AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Forest Ecosystems Article
PDF (5.3 MB)
Cite
EndNote(RIS) BibTeX
Collect
AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

How forest age impacts on net primary productivity: Insights from future multi-scenarios

Lei Tiana,b, Yu Taoa, Simms Joannab, Annikki Mäkeläb, Mingyang Lia( )
Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China
Faculty of Agriculture and Forestry, University of Helsinki, Helsinki, Finland
Show Author Information

Abstract

Forest net primary productivity (NPP) constitutes a key flux within the terrestrial ecosystem carbon cycle and serves as a significant indicator of the forests carbon sequestration capacity, which is closely related to forest age. Despite its significance, the impact of forest age on NPP is often ignored in future NPP projections. Here, we mapped forest age in Hunan Province at a 30-m resolution utilizing a combination of Landsat time series stack (LTSS), national forest inventory (NFI) data, and the relationships between height and age. Subsequently, NPP was derived from NFI data and the relationships between NPP and age was built for various forest types. Then forest NPP was predicted based on the NPP-age relationships under three future scenarios, assessing the impact of forest age on NPP. Our findings reveal substantial variations in forest NPP in Hunan Province under three future scenarios: under the age-only scenario, NPP peaks in 2041 (133.56 Tg C·yr−1), while NPP peaks three years later in 2044 (141.14 Tg C·yr−1) under the natural development scenario. The maximum afforestation scenario exhibits the most rapid increase in NPP, with peaking in 2049 (197.95 Tg C·yr−1). However, with the aging of the forest, NPP is projected to then decrease by 7.54%, 6.07%, and 7.47% in 2060, and 20.05%, 19.74%, and 28.38% in 2100, respectively, compared to their peaks under the three scenarios. This indicates that forest NPP will continue to decline soon. Controlling the age structure of forests through selective logging, afforestation and reforestation, and encouraging natural regeneration after disturbance could mitigate this declining trend in forest NPP, but implications of these measures on the full forest carbon balance remain to be studied. Insights from the future multi-scenarios are expected to provide data to support sustainable forest management and national policy development, which will inform the achievement of carbon neutrality goals by 2060.

Keywords

Net primary productivityForest ageNPP-Age relationshipsNPP projectionsAfforestation

References

 

Allen, C.D., Macalady, A.K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D.D., Hogg, E.H., Gonzalez, P., Fensham, R., Zhang, Z., Castro, J., Demidova, N., Lim, J.H., Allard, G., Running, S.W., Semerci, A., Cobb, N., 2010. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For. Ecol. Manag. 259, 660–684. https://doi.org/10.1016/j.foreco.2009.09.001.
Crossref Google Scholar
 

Aryal, D.R., De Jong, B.H.J., Sánchez-Silva, S., Haas-Ek, A., Esparza-Olguin, L., Ochoa-Gaona, S., Ghimire, R., Morales-Ruiz, D.E., 2024. Biomass recovery along a tropical forest succession: trends on tree diversity, wood traits and stand structure. For. Ecol. Manag. 555, 121709. https://doi.org/10.1016/j.foreco.2024.121709.
Crossref Google Scholar
 

Baldocchi, D., Penuelas, J., 2019. The physics and ecology of mining carbon dioxide from the atmosphere by ecosystems. Global Change Biol. 25, 1191–1197. https://doi.org/10.1111/gcb.14559.
Crossref Google Scholar
 
Baltodano, J., 2000. Monoculture forestry: a critique from an ecological perspective. Tree trouble: a compilation of testimonies on the negative impact of large-scale monoculture tree plantations. The 6th COP of the FCCC. The Hague, The Netherlands.
 

