Journal Home > Volume 10 , Issue 6
Forest Ecosystems 2023, 10(6): 100144 https://doi.org/10.1016/j.fecs.2023.100144
Research Article | Open Access | Issue | Published: 23 October 2023

Sensitivity of forest phenology in China varies with proximity to forest edges

Show Author's Information Weibin Youa,b,  Ziyi Xianc,d,  Guoyi Zhouc,d,  Evgenios Agathokleousc,d,  Zhen Yuc,d( )
College of JunCao Science and Ecology, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Fujian Southern Forest Resources and Environmental Engineering Technology Research Center, College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Research Center for Global Changes and Ecosystem Carbon Sequestration & Mitigation, Nanjing University of Information Science & Technology, Nanjing 210044, China
Keywords:
Climate change, Edge effects, Natural forests, Planted forests, Phenology sensitivity
Cite this article:
You W, Xian Z, Zhou G, et al. Sensitivity of forest phenology in China varies with proximity to forest edges. Forest Ecosystems, 2023, 10(6): 100144. https://doi.org/10.1016/j.fecs.2023.100144
Download citation
EndNote(RIS)
BibTeX

97

Views

7

Downloads

Citations

0

Crossref

0

WoS

0

Scopus

0

CSCD

Abstract Full text About this article
Background

Shifts in forest phenological events serve as strong indicators of climate change. However, the sensitivity of phenology events to climate change in relation to forest origins has received limited attention. Moreover, it is unknown whether forest phenology changes with the proximity to forest edge.

Methods

This study examined the green-up dates, dormancy dates, time-integrated NDVI (LiNDVI, a measure of vegetation productivity in growing season), and their sensitivities to climatic factors along the gradients of distance (i.e. proximity) to forest edge (0–2 ​km) in China's natural forests (NF) and planted forests (PF). For the analysis, field-surveyed data were integrated with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI from 2000 to 2022.

Results

Our results reveal that PF had earlier green-up dates, later dormancy dates, and higher LiNDVI than NF. However, green-up sensitivities to temperature were higher at the edges of NF, whereas no such pattern was observed in PF. Conversely, the sensitivity of dormancy dates remains relatively stable from the inner to the edge of both NF and PF, except for a quadratic change in dormancy date sensitivity to precipitation found in NF. Additionally, we found that the green-up sensitivity to temperature increased with decreasing proximity to edge in NF evergreen forests, while it showed the opposite trend in PF evergreen forests. Furthermore, we observed that the precipitation impact on green-up dates shifts from postponing to advancing from the inner to the edge of NF, whereas precipitation dominantly postpones PF's green-up dates regardless of the proximity to edge. The LiNDVI exhibits higher sensitivity to precipitation at the edge areas, a phenomenon observed in NF but not in PF.

Conclusions

These results suggest that the responses of forests to climate change vary with the distance to the edge. With increasing edge forests, which results from fragmentation caused by global changes, we anticipate that desynchronized phenological events along the distance to the edge could alter biogeochemical cycles and reshape ecosystem services such as energy flows, pollination duration, and the tourism industry. Therefore, we advocate for further investigations of edge effects to improve ecosystem modelling, enhance forest stability, and promote sustainable tourism.


menu
Abstract
Full text
Outline
About this article

Sensitivity of forest phenology in China varies with proximity to forest edges

Show Author's information Weibin Youa,b, Ziyi Xianc,d, Guoyi Zhouc,d, Evgenios Agathokleousc,d, Zhen Yuc,d( )
College of JunCao Science and Ecology, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Fujian Southern Forest Resources and Environmental Engineering Technology Research Center, College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Research Center for Global Changes and Ecosystem Carbon Sequestration & Mitigation, Nanjing University of Information Science & Technology, Nanjing 210044, China

Abstract

Background

Shifts in forest phenological events serve as strong indicators of climate change. However, the sensitivity of phenology events to climate change in relation to forest origins has received limited attention. Moreover, it is unknown whether forest phenology changes with the proximity to forest edge.

