Abstract
It is necessary to understand vegetation dynamics and their climatic controls for sustainable ecosystem management. This study examines the vegetation dynamics and the effect of climate change on vegetation growth in the pristine conditions of 58 woodland National Nature Reserves (NNRs) located in the upper Yangtze River basin (UYRB) in China which are little influenced by human activities. Changes in the normalized difference vegetation index (NDVI), precipitation, and temperature in the selected NNRs were observed and analyzed for the period between 1999 and 2015. The relationship between time-lag effect of climate and changes in the NDVI were assessed using Pearson correlations. The results showed three major trends. 1) The NDVI increased during the study period; this indicates an increase in the amount of green vegetation, especially due to the warmer climate during the growing season. The NDVIs in March and September were significantly affected by the temperature of the previous months. Spring temperatures increased significantly (P < 0.05) and there was a delay between climatic factors and their effect on vegetation, which depended on the previous season. In particular, the spring temperature had a delayed effect on the NDVI in summer. 2) The way in which vegetation responds to climatic factors varied significantly across the seasons. Temperature had a greater effect on the NDVI in spring and summer and the effect was greater at higher altitudes. A similar trend was observed for precipitation, except for altitudes of 1000–2000 m. 3) Temperature had a greater effect on the NDVI in spring and autumn at higher altitudes. The same trend was observed for precipitation in summer. These findings suggest that the vegetation found in NNRs in the upper reaches of the Yangtze River was in good condition between 1999 and 2015 and that the growth and development of vegetation in the region has not been adversely affected by climate change. This demonstrates the effectiveness of nature reserves in protecting regional ecology and minimizing anthropogenic effects.
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References
Ababneh L, Woolfenden W (2010) Monitoring for potential effects of climate change on the vegetation of two alpine meadows in the White Mountains of California, USA. Quaternary International 215: 3–14. https://doi.org/10.1016/j.quaint.2009.05.013
Arrogante-Funes P, Novillo CJ, Romero-Calcerrada R (2018) Monitoring NDVI Inter-Annual Behavior in Mountain Areas of Mainland Spain (2001-2016). Sustainability 10. https://doi.org/10.3390/su10124363
Asam S, Callegari M, Matiu M, et al. (2018) Relationship between Spatiotemporal Variations of Climate, Snow Cover and Plant Phenology over the Alps-An Earth Observation-Based Analysis. Remote Sensing 10. https://doi.org/10.3390/rs10111757
Brenes CLM, Jones KW, Schlesinger P, et al. (2018) The impact of protected area governance and management capacity on ecosystem function in Central America. Plos One 13. https://doi.org/10.1371/journal.pone.0205964
Chen AF, He B, Wang HL, et al. (2015) Notable shifting in the responses of vegetation activity to climate change in China. Physics and Chemistry of the Earth 87-88: 60–66. https://doi.org/10.1016/j.pce.2015.08.008
Chen BX, Zhang XZ, 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: 11–18. https://doi.org/10.1016/j.agrformet.2014.01.002
Chen FY, Lin AW, Zhu HJ, et al. (2018) Quantifying Climate Change and Ecological Responses within the Yangtze River Basin, China. Sustainability 10. https://doi.org/10.3390/su10093026
Chu H, Venevsky S, Wu C, et al. (2019) NDVI-based vegetation dynamics and its response to climate changes at Amur-Heilongjiang River Basin from 1982 to 2015. Science of the Total Environment 650: 2051–2062. https://doi.org/10.1016/j.scitotenv.2018.09.115
Cui LF, Wang LC, Singh RP, et al. (2018) Association analysis between spatiotemporal variation of vegetation greenness and precipitation/temperature in the Yangtze River Basin (China). Environmental Science and Pollution Research 25: 21867–21878.https://doi.org/10.1007/s11356-018-2340-4
Feoli E, Perez-Gomez R, Oyonarte C, et al. (2017) Using spatial data mining to analyze area-diversity patterns among soil, vegetation, and climate: A case study from Almeria, Spain. Geoderma 287: 164–169. https://doi.org/10.1016/j.geoderma.2016.09.011