Bernier, P., Schoene, D., 2009. Adapting forests and their management to climate change: an overiew. Unasylva 60, 5–11.
Google Scholar
 

Besnard, S., Koirala, S., Santoro, M., Weber, U., Nelson, J., Gutter, J., Herault, B., Kassi, J., N'Guessan, A., Neigh, C., Poulter, B., Zhang, T., Carvalhais, N., 2021. Mapping global forest age from forest inventories, biomass and climate data. Earth Syst. Sci. Data 13, 4881–4896. https://doi.org/10.5194/essd-13-4881-2021.
Crossref Google Scholar
 

Bond-Lamberty, B., Wang, C.K., Gower, S.T., 2004. Net primary production and net ecosystem production of a boreal black spruce wildfire chronosequence. Global Change Biol. 10, 473–487. https://doi.org/10.1111/j.1529-8817.2003.0742.x.
Crossref Google Scholar
 

Bowyer, J.L., 2006. Forest plantations threatening or saving natural forests? IUCN/WWF Forest Conservation Newsletter 31, 8–9.
Google Scholar
 

Brockerhoff, E.G., Jactel, H., Parrotta, J.A., Ferraz, S.F.B., 2013. Role of eucalypt and other planted forests in biodiversity conservation and the provision of biodiversity-related ecosystem services. For. Ecol. Manag. 301, 43–50. https://doi.org/10.1016/j.foreco.2012.09.018.
Crossref Google Scholar
 

Bryan, B.A., Gao, L., Ye, Y.Q., Sun, X.F., Connor, J.D., Crossman, N.D., Stafford-Smith, M., Wu, J.G., He, C.Y., Yu, D.Y., Liu, Z.F., Li, A., Huang, Q.X., Ren, H., Deng, X.Z., Zheng, H., Niu, J.M., Han, G.D., Hou, X.Y., 2018. China's response to a national land-system sustainability emergency. Nature 559, 193–204. https://doi.org/10.1038/s41586-018-0280-2.
Crossref Google Scholar
 

Cai, W.X., He, N.P., Li, M.X., Xu, L., Wang, L.Z., Zhu, J.H., Zeng, N., Yan, P., Si, G.X., Zhang, X.Q., Cen, X.Y., Yu, G.R., Sun, O.J., 2022. Carbon sequestration of Chinese forests from 2010 to 2060 spatiotemporal dynamics and its regulatory strategies. Sci. Bull. 67, 836–843. https://doi.org/10.1016/j.scib.2021.12.012.
Crossref Google Scholar
 

Camenzind, T., Hättenschwiler, S., Treseder, K.K., Lehmann, A., Rillig, M.C., 2018. Nutrient limitation of soil microbial processes in tropical forests. Ecol. Monogr. 88, 4–21. https://doi.org/10.1002/ecm.1279.
Crossref Google Scholar
 

Cao, H., Liu, J., Wang, G.Z., Yang, G., Luo, L., 2015. Identification of sand and dust storm source areas in Iran. J. Arid Land 7, 567–578. https://doi.org/10.1007/s40333-015-0127-8.
Crossref Google Scholar
 

Carnus, J.M., Parrotta, J., Brockerhoff, E., Arbez, M., Jactel, H., Kremer, A., Lamb, D., O'Hara, K., Walters, B., 2006. Planted forests and biodiversity. J. For. 104, 65–77. https://doi.org/10.1093/jof/104.2.65.
Crossref Google Scholar
 

Chapin, F.S., Woodwell, G.M., Randerson, J.T., Rastetter, E.B., Lovett, G.M., Baldocchi, D.D., Clark, D.A., Harmon, M.E., Schimel, D.S., Valentini, R., Wirth, C., Aber, J.D., Cole, J.J., Goulden, M.L., Harden, J.W., Heimann, M., Howarth, R.W., Matson, P.A., McGuire, A.D., Melillo, J.M., Mooney, H.A., Neff, J.C., Houghton, R.A., Pace, M.L., Ryan, M.G., Running, S.W., Sala, O.E., Schlesinger, W.H., Schulze, E.D., 2006. Reconciling carbon-cycle concepts, terminology, and methods. Ecosystems 9, 1041–1050. https://doi.org/10.1007/s10021-005-0105-7.
Crossref Google Scholar
 

Chen, C., Riley, W.J., Prentice, I.C., Keenan, T.F., 2022. CO2 fertilization of terrestrial photosynthesis inferred from site to global scales. P. Natl. Acad. Sci. USA 119, e2115627119. https://doi.org/10.1073/pnas.2115627119.
Crossref Google Scholar
 

Chen, J.M., 2021. Carbon neutrality: toward a sustainable future. Innovation 2, 100127. https://doi.org/10.1016/j.xinn.2021.100127.
Crossref Google Scholar
 