Methods

This study examined the green-up dates, dormancy dates, time-integrated NDVI (LiNDVI, a measure of vegetation productivity in growing season), and their sensitivities to climatic factors along the gradients of distance (i.e. proximity) to forest edge (0–2 ​km) in China's natural forests (NF) and planted forests (PF). For the analysis, field-surveyed data were integrated with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI from 2000 to 2022.

Results

Our results reveal that PF had earlier green-up dates, later dormancy dates, and higher LiNDVI than NF. However, green-up sensitivities to temperature were higher at the edges of NF, whereas no such pattern was observed in PF. Conversely, the sensitivity of dormancy dates remains relatively stable from the inner to the edge of both NF and PF, except for a quadratic change in dormancy date sensitivity to precipitation found in NF. Additionally, we found that the green-up sensitivity to temperature increased with decreasing proximity to edge in NF evergreen forests, while it showed the opposite trend in PF evergreen forests. Furthermore, we observed that the precipitation impact on green-up dates shifts from postponing to advancing from the inner to the edge of NF, whereas precipitation dominantly postpones PF's green-up dates regardless of the proximity to edge. The LiNDVI exhibits higher sensitivity to precipitation at the edge areas, a phenomenon observed in NF but not in PF.

Conclusions

These results suggest that the responses of forests to climate change vary with the distance to the edge. With increasing edge forests, which results from fragmentation caused by global changes, we anticipate that desynchronized phenological events along the distance to the edge could alter biogeochemical cycles and reshape ecosystem services such as energy flows, pollination duration, and the tourism industry. Therefore, we advocate for further investigations of edge effects to improve ecosystem modelling, enhance forest stability, and promote sustainable tourism.

Keywords: Climate change, Edge effects, Natural forests, Planted forests, Phenology sensitivity

References(67)

Baker, T.P., Jordan, G.J., Steel, E.A., Fountain-Jones, N.M., Wardlaw, T.J., Baker, S.C., 2014. Microclimate through space and time: microclimatic variation at the edge of regeneration forests over daily, yearly and decadal time scales. For. Ecol. Manag. 334, 174-184. https://doi.org/10.1016/j.foreco.2014.09.008.
DOI Google Scholar

Berra, E.F., Gaulton, R., 2021. Remote sensing of temperate and boreal forest phenology: a review of progress, challenges and opportunities in the intercomparison of in-situ and satellite phenological metrics. For. Ecol. Manag. 480, 118663. https://doi.org/10.1016/j.foreco.2020.118663.
DOI Google Scholar

Blanchard, G., Barbier, N., Vieilledent, G., Ibanez, T., Hequet, V., McCoy, S., Birnbaum, P., 2023. UAV-Lidar reveals that canopy structure mediates the influence of edge effects on forest diversity, function and microclimate. J. Ecol. 111(7), 1375-1586. https://doi.org/10.1111/1365-2745.14105.
DOI Google Scholar

Brinck, K., Fischer, R., Groeneveld, J., Lehmann, S., Dantas, D.P.M., Pütz, S., Sexton, J.O., Song, D.X., Huth, A., 2017. High resolution analysis of tropical forest fragmentation and its impact on the global carbon cycle. Nat. Commun. 8(1), 14855. https://doi.org/10.1038/ncomms14855.
DOI Google Scholar

Chen, C., Park, T., Wang, X., Piao, S., Xu, B., Chaturvedi, R. K., Myneni, R. B., 2019. China and India lead in greening of the world through land-use management. Nat. Sustain. 2(2), 122-129. https://doi.org/10.1038/s41893-019-0220-7.
DOI Google Scholar

