese)
|
|
|
[30] |
Sirami C, Gross N, Baillod A B, et al. 2019. Increasing crop heterogeneity enhances multitrophic diversity across agricultural regions. Proceedings of the National Academy of Sciences of the United States of America, 116(33): 16442-16447.
|
|
|
[31] |
Stott P. 2016. How climate change affects extreme weather events: Research can increasingly determine the contribution of climate change to extreme events such as droughts. Science, 352(6293): 1517-1518.
|
|
|
[32] |
van Ruijven J, Berendse F. 2010. Diversity enhances community recovery, but not resistance, after drought. Journal of Ecology, 98(1): 81-86.
|
|
|
[33] |
Vicente-Serrano S M, Beguería S, Lopez-Moreno J I. 2010. A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. Journal of Climate, 23(7): 1696-1718.
|
|
|
[34] |
Wang Z Z, Fu B J, Wu X T, et al. 2023. Vegetation resilience does not increase consistently with greening in China's Loess Plateau. Communications Earth & Environment, 4(1): 336, doi: 10.1038/s43247-023-01000-3.
|
|
|
[35] |
Xiao J Y, Yu C Q, Fu G. 2023. Response of aboveground net primary production, species and phylogenetic diversity to warming and increased precipitation in an alpine meadow. Plants, 12(17): 3017, doi: 10.3390/plants12173017.
|
|
|
[36] |
Xu Z X, di Vittorio A. 2021. Hydrological analysis in watersheds with a variable-resolution global climate model (VR-CESM). Journal of Hydrology, 601: 126646, doi: 10.1016/j.jhydrol.2021.126646.
|
|
|
[37] |
Yang J W, Chen H, Hou Y K, et al. 2019. A method to identify the drought-flood transition based on the meteorological drought index. Acta Geographica Sinica, 74(11): 2358-2370. (in Chinese)
doi: 10.11821/dlxb201911012
|
|
|
[38] |
Yoo S H, Park C H. 2013. MCP, kernel density estimation and LoCoH analysis for the core area zoning of the red-crowned Crane's feeding habitat in Cheorwon, Korea. Korean Journal of Environment and Ecology, 27(1): 11-21. (in Korean)
|
|
|
[39] |
Yuan Q, Xu Z, Shi W, et al. 2004. Establishment of the sharing information system of grassland resources in China. Grassland of China, 26(4): 16-20. (in Chinese)
|
|
|
[40] |
Zhang D, Guo Y F, Qi W, et al. 2023. Study on the composition and diversity of plant communities in different degradation succession sequences of the Ordos desert grassland. Inner Mongolia Water Resources, 10: 3-5. (in Chinese)
|
|
|
[41] |
Zhang F Y, Quan Q, Ma F F, et al. 2019. Differential responses of ecosystem carbon flux components to experimental precipitation gradient in an alpine meadow. Functional Ecology, 33(5): 889-900.
|
|
|
[42] |
Zhou X, Wang Y, Li J. 2023. Response of plant community composition to precipitation changes in typical grasslands in the Loess Plateau. Biodiversity Science, 31(3): 42-51.
|
|
|
|
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