Geldmann J, Coad L, Barnes M, et al. (2015) Changes in protected area management effectiveness over time: A global analysis. Biological Conservation 191: 692–699. https://doi.org/10.1016/j.biocon.2015.08.029
Gillespie TW, Ostermann-Kelm S, Dong CY, et al. (2018) Monitoring changes of NDVI in protected areas of southern California. Ecological Indicators 88: 485–494. https://doi.org/10.1016/j.ecolind.2018.01.031
Guan Q, Yang L, Pan N, et al. (2018) Greening and Browning of the Hexi Corridor in Northwest China: Spatial Patterns and Responses to Climatic Variability and Anthropogenic Drivers. Remote Sensing 10. https://doi.org/10.3390/rs10081270
Guo J, Chen H, Xu CY, et al. (2012) Prediction of variability of precipitation in the Yangtze River Basin under the climate change conditions based on automated statistical downscaling. Stochastic Environmental Research and Risk Assessment 26: 157–176. https://doi.org/10.1007/s00477-011-0464-x
Guo LH, Wu SH, Zhao DS, et al. (2014) NDVI-Based Vegetation Change in Inner Mongolia from 1982 to 2006 and Its Relationship to Climate at the Biome Scale. Advances in Meteorology. https://doi.org/10.1155/2014/692068
He B, Chen AF, Wang HL, et al. (2015) Dynamic Response of Satellite-Derived Vegetation Growth to Climate Change in the Three North Shelter Forest Region in China. Remote Sensing 7: 9998–10016. https://doi.org/10.3390/rs70809998
Holben BN (1986) CHARACTERISTICS OF MAXIMUM-VALUE COMPOSITE IMAGES FROM TEMPORAL AVHRR DATA. International Journal of Remote Sensing 7: 1417–1434. https://doi.org/10.1080/01431168608948945
Hou WJ, Gao JB, Wu SH, et al. (2015) Interannual Variations in Growing-Season NDVI and Its Correlation with Climate Variables in the Southwestern Karst Region of China. Remote Sensing 7: 11105–11124. https://doi.org/10.3390/rs70911105
Howe PD, Markowitz EM, Lee TM, et al. (2013) Global perceptions of local temperature change. Nature Climate Change 3: 352–356. https://doi.org/10.1038/nclimate1768
Huang F, Xu SL (2016) Spatio-Temporal Variations of Rain-Use Efficiency in the West of Songliao Plain, China. Sustainability 8. https://doi.org/10.3390/su8040308
Huang Y, Fu J, Wang W, et al. (2019) Development of China’s nature reserves over the past 60 years: An overview. Land Use Policy 80: 224–232. https://doi.org/10.1016/j.landusepol.2018.10.020
Jiapaer G, Liang SL, Yi QX, et al. (2015) Vegetation dynamics and responses to recent climate change in Xinjiang using leaf area index as an indicator. Ecological Indicators 58: 64–76. https://doi.org/10.1016/j.ecolind.2015.05.036
Jin JX, Wang Y, Jiang H, et al. (2016) Recent NDVI-Based Variation in Growth of Boreal Intact Forest Landscapes and Its Correlation with Climatic Variables. Sustainability 8. https://doi.org/10.3390/su8040326
Kang C, Zhang YL, Wang ZF, et al. (2017) The Driving Force Analysis of NDVI Dynamics in the Trans-Boundary Tumen River Basin between 2000 and 2015. Sustainability 9. https://doi.org/10.3390/su9122350
Li A, Wu J, Huang J (2012) Distinguishing between humaninduced and climate-driven vegetation changes: a critical application of RESTREND in inner Mongolia. Landscape Ecology 27: 969–982. https://doi.org/10.1007/s10980-012-9751-2
Li CF, Zhang C, Luo GP, et al. (2015) Carbon stock and its responses to climate change in Central Asia. Global Change Biology 21: 1951–1967. https://doi.org/10.1111/gcb.12846
Li JJ, Peng SZ, Li Z (2017) Detecting and attributing vegetation changes on China’s Loess Plateau. Agricultural and Forest Meteorology 247: 260–270. https://doi.org/10.1016/j.agrformet.2017.08.005
Liang J, Xing WL, Zeng GM, et al. (2018) Where will threatened migratory birds go under climate change? Implications for China’s national nature reserves. Science of the Total Environment 645: 1040–1047. https://doi.org/10.1016/j.scitotenv.2018.07.196
Liu HJ, Bu RC, Liu JT, et al. (2011) Predicting the wetland distributions under climate warming in the Great Xing’an Mountains, northeastern China. Ecological Research 26: 605–613. https://doi.org/10.1007/s11284-011-0819-2
Liu XF, Zhang JS, Zhu XF, et al. (2014) Spatiotemporal changes in vegetation coverage and its driving factors in the Three-River Headwaters Region during 2000-2011. Journal of Geographical Sciences 24: 288–302. https://doi.org/10.1007/s11442-014-1088-0