Chen, X., Ciais, P., Maignan, F., Zhang, Y., Bastos, A., Liu, L., Zhang, H., 2021. Vapor pressure deficit and sunlight explain seasonality of leaf phenology and photosynthesis across Amazonian evergreen broadleaved forest. Global Biogeochem. Cycles 35(6), e2020GB006893. https://doi.org/10.1029/2020GB006893.
DOI Google Scholar
Collinge, S.K., 2009. Ecology of Fragmented Landscapes. Johns Hopkins University Press, Baltimore.
DOI

de Casenave, J.L., Pelotto, J.P., Protomastro, J., 1995. Edge-interior differences in vegetation structure and composition in a Chaco semi-arid forest, Argentina. For. Ecol. Manag. 72(1), 61-69. https://doi.org/10.1016/0378-1127(94)03444-2.
DOI Google Scholar

Dong, Y., Agathokleous, E., Liu, S., Yu, Z., 2023. Demographic changes in China's forests from 1998 to 2018. For. Ecosyst. 10, 100094. https://doi.org/10.1016/j.fecs.2023.100094.
DOI Google Scholar

Elmore, A.J., Guinn, S.M., Minsley, B.J., Richardson, A.D., 2012. Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests. Global Change Biol. 18(2), 656-674. https://doi.org/10.1111/j.1365-2486.2011.02521.x.
DOI Google Scholar

Esseen, P.A., Hedström Ringvall, A., Harper, K.A., Christensen, P., Svensson, J., 2016. Factors driving structure of natural and anthropogenic forest edges from temperate to boreal ecosystems. J. Veg. Sci. 27(3), 482-492. https://doi.org/10.1111/jvs.12387.
DOI Google Scholar

Ettinger, A.K., Gee, S., Wolkovich E.M., 2018. Phenological sequences: how early-season events define those that follow. Am. J. Bot. 105(10), 1771-1780. https://doi.org/10.1002/ajb2.1174.
DOI Google Scholar

Fahrig, L., Arroyo-Rodríguez, V., Bennett, J.R., Boucher-Lalonde, V., Cazetta, E., Currie, D.J., Eigenbrod, F., Ford, A.T., Harrison, S.P., Jaeger, J.A.G, Koper, N., Martin, A.E., Martin, J.L., Metzger, J.P., Morrison, P., Rhodes, J.R., Saunders, D.A., Simberloff, D., Smith, A.C., Tischendorf, L., Vellend, M., Watling, J.I., 2019. Is habitat fragmentation bad for biodiversity? Biol. Conserv. 230, 179-186. https://doi.org/10.1016/j.biocon.2018.12.026.
DOI Google Scholar

Fischer, R., Taubert, F., Müller, M.S., Groeneveld, J., Lehmann, S., Wiegand, T. Huth, A., 2021. Accelerated forest fragmentation leads to critical increase in tropical forest edge area. Sci. Adv. 7(37), eabg7012. https://doi.org/10.1126/sciadv.abg7012.
DOI Google Scholar
Food and Agriculture Organization of the United Nations (FAO), 2020. Global Forest Resources Assessment 2020: Main Report. Rome.

Gao, X., Gray, J.M., Reich, B.J., 2021. Long-term, medium spatial resolution annual land surface phenology with a Bayesian hierarchical model. Remote Sens. Environ. 261, 112484. https://doi.org/10.1016/j.rse.2021.112484.
DOI Google Scholar

Garvey, S.M., Templer, P.H., Pierce, E.A., Reinmann, A.B., Hutyra, L.R., 2022. Diverging patterns at the forest edge: soil respiration dynamics of fragmented forests in urban and rural areas. Global Change Biol. 28(9), 3094-3109. https://doi.org/10.1111/gcb.16099.
DOI Google Scholar

Ge, Q., Dai, J., Liu, J., Zhong, S., Liu, H., 2013. The effect of climate change on the fall foliage vacation in China. Tourism Manag. 38, 80-84. https://doi.org/10.1016/j.tourman.2013.02.020.
DOI Google Scholar