Chen, J.M., Ju, W.M., Ciais, P., Viovy, N., Liu, R.G., Liu, Y., Lu, X.H., 2019a. Vegetation structural change since 1981 significantly enhanced the terrestrial carbon sink. Nat. Commun. 10, 4259. https://doi.org/10.1038/s41467-019-12257-8.
Crossref Google Scholar
 

Chen, J.M., Ju, W.M., Cihlar, J., Price, D., Liu, J., Chen, W.J., Pan, J.J., Black, A., Barr, A., 2003. Spatial distribution of carbon sources and sinks in Canada's forests. Tellus B 55, 622–641. https://doi.org/10.1034/j.1600-0889.2003.00036.x.
Crossref Google Scholar
 

Chen, L.C., Guan, X., Li, H.M., Wang, Q.K., Zhang, W.D., Yang, Q.P., Wang, S.L., 2019b. Spatiotemporal patterns of carbon storage in forest ecosystems in Hunan Province, China. For. Ecol. Manag. 432, 656–666. https://doi.org/10.1016/j.foreco.2018.09.059.
Crossref Google Scholar
 

Chen, W.J., Chen, J.M., Price, D.T., Cihlar, J., 2002. Effects of stand age on net primary productivity of boreal black spruce forests in Ontario, Canada. Can. J. For. Res. 32, 833–842. https://doi.org/10.1139/x01-165.
Crossref Google Scholar
 

Clay, L., Motallebi, M., Song, B., 2019. An analysis of common forest management practices for carbon sequestration in South Carolina. Forests 10. https://doi.org/10.3390/f10110949.
Crossref Google Scholar
 

Drake, J.E., Davis, S.C., Raetz, L.M., DeLucia, E.H., 2011. Mechanisms of age-related changes in forest production: the influence of physiological and successional changes. Global Change Biol. 17, 1522–1535. https://doi.org/10.1111/j.1365-2486.2010.02342.x.
Crossref Google Scholar
 

Dybala, K.E., Steger, K., Walsh, R.G., Smart, D.R., Gardali, T., Seavy, N.E., 2019. Optimizing carbon storage and biodiversity co-benefits in reforested riparian zones. J. Appl. Ecol. 56, 343–353. https://doi.org/10.1111/1365-2664.13272.
Crossref Google Scholar
 

Ebrahimy, H., Aghighi, H., Azadbakht, M., Amani, M., Mahdavi, S., Matkan, A.A., 2021. Downscaling MODIS land surface temperature product using an adaptive random forest regression method and Google Earth engine for a 19-years spatiotemporal trend analysis over Iran. IEEE J-Stars 14, 2103–2112. https://doi.org/10.1109/jstars.2021.3051422.
Crossref Google Scholar
 

Erbaugh, J.T., Pradhan, N., Adams, J., Oldekop, J.A., Agrawal, A., Brockington, D., Pritchard, R., Chhatre, A., 2020. Global forest restoration and the importance of prioritizing local communities. Nat. Ecol. Evol. 4, 1472–1476. https://doi.org/10.1038/s41559-020-01282-2.
Crossref Google Scholar
 
Evans, J., 2000. Sustainability of productivity in successive rotations. Proceedings of the International Conference on Timber Plantation Development. Manila, Philippines.
 

Feng, Y.H., Schmid, B., Loreau, M., Forrester, D., Fei, S.L., Zhu, J.X., Tang, Z.Y., Zhu, J.L., Hong, P.B., Ji, C.J., Shi, Y., Su, H.J., Xiong, X.Y., Xiao, J., Wang, S.P., Fang, J.Y., 2022. Multispecies forest plantations outyield monocultures across a broad range of conditions. Science 376, 865–868. https://doi.org/10.1126/science.abm6363.
Crossref Google Scholar
 

Ferreira, G.W.D., Rau, B.M., Aubrey, D.P., 2020. Herbicide, fertilization, and planting density effects on intensively managed loblolly pine early stand development. For. Ecol. Manag. 472, 118206. https://doi.org/10.1016/j.foreco.2020.118206.
Crossref Google Scholar
 