Liu YL, Lei HM (2015) Responses of Natural Vegetation Dynamics to Climate Drivers in China from 1982 to 2011. Remote Sensing 7: 10243–10268. https://doi.org/10.3390/rs70810243
Liu Z, Liu Y, Li Y (2018) Anthropogenic contributions dominate trends of vegetation cover change over the farming-pastoral ecotone of northern China. Ecological Indicators 95: 370–378. https://doi.org/10.1016/j.ecolind.2018.07.063
Lu GY, Wong DW (2008) An adaptive inverse-distance weighting spatial interpolation technique. Computers & Geosciences 34: 1044–1055. https://doi.org/10.1016/j.cageo.2007.07.010
Mackenzie L, Bao K, Mao L, et al. (2018) Anthropogenic and climate-driven environmental change in the Songnen Plain of northeastern China over the past 200 years. Palaeogeography Palaeoclimatology Palaeoecology 511: 208–217. https://doi.org/10.1016/j.palaeo.2018.08.005
Meng M, Ni J, Zong MJ (2011) Impacts of changes in climate variability on regional vegetation in China: NDVI-based analysis from 1982 to 2000. Ecological Research 26: 421–428. https://doi.org/10.1007/s11284-011-0801-z
Moral FJ (2010) Comparison of different geostatistical approaches to map climate variables: application to precipitation. International Journal of Climatology 30: 620–631. https://doi.org/10.1002/joc.1913
Nepstad DC, Stickler CM, Soares B, et al. (2008) Interactions among Amazon land use, forests and climate: prospects for a near-term forest tipping point. Philosophical Transactions of the Royal Society B-Biological Sciences 363: 1737–1746. https://doi.org/10.1098/rstb.2007.0036
Nepstad DC, Verissimo A, Alencar A, et al. (1999) Large-scale impoverishment of Amazonian forests by logging and fire. Nature 398: 505–508. https://doi.org/10.1038/19066
Peng SS, Piao SL, Ciais P, et al. (2013) Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation. Nature 501: 88–92. https://doi.org/10.1038/nature12434
Piao S, Yin G, Tan J, et al. (2015a) Detection and attribution of vegetation greening trend in China over the last 30 years. Global Change Biology 21: 1601–1609. https://doi.org/10.1111/gcb.12795
Piao SL, Fang JY, Zhou LM, et al. (2006) Variations in satellitederived phenology in China’s temperate vegetation. Global Change Biology 12: 672–685. https://doi.org/10.1111/j.1365-2486.2006.01123.x
Piao SL, Yin GD, Tan JG, et al. (2015b) Detection and attribution of vegetation greening trend in China over the last 30 years. Global Change Biology 21: 1601–1609. https://doi.org/10.1111/gcb.12795
Qu B, Zhu W, Jia S, et al. (2015) Spatio-Temporal Changes in Vegetation Activity and Its Driving Factors during the Growing Season in China from 1982 to 2011. Remote Sensing 7: 13729–13752. https://doi.org/10.3390/rs71013729
Qu S, Wang L, Lin A, et al. (2018) What drives the vegetation restoration in Yangtze River basin, China: Climate change or anthropogenic factors? Ecological Indicators 90: 438–450. https://doi.org/10.1016/j.ecolind.2018.03.029
Richardson AD, Black TA, Ciais P, et al. (2010) Influence of spring and autumn phenological transitions on forest ecosystem productivity. Philosophical Transactions of the Royal Society B-Biological Sciences 365: 3227–3246. https://doi.org/10.1098/rstb.2010.0102
Santini M, Collalti A, Valentini R (2014) Climate change impacts on vegetation and water cycle in the Euro-Mediterranean region, studied by a likelihood approach. European Physical Journal D 14: 1405–1418. https://doi.org/10.1007/s10113-013-0582-8
Scheiter S, Higgins SI (2008) Impacts of Climate Change on the Vegetation of Africa: an Adaptive Dynamic Vegetation Modelling Approach. Global Change Biology 15: 2224–2246. https://doi.org/10.1111/j.1365-2486.2008.01838.x
Sommer JH, Kreft H, Kier G, et al. (2010) Projected impacts of climate change on regional capacities for global plant species richness. Proceedings of the Royal Society B-Biological Sciences 277: 2271–2280. https://doi.org/10.1098/rspb.2010.0120
Streher AS, Sobreiro JFF, Morellato LPC, et al. (2017) Land Surface Phenology in the Tropics: The Role of Climate and Topography in a Snow-Free Mountain. Ecosystems 20: 1436–1453. https://doi.org/10.1007/s10021-017-0123-2
Su BD, Huang JL, Zeng XF, et al. (2017) Impacts of climate change on streamflow in the upper Yangtze River basin. Climatic Change 141: 533–546. https://doi.org/10.1007/s10584-016-1852-5