Haddad, N.M., Brudvig, L.A., Clobert, J., 2015. Habitat fragmentation and its lasting impact on Earth's ecosystems. Sci. Adv. 1(2), e1500052. https://doi.org/10.1126/sciadv.1500052.
DOI Google Scholar

Han, P., Christine, B., 2019. Global change-driven modulation of bottom–up forces and cascading effects on biocontrol services. Curr. Opin. Insect Sci. 35, 27-33. https://doi.org/10.1016/j.cois.2019.05.005.
DOI Google Scholar

Hong, S., Zhang, Y., Yao, Y., Meng, F., Zhao, Q., Zhang, Y., 2022. Contrasting temperature effects on the velocity of early-versus late-stage vegetation green-up in the Northern Hemisphere. Global Change Biol. 28(23), 6961-6972. https://doi.org/10.1111/gcb.16414.
DOI Google Scholar

Jia, G.J., Epstein, H.E., Walker, D.A., 2006. Spatial heterogeneity of tundra vegetation response to recent temperature changes. Global Change Biol. 12(1), 42-55, https://doi.org/10.1111/j.1365-2486.2005.01079.x.
DOI Google Scholar

Keenan, T.F., Gray, J., Friedl, M.A., Toomey, M., Bohrer, G., Hollinger, D.Y., Munger, J.W., O'Keefe, J., Schmid, H.P., Wing, I.S., Yang, B., 2014. Net carbon uptake has increased through warming-induced changes in temperate forest phenology. Nat. Clim. Change, 4(7), 598-604. https://doi.org/10.1038/NCLIMATE2253.
DOI Google Scholar

Kim, M., Lee, S., Lee, H., Lee, S., 2021. Phenological response in the trophic levels to climate change in Korea. Int. J. Environ. Res. Publ. Health 18(3), 1086. https://doi.org/10.3390/ijerph18031086.
DOI Google Scholar

Koebsch, F., Sonnentag, O., Järveoja, J., 2020. Refining the role of phenology in regulating gross ecosystem productivity across European peatlands. Global Change Biol. 26(2), 876-887. https://doi.org/10.1111/gcb.14905.
DOI Google Scholar

Kudo, G., Cooper, E.J., 2019. When spring ephemerals fail to meet pollinators: mechanism of phenological mismatch and its impact on plant reproduction. P. Roy. Soc. B-Biol. Sci. 286(1904), 20190573. https://doi.org/10.1098/rspb.2019.0573.
DOI Google Scholar

Li, X., Ault, T., Richardson, A.D., 2023. Impacts of shifting phenology on boundary layer dynamics in North America in the CESM. Agric. For. Meteorol. 330, 109286. https://doi.org/10.1016/j.agrformet.2022.109286.
DOI Google Scholar

Liu, J., Coomes, D.A., Gibson, L., Hu, G., Liu, J., Luo, Y., Yu, M., 2019. Forest fragmentation in China and its effect on biodiversity. Biol. Rev. 94(5), 1636-1657. https://doi.org/10.1111/brv.12519.
DOI Google Scholar

Ma, J., Li, J., Wu, W., Liu, J., 2023. Global forest fragmentation change from 2000 to 2020. Nat. Commun. 14(1), 3752. https://doi.org/10.1038/s41467-023-39221-x.
DOI Google Scholar

Matlack, G.R., 1993. Sociological edge effects: spatial distribution of human impact in suburban forest fragments. Environ. Manag.17, 829-835. https://doi.org/10.1007/BF02393903.
DOI Google Scholar

Meeussen, C., Govaert, S., Vanneste, T., Calders, K., Bollmann, K., Brunet, J., Cousins, S.A., Diekmann, M., Graae, B.J., Hedwall, P.O., Moorthy, S.M.K., 2020. Structural variation of forest edges across Europe. For. Ecol. Manag. 462, 117929. https://doi.org/10.1016/j.foreco.2020.117929.
DOI Google Scholar
Menke, W., 2018. Geophysical Data Analysis: Discrete Inverse Theory. Academic Press.