Fisher, J.B., Badgley, G., Blyth, E., 2012. Global nutrient limitation in terrestrial vegetation. Global Biogeochem. Cycles 26, GB004252. https://doi.org/10.1029/2011gb004252.
Crossref Google Scholar
 

Foga, S., Scaramuzza, P.L., Guo, S., Zhu, Z., Dilley, R.D., Beckmann, T., Schmidt, G.L., Dwyer, J.L., Hughes, M.J., Laue, B., 2017. Cloud detection algorithm comparison and validation for operational Landsat data products. Remote Sens. Environ. 194, 379–390. https://doi.org/10.1016/j.rse.2017.03.026.
Crossref Google Scholar
 

Friedlingstein, P., Jones, M.W., O'Sullivan, M., Andrew, R.M., Bakker, D.C.E., Hauck, J., Le Quéré, C., Peters, G.P., Peters, W., Pongratz, J., Sitch, S., Canadell, J.G., Ciais, P., Jackson, R.B., Alin, S.R., Anthoni, P., Bates, N.R., Becker, M., Bellouin, N., Bopp, L., Chau, T.T.T., Chevallier, F., Chini, L.P., Cronin, M., Currie, K.I., Decharme, B., Djeutchouang, L.M., Dou, X.Y., Evans, W., Feely, R.A., Feng, L., Gasser, T., Gilfillan, D., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Houghton, R.A., Hurtt, G.C., Iida, Y., Ilyina, T., Luijkx, I.T., Jain, A., Jones, S.D., Kato, E., Kennedy, D., Goldewijk, K.K., Knauer, J., Korsbakken, J.I., Körtzinger, A., Landschützer, P., Lauvset, S.K., Lefèvre, N., Lienert, S., Liu, J.J., Marland, G., McGuire, P.C., Melton, J.R., Munro, D.R., Nabel, J.E.M.S., Nakaoka, S.I., Niwa, Y., Ono, T., Pierrot, D., Poulter, B., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T.M., Schwinger, J., Schwingshackl, C., Séférian, R., Sutton, A.J., Sweeney, C., Tanhua, T., Tans, P.P., Tian, H.Q., Tilbrook, B., Tubiello, F., van der Werf, G.R., Vuichard, N., Wada, C., Wanninkhof, R., Watson, A.J., Willis, D., Wiltshire, A.J., Yuan, W.P., Yue, C., Yue, X., Zaehle, S., Zeng, J.Y., 2022a. Global carbon budget 2021. Earth Syst. Sci. Data 14, 1917–2005. https://doi.org/10.5194/essd-14-1917-2022.
Crossref Google Scholar
 

Friedlingstein, P., O'Sullivan, M., Jones, M.W., Andrew, R.M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I.T., Olsen, A., Peters, G.P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J.G., Ciais, P., Jackson, R.B., Alin, S.R., Alkama, R., Arneth, A., Arora, V.K., Bates, N.R., Becker, M., Bellouin, N., Bittig, H.C., Bopp, L., Chevallier, F., Chini, L.P., Cronin, M., Evans, W., Falk, S., Feely, R.A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R.A., Hurtt, G.C., Iida, Y., Ilyina, T., Jain, A.K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Goldewijk, K.K., Knauer, J., Korsbakken, J.I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J.J., Liu, Z., Marland, G., Mayot, N., McGrath, M.J., Metzl, N., Monacci, N.M., Munro, D.R., Nakaoka, S.I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P., Pan, N.Q., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T.M., Schwinger, J., Séférian, R., Shutler, J.D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A.J., Sweeney, C., Takao, S., Tanhua, T., Tans, P.P., Tian, X.J., Tian, H.Q., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G.R., Walker, A.P., Wanninkhof, R., Whitehead, C., Wranne, A.W., Wright, R., Yuan, W.P., Yue, C., Yue, X., Zaehle, S., Zeng, J.Y., Zheng, B., 2022b. Global carbon budget 2022. Earth Syst. Sci. Data 14, 4811–4900. https://doi.org/10.5194/essd-14-4811-2022.
Crossref Google Scholar
 