Sun J, Qin XJ (2016) Precipitation and temperature regulate the seasonal changes of NDVI across the Tibetan Plateau. Environmental Earth Sciences 75. https://doi.org/10.1007/s12665-015-5177-x
Szabo S, Elemer L, Kovacs Z, et al. (2019) NDVI dynamics as reflected in climatic variables: spatial and temporal trends - a case study of Hungary. GIScience & Remote Sensing 56: 624–644. https://doi.org/10.1080/15481603.2018.1560686
Takem BM, Kaffo C, Fish L (2010) “Protected area” coverage in Cameroon on the eve of the Convention on Biological Diversity 2010 target. International Forestry Review 12: 231–239. https://doi.org/10.1505/ifor.12.3.231
Tan ZQ, Tao H, Jiang JH, et al. (2015b) Influences of Climate Extremes on NDVI (Normalized Difference Vegetation Index) in the Poyang Lake Basin, China. Wetlands 35: 1033–1042. https://doi.org/10.1007/s13157-015-0692-9
Tanja S, Berninger F, Vesala T, et al. (2003) Air temperature triggers the recovery of evergreen boreal forest photosynthesis in spring. Global Change Biology 9: 1410–1426. https://doi.org/10.1046/j.1365-2486.2003.00597.x
Tanner-McAllister SL, Rhodes J, Hockings M (2017) Managing for climate change on protected areas: An adaptive management decision making framework. Journal of Environmental Management 204: 510–518. https://doi.org/10.1016/j.jenvman.2017.09.038
Thorne JH, Choe H, Boynton RM, et al. (2017) The impact of climate change uncertainty on California’s vegetation and adaptation management. Ecosphere 8: e02021. https://doi.org/10.1002/ecs2.2021
Tsai HP, Yang MD (2016) Relating Vegetation Dynamics to Climate Variables in Taiwan Using 1982-2012 NDVI3g Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9: 1624–1639. https://doi.org/10.1109/jstars.2015.2511742
Wen L, Yang X, Saintilan N (2012) Local climate determines the NDVI-based primary productivity and flooding creates heterogeneity in semi-arid floodplain ecosystem. Ecological Modelling 242: 116–126. https://doi.org/10.1016/j.ecolmodel.2012.05.018
Wu C, Venevsky S, Sitch S, et al. (2017) Present-day and future contribution of climate and fires to vegetation composition in the boreal forest of China. Ecosphere 8. https://doi.org/10.1002/ecs2.1917
Xie B, Jia X, Qin Z, et al. (2016) Vegetation dynamics and climate change on the Loess Plateau, China: 1982-2011. Regional Environmental Change 16: 1583–1594. https://doi.org/10.1007/s10113-015-0881-3
Xu J, Melick DR (2007) Rethinking the effectiveness of public protected areas in southwestern China. Conservation Biology 21: 318–328. https://doi.org/10.1111/j.1523-1739.2006.00636.x
Zeng Z, Piao S, Li LZX, et al. (2017) Climate mitigation from vegetation biophysical feedbacks during the past three decades. Nature Climate Change 7: 432–436. https://doi.org/10.1038/nclimate3299
Zhang Q, Kong DD, Singh VP, et al. (2017) Response of vegetation to different time-scales drought across China: Spatiotemporal patterns, causes and implications. Global and Planetary Change 152: 1–11. https://doi.org/10.1016/j.gloplacha.2017.02.008
Zhou X, Yamaguchi Y, Arjasakusuma S (2018) Distinguishing the vegetation dynamics induced by anthropogenic factors using vegetation optical depth and AVHRR NDVI: A crossborder study on the Mongolian Plateau. Science of the Total Environment 616: 730–743. https://doi.org/10.1016/j.scitotenv.2017.10.253
Zhou Y, Zhang L, Fensholt R, et al. (2015) Climate Contributions to Vegetation Variations in Central Asian Drylands: Pre- and Post-USSR Collapse. Remote Sensing 7: 2449–2470. https://doi.org/10.3390/rs70302449
Acknowledgements
This research was jointly funded by the 135 Strategic Program of the Institute of Mountain Hazards and Environment, CAS (Grant No. SDS- 135-1703), and the Science and Technology Service Network Initiative of Chinese Academy of Sciences: Ecological Risk Assessment and Protection of the Yangtze River Economic Belt (KFJ-STS-ZDTP).
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Zhang, Yx., Wang, Yk., Fu, B. et al. Impact of climatic factors on vegetation dynamics in the upper Yangtze River basin in China. J. Mt. Sci. 17, 1235–1250 (2020). https://doi.org/10.1007/s11629-019-5649-7
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DOI: https://doi.org/10.1007/s11629-019-5649-7