Menzel, A., Estrella, N., Fabian, P., 2001. Spatial and temporal variability of the phenological seasons in Germany from 1951 to 1996. Global Change Biol. 7(6), 657-666. https://doi.org/10.1111/j.1365-2486.2001.00430.x.
DOI Google Scholar

Morreale, L.L., Thompson, J.R., Tang, X., 2021.Elevated growth and biomass along temperate forest edges. Nat. Commun. 12(1), 7181. https://doi.org/10.1038/s41467-021-27373-7.
DOI Google Scholar

Müller, A., Correa, M.Z., Führ, C.S., Padoin, T.O.H., de Quevedo, D.M., Schmitt, J.L., 2021. The effects of natural and artificial edges on phenology: a case study of Ctenitis submarginalis. Austral Ecol. 46(3), 387-397. https://doi.org/10.1111/aec.12994.
DOI Google Scholar

Nunes, M.H., Camargo, J.L.C., Vincent, G., Calders, K., Oliveira, R.S., Huete, A., Maeda, E.E., 2022. Forest fragmentation impacts the seasonality of Amazonian evergreen canopies. Nat. Commun. 13(1), 917. https://doi.org/10.1038/s41467-022-28490-7.
DOI Google Scholar

Ochoa-Hueso, R., Delgado-Baquerizo, M., Risch, A.C., Schrama, M., Morriën, E., Barmentlo, S.H., van der Putten, W.H., 2021. Ecosystem coupling: a unifying framework to understand the functioning and recovery of ecosystems. One Earth 4(7), 951-966. https://doi.org/10.1016/j.oneear.2021.06.011.
DOI Google Scholar

Park, H., Jeong, S., Peñuelas, J., 2020. Accelerated rate of vegetation green-up related to warming at northern high latitudes. Global Change Biol. 26(11), 6190-6202. https://doi.org/10.1111/gcb.15322.
DOI Google Scholar
Peng, S., 2020. 1-km Monthly Precipitation Dataset for China (1901-2022). National Tibetan Plateau Data Center, Beijing, China. https://doi.org/10.5281/zenodo.3185722.

Peng, S., Ding, Y., Liu, W., 2019. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017. Earth Syst. Sci. Data. 11(4), 1931-1946. https://doi.org/10.5194/essd-11-1931-2019.
DOI Google Scholar

Pettorelli, N., Vik, J.O., Mysterud, A., Gaillard, J.M., Tucker, C.J., Stenseth, N.C., 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends Ecol. Evol. 20(9), 503-510. https://doi.org/10.1016/j.tree.2005.05.011.
DOI Google Scholar

Pfeifer, M., Lefebvre, V., Peres, C.A., Banks-Leite, C., Wearn, O.R., Marsh, C.J., Butchart S.H., Arroyo-Rodríguez, V., Barlow, J., Cerezo, A., Cisneros, L., 2017. Creation of forest edges has a global impact on forest vertebrates. Nature 551(7679), 187-191. https://doi.org/10.1038/nature24457.
DOI Google Scholar

Piao, S., Liu, Q., Chen, A., 2019. Plant phenology and global climate change: Current progresses and challenges. Global Change Biol. 25(6), 1922-1940. https://doi.org/10.1111/gcb.14619.
DOI Google Scholar

Piao, S., Wang, J., Li, X., Xu, H., Zhang, Y., 2022. Spatio-temporal changes in the speed of canopy development and senescence in temperate China. Global Change Biol. 28(24), 7366-7375. https://doi.org/10.1111/gcb.16408.
DOI Google Scholar

Remy, E., Wuyts, K., Boeckx, P., Ginzburg, S., Gundersen, P., Demey, A., Bulcke, J.V.D., Acker, J.V., Verheyen, K., 2016. Strong gradients in nitrogen and carbon stocks at temperate forest edges. For. Ecol. Manag. 376, 45-58. https://doi.org/10.1016/j.scitotenv.2020.143497.
DOI Google Scholar