Gang, C.C., Zhao, W., Zhao, T., Zhang, Y., Gao, X.R., Wen, Z.M., 2018. The impacts of land conversion and management measures on the grassland net primary productivity over the Loess Plateau, Northern China. Sci. Total Environ. 645, 827–836. https://doi.org/10.1016/j.scitotenv.2018.07.161.
Crossref Google Scholar
 

Gao, B.L., Taylor, A.R., Searle, E.B., Kumar, P., Ma, Z.L., Hume, A.M., Chen, H.Y.H., 2018. Carbon storage declines in old boreal forests irrespective of succession pathway. Ecosystems 21, 1168–1182. https://doi.org/10.1007/s10021-017-0210-4.
Crossref Google Scholar
 

Gough, C.M., Vogel, C.S., Schmid, H.P., Curtis, P.S., 2008. Controls on annual forest carbon storage: lessons from the past and predictions for the future. Bioscience 58, 609–622. https://doi.org/10.1641/b580708.
Crossref Google Scholar
 

Goulden, M.L., McMillan, A.M.S., Winston, G.C., Rocha, A.V., Manies, K.L., Harden, J.W., Bond-Lamberty, B.P., 2011. Patterns of NPP, GPP, respiration, and NEP during boreal forest succession. Global Change Biol. 17, 855–871. https://doi.org/10.1111/j.1365-2486.2010.02274.x.
Crossref Google Scholar
 

Gundersen, P., Thybring, E.E., Nord-Larsen, T., Vesterdal, L., Nadelhoffer, K.J., Johannsen, V.K., 2021. Old-growth forest carbon sinks overestimated. Nature 591, E21–E23. https://doi.org/10.1038/s41586-021-03266-z.
Crossref Google Scholar
 

Guo, D., Song, X.N., Hu, R.H., Cai, S.H., Zhu, X.M., Hao, Y.B., 2021. Grassland type-dependent spatiotemporal characteristics of productivity in Inner Mongolia and its response to climate factors. Sci. Total Environ. 775, 145644. https://doi.org/10.1016/j.scitotenv.2021.145644.
Crossref Google Scholar
 

Hartley, M.J., 2002. Rationale and methods for conserving biodiversity in plantation forests. For. Ecol. Manag. 155, 81–95. https://doi.org/10.1016/s0378-1127(01)00549-7.
Crossref Google Scholar
 

He, L.M., Chen, J.M., Pan, Y.D., Birdsey, R., Kattge, J., 2012. Relationships between net primary productivity and forest stand age in U.S. forests. Global Biogeochem. Cycles 26, GB3009. https://doi.org/10.1029/2010gb003942.
Crossref Google Scholar
 

Houghton, R.A., Hall, F., Goetz, S.J., 2009. Importance of biomass in the global carbon cycle. J. Geophys. Res-Biogeo. 114, G00E03. https://doi.org/10.1029/2009jg000935.
Crossref Google Scholar
 

Hua, F.Y., Bruijnzeel, L.A., Meli, P., Martin, P.A., Zhang, J., Nakagawa, S., Miao, X.R., Wang, W.Y., McEvoy, C., Peña-Arancibia, J.L., Brancalion, P.H.S., Smith, P., Edwards, D.P., Balmford, A., 2022. The biodiversity and ecosystem service contributions and trade-offs of forest restoration approaches. Science 376, 839–844. https://doi.org/10.1126/science.abl4649.
Crossref Google Scholar
 

Huang, Y., Sun, W.J., Qin, Z.C., Zhang, W., Yu, Y.Q., Li, T.T., Zhang, Q., Wang, G.C., Yu, L.F., Wang, Y.J., Ding, F., Zhang, P., 2022. The role of China's terrestrial carbon sequestration 2010-2060 in offsetting energy-related CO2 emissions. Natl. Sci. Rev. 9, nwac057. https://doi.org/10.1093/nsr/nwac057.
Crossref Google Scholar
 

Jackson, R.B., Jobbágy, E.G., Avissar, R., Roy, S.B., Barrett, D.J., Cook, C.W., Farley, K.A., le Maitre, D.C., McCarl, B.A., Murray, B.C., 2005. Trading water for carbon with biological sequestration. Science 310, 1944–1947. https://doi.org/10.1126/science.1119282.
Crossref Google Scholar
 

Kalliokoski, T., Bäck, J., Boy, M., Kulmala, M., Kuusinen, N., Mäkelä, A., Minkkinen, K., Minunno, F., Paasonen, P., Peltoniemi, M., Taipale, D., Valsta, L., Vanhatalo, A., Zhou, L.X., Zhou, P.T., Berninger, F., 2020. Mitigation impact of different harvest scenarios of Finnish forests that account for albedo, aerosols, and trade-offs of carbon sequestration and avoided emissions. Front. For. Glob. Change 3, 562044. https://doi.org/10.3389/ffgc.2020.562044.
Crossref Google Scholar
 

Keenan, R.J., 2015. Climate change impacts and adaptation in forest management: a review. Ann. For. Sci. 72, 145–167. https://doi.org/10.1007/s13595-014-0446-5.
Crossref Google Scholar
 

Kelly, A.E., Goulden, M.L., 2008. Rapid shifts in plant distribution with recent climate change. Proc. Natl. Acad. Sci. USA 105, 11823–11826. https://doi.org/10.1073/pnas.0802891105.
Crossref Google Scholar
 

Kennedy, R.E., Yang, Z.G., Cohen, W.B., 2010. Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr - temporal segmentation algorithms. Remote Sens. Environ. 114, 2897–2910. https://doi.org/10.1016/j.rse.2010.07.008.
Crossref Google Scholar
 

Kennedy, R.E., Yang, Z.Q., Gorelick, N., Braaten, J., Cavalcante, L., Cohen, W.B., Healey, S., 2018. Implementation of the LandTrendr algorithm on Google earth engine. Rem. Sens. 10, 691. https://doi.org/10.3390/rs10050691.
Crossref Google Scholar
 

Lennox, G.D., Gardner, T.A., Thomson, J.R., Ferreira, J., Berenguer, E., Lees, A.C., Mac Nally, R., Aragao, L.E.O.C., Ferraz, S.F.B., Louzada, J., Moura, N.G., Oliveira, V.H.F., Pardini, R., Solar, R.R.C., Vaz-de Mello, F.Z., Vieira, I.C.G., Barlow, J., 2018. Second rate or a second chance? Assessing biomass and biodiversity recovery in regenerating Amazonian forests. Global Change Biol. 24, 5680–5694. https://doi.org/10.1111/gcb.14443.
Crossref Google Scholar
 

Li, C.C., Wang, J., Hu, L.Y., Yu, L., Clinton, N., Huang, H.B., Yang, J., Gong, P., 2014. A circa 2010 thirty meter resolution forest map for China. Rem. Sens. 6, 5325–5343. https://doi.org/10.3390/rs6065325.
Crossref Google Scholar
 

Li, P., Shang, R., Chen, J.M., Xu, M., Lin, X., Yu, G., He, N., Xu, L., 2024. Evaluation of five models for constructing forest NPP-age relationships in China based on 3121 field survey samples. Biogeosciences 21, 625–639. https://doi.org/10.5194/bg-21-625-2024.
Crossref Google Scholar
 

Li, T., Li, M.Y., Ren, F., Tian, L., 2022. Estimation and spatio-temporal change analysis of NPP in subtropical forests: a case study of Shaoguan, Guangdong, China. Rem. Sens. 14, 2541. https://doi.org/10.3390/rs14112541.
Crossref Google Scholar
 

Liang, S., Zhao, X., Yuan, W., Liu, S., Cheng, X., Xiao, Z., Zhang, X.T., Liu, Q., Cheng, J., Tang, H.R., 2013. A long-term Global Land Surface Satellite (GLASS) dataset for environmental studies. Int. J. Digit. Earth 5, 5–33. https://doi.org/10.1080/17538947.2013.805262.
Crossref Google Scholar
 

Liang, S.L., Cheng, J., Jia, K., Jiang, B., Liu, Q., Xiao, Z.Q., Yao, Y.J., Yuan, W.P., Zhang, X.T., Zhao, X., Zhou, J., 2021a. The global land surface satellite (GLASS) product suite. Bull. Am. Meteorol. Soc. 102, E323–E337. https://doi.org/10.1175/bams-d-18-0341.1.
Crossref Google Scholar
 