Richardson, A.D., Keenan, T.F., Migliavacca, M., Ryu, Y., Sonnentag, O., Toomey, M., 2013. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agric. For. Meteorol. 169, 156-173. https://doi.org/10.1080/15481603.2022.2163575.
DOI Google Scholar

Ruddell, E.J., Hammitt, W.E., 1987. Prospect refuge theory: a psychological orientation for edge effect in recreation environments. J. Leisure Res. 19(4), 249-260. https://doi.org/10.1080/00222216.1987.11969696.
DOI Google Scholar

Sippel, S., Reichstein, M., Ma, X., 2018. Drought, heat, and the carbon cycle: a review. Curr. Clim. Change Rep. 4, 266-286. https://doi.org/10.1007/s40641-018-0103-4.
DOI Google Scholar

Smith, I.A., Hutyra, L.R., Reinmann, A.B., Marrs, J.K., Thompson, J.R., 2018. Piecing together the fragments: elucidating edge effects on forest carbon dynamics. Front. Ecol. Environ. 16(4), 213-221. https://doi.org/10.1002/fee.1793.
DOI Google Scholar

Spencer, D.M., Holecek, D.F., 2007. A profile of the fall foliage tourism market. J. Vacat. Mark. 13(4), 339-358. https://doi.org/10.1177/1356766707081011.
DOI Google Scholar

Sun, P., Yu, Z., Liu, S., Wei, X., Wang, J., Zegre, N., Liu, N., 2012. Climate change, growing season water deficit and vegetation activity along the north–south transect of eastern China from 1982 through 2006. Hydrol. Earth Syst. Sci. 16(10), 3835-3850. https://doi.org/10.5194/hess-16-3835-2012.
DOI Google Scholar

Tang, X., Zhao, X., Bai, Y., Tang, Z., Wang, W., Zhao, Y., Zhou, G., 2018. Carbon pools in China's terrestrial ecosystems: new estimates based on an intensive field survey. Proc. Natl. Acad. Sci. U.S.A. 115(16), 4021-4026. https://doi.org/10.1073/pnas.1700291115.
DOI Google Scholar

Thackeray, S.J., Henrys, P.A., Hemming, D., Bell, J.R., Botham, M.S., Burthe, S., Helaouet, P., Johns, D.G., Jones, I.D., Leech, D.I., Mackay, E.B., 2016. Phenological sensitivity to climate across taxa and trophic levels. Nature 535(7611), 241-245. https://doi.org/10.1038/nature18608.
DOI Google Scholar

Vinod, N., Slot, M., McGregor, I.R., Ordway, E.M., Smith, M.N., Taylor, T.C., Anderson-Teixeira, K.J., 2023. Thermal sensitivity across forest vertical profiles: patterns, mechanisms, and ecological implications. New Phytol. 237(1), 22-47. https://doi.org/10.1111/nph.18539.
DOI Google Scholar

Vogado, N.O., de Camargo, M.G.G., Locosselli, G.M., Morellato, L.P.C., 2016. Edge effects on the phenology of the guamirim, Myrcia guianensis (Myrtaceae), a cerrado tree, Brazil. Trop. Conserv. Sci. 9(1), 291-312. https://doi.org/10.1177/194008291600900115.
DOI Google Scholar

Wang, C., Tang, Y., 2019. Responses of plant phenology to nitrogen addition: a meta-analysis. Oikos 128(9), 1243-1253. https://doi.org/10.1111/oik.06099.
DOI Google Scholar

Xia, J., Niu, S., Ciais, P., Janssens, I.A., Chen, J., Ammann, C., Arain, A., Blanken, P.D., Cescatti, A., Bonal, D., Buchmann, N., 2015. Joint control of terrestrial gross primary productivity by plant phenology and physiology. Proc. Natl. Acad. Sci. U. S. A. 112(9), 2788-2793. https://doi.org/10.1073/pnas.1413090112.
DOI Google Scholar