Liang, X., Guan, Q.F., Clarke, K.C., Liu, S.S., Wang, B.Y., Yao, Y., 2021b. Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: a case study in Wuhan, China. Comput. Environ. Urban 85, 101569. https://doi.org/10.1016/j.compenvurbsys.2020.101569.
Crossref Google Scholar
 

Liu, C.L.C., Kuchma, O., Krutovsky, K.V., 2018. Mixed-species versus monocultures in plantation forestry: development, benefits, ecosystem services and perspectives for the future. Glob. Ecol. Conserv. 15, e00419. https://doi.org/10.1016/j.gecco.2018.e00419.
Crossref Google Scholar
 

Liu, Z., Deng, Z., He, G., Wang, H.L., Zhang, X., Lin, J., Qi, Y., Liang, X., 2022. Challenges and opportunities for carbon neutrality in China. Nat. Rev. Earth Environ. 3, 141–155. https://doi.org/10.1038/s43017-021-00244-x.
Crossref Google Scholar
 

Lu, F., Hu, H.F., Sun, W.J., Zhu, J.J., Liu, G.B., Zhou, W.M., et al., 2018. Effects of national ecological restoration projects on carbon sequestration in China from 2001 to 2010. Proc. Natl. Acad. Sci. USA 115, 4039–4044. https://doi.org/10.1073/pnas.1700294115.
Crossref Google Scholar
 

Lu, N., Tian, H.Q., Fu, B.J., Yu, H.Q., Piao, S.L., Chen, S.Y., Zhang, Q.F., Shi, P.L., Liu, X.P., Wu, X., Zhang, L., Wei, X.H., Dai, L.M., Zhang, K.R., Sun, Y.R., Xue, S., Zhang, W.J., Xiong, D.P., Deng, L., Liu, B.J., Zhou, L., Zhang, C., Zheng, X., Cao, J.S., Huang, Y., He, N.P., Zhou, G.Y., Bai, Y.F., Xie, Z.Q., Tang, Z.Y., Wu, B.F., Fang, J.Y., Liu, G.H., Yu, G.R., 2022. Biophysical and economic constraints on China's natural climate solutions. Nat. Clim. Change 12, 847–853. https://doi.org/10.1038/s41558-022-01432-3.
Crossref Google Scholar
 

Lucier, A., Ayres, M., Karnosky, D., Thompson, I., Loehle, C., Percy, K., Sohngen, B., 2009. Forest responses and vulnerabilities to recent climate change. IUFRO World Series 22, 29–52.
Google Scholar
 

Luyssaert, S., Schulze, E.D., Börner, A., Knohl, A., Hessenmöller, D., Law, B.E., Ciais, P., Grace, J., 2008. Old-growth forests as global carbon sinks. Nature 455, 213–215. https://doi.org/10.1038/nature07276.
Crossref Google Scholar
 

Mallapaty, S., 2020. How China could be carbon neutral by mid-century. Nature 586, 482–483. https://doi.org/10.1038/d41586-020-02927-9.
Crossref Google Scholar
 

Masek, J.G., Vermote, E.F., Saleous, N.E., Wolfe, R., Hall, F.G., Huemmrich, K.F., Gao, F., Kutler, J., Lim, T.K., 2006. A Landsat surface reflectance dataset for North America, 1990-2000. IEEE Geosci. Remote S. 3, 68–72. https://doi.org/10.1109/lgrs.2005.857030.
Crossref Google Scholar
 

Moghaddam, E.R., 2014. Growth, development and yield in pure and mixed forest stands. Int. J. Adv. Biol. Biomed. Res. 2, 2725–2730.
Google Scholar
 

Molotoks, A., Stehfest, E., Doelman, J., Albanito, F., Fitton, N., Dawson, T.P., Smith, P., 2018. Global projections of future cropland expansion to 2050 and direct impacts on biodiversity and carbon storage. Global Change Biol. 24, 5895–5908. https://doi.org/10.1111/gcb.14459.
Crossref Google Scholar
 

Munsi, M., Areendran, G., Joshi, P.K., 2012. Modeling spatio-temporal change patterns of forest cover: a case study from the Himalayan foothills (India). Reg. Environ. Change 12, 619–632. https://doi.org/10.1007/s10113-011-0272-3.
Crossref Google Scholar
 
NASA, J.P.L., 2020. NASADEM Merged DEM Global 1 arc second V001. NASA EOSDIS Land Processes Distributed Active Archive Center.
 