Xie, Y., Wang, X., Silander Jr, J.A., 2015. Deciduous forest responses to temperature, precipitation, and drought imply complex climate change impacts. Proc. Natl. Acad. Sci. U. S. A. 112(44), 13585-13590. https://doi.org/10.1073/pnas.1509991112.
DOI Google Scholar

Yang, J., Huang, X., 2021. The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019. Earth Syst. Sci. Data 13(8), 3907-3925. https://doi.org/10.5194/essd-13-3907-2021.
DOI Google Scholar

Yu, L., Liu, T., Bu, K., Yan, F., Yang, J., Chang, L., Zhang, S., 2017. Monitoring the long term vegetation phenology change in Northeast China from 1982 to 2015. Sci. Rep., 7(1), 14770. https://doi.org/10.1038/s41598-017-14918-4.
DOI Google Scholar

Yu, Z., Lu, C., Cao, P., Tian, H., Hessl, A., Pederson, N., 2018. Earlier leaf-flushing suppressed ecosystem productivity by draining soil water in the Mongolian Plateau. Agric. For. Meteorol. 250, 1-8. https://doi.org/10.1016/j.agrformet.2017.11.035.
DOI Google Scholar

Yu, Z., Zhou, G., Liu, S., Sun, P., Agathokleous, E., 2020. Impacts of forest management intensity on carbon accumulation of China's forest plantations. For. Ecol. Manag. 472, 118252. https://doi.org/10.1016/j.foreco.2020.118252.
DOI Google Scholar

Yu, Z., Ciais, P., Piao, S., Houghton, R.A., Lu, C., Tian, H., Agathokleous, E, Kattel, G. R., Sitch, S., Goll, D., Yue, X., Walker, A., Friedlingstein, P., Jain, A.K., Liu, S., Zhou, G., 2022. Forest expansion dominates China's land carbon sink since 1980. Nat. Commun. 13(1), 5374. https://doi.org/10.1038/s41467-022-32961-2.
DOI Google Scholar

Yuan, X., Wang, Y., Ji, P., Wu, P., Sheffield, J., Otkin, J.A., 2023. A global transition to flash droughts under climate change. Science 380(6641), 187-191. https://doi.org/10.1126/science.abn6301.
DOI Google Scholar

Zaninotto, V., Raynaud, X., Gendreau, E., Kraepiel, Y., Motard, E., Babiar, O., Dajoz, I., 2020. Broader phenology of pollinator activity and higher plant reproductive success in an urban habitat compared to a rural one. Ecol. Evol. 10(20), 11607-11621. https://doi.org/10.1002/ece3.6794.
DOI Google Scholar

Zhao, Y., Chen, X., Kim, J.S., Williams, M., 2022. Effects of temperature and precipitation on litterfall phenology in four evergreen broad-leaved forests of southern China. Biotropica, 54(3), 739-753. https://doi.org/10.1111/btp.13094.
DOI Google Scholar

Zhou, D., Zhao, S., Zhang, L., Sun, G., Liu, Y., 2015. The footprint of urban heat island effect in China. Sci. Rep. 5(1), 1-11. https://doi.org/10.1038/srep11160.
DOI Google Scholar
Publication history
Copyright
Acknowledgements
Rights and permissions

Publication history

Received: 22 July 2023
Revised: 13 October 2023
Accepted: 14 October 2023
Published: 23 October 2023
Issue date: December 2023

Copyright

© 2023 The Authors.

Acknowledgements

Acknowledgements

We thank Jingyun Fang, Guirui Yu, Gengxu Wang, Keping Ma, Shenggong Li, Sheng Du, Shijie Han, Youxin Ma, Deqiang Zhang, Shizhong Liu, Guowei Chu, Qianmei Zhang, Yuelin Li, Wantong Wang, Junhua Yan, Juxiu Liu, and Xuli Tang for their efforts in collecting field data.

Rights and permissions

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Return