Nguyen, H., Firn, J., Lamb, D., Herbohn, J., 2014. Wood density: a tool to find complementary species for the design of mixed species plantations. For. Ecol. Manag. 334, 106–113. https://doi.org/10.1016/j.foreco.2014.08.022.
Crossref Google Scholar
 

Pan, Y.D., Birdsey, R.A., Fang, J.Y., Houghton, R., Kauppi, P.E., Kurz, W.A., Phillips, O.L., Shvidenko, A., Lewis, S.L., Canadell, J.G., Ciais, P., Jackson, R.B., Pacala, S.W., McGuire, A.D., Piao, S.L., Rautiainen, A., Sitch, S., Hayes, D., 2011. A large and persistent carbon sink in the world's forests. Science 333, 988–993. https://doi.org/10.1126/science.1201609.
Crossref Google Scholar
 

Payne, N.J., Cameron, D.A., Leblanc, J.D., Morrison, I.K., 2019. Carbon storage and net primary productivity in Canadian boreal mixedwood stands. J. For. Res. 30, 1667–1678. https://doi.org/10.1007/s11676-019-00886-0.
Crossref Google Scholar
 

Peng, B., Zhou, Z., Cai, W., Li, M., Xu, L., He, N., 2023. Maximum potential of vegetation carbon sink in Chinese forests. Sci. Total Environ. 905, 167325. https://doi.org/10.1016/j.scitotenv.2023.167325.
Crossref Google Scholar
 

Peñuelas, J., Ciais, P., Canadel, l J.G., Janssens, I.A., Fernández-Martínez, M., Carnicer, J., Obersteiner, M., Piao, S.L., Vautard, R., Sardans, J., 2017. Shifting from a fertilization-dominated to a warming-dominated period. Nat. Ecol. Evol. 1, 1438–1445. https://doi.org/10.1038/s41559-017-0274-8.
Crossref Google Scholar
 

Piao, S.L., Friedlingstein, P., Ciais, P., Viovy, N., Demarty, J., 2007. Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades. Global Biogeochem. Cycles 21, GB002888. https://doi.org/10.1029/2006gb002888.
Crossref Google Scholar
 

Piao, S.L., He, Y., Wang, X.H., Chen, F.H., 2022a. Estimation of China's terrestrial ecosystem carbon sink: methods, progress and prospects. Sci. China Earth Sci. 65, 641–651. https://doi.org/10.1007/s11430-021-9892-6.
Crossref Google Scholar
 

Piao, S.L., Yue, C., Ding, J.Z., Guo, Z.T., 2022b. Perspectives on the role of terrestrial ecosystems in the 'carbon neutrality' strategy. Sci. China Earth Sci. 65, 1178–1186. https://doi.org/10.1007/s11430-022-9926-6.
Crossref Google Scholar
 

Pilli, R., Grassi, G., Kurz, W.A., Fiorese, G., Cescatti, A., 2017. The European forest sector: past and future carbon budget and fluxes under different management scenarios. Biogeosciences 14, 2387–2405. https://doi.org/10.5194/bg-14-2387-2017.
Crossref Google Scholar
 

Potapov, P., Li, X.Y., Hernandez-Serna, A., Tyukavina, A., Hansen, M.C., Kommareddy, A., Pickens, A., Turubanova, S., Tang, H., Silva, C.E., Armston, J., Dubayah, R., Blair, J.B., Hofton, M., 2021. Mapping global forest canopy height through integration of GEDI and Landsat data. Remote Sens. Environ. 253, 112165. https://doi.org/10.1016/j.rse.2020.112165.
Crossref Google Scholar
 

Pretzsch, H., Schütze, G., 2016. Effect of tree species mixing on the size structure, density, and yield of forest stands. Eur. J. For. Res. 135, 1–22. https://doi.org/10.1007/s10342-015-0913-z.
Crossref Google Scholar
 

Reichstein, M., Bahn, M., Ciais, P., Frank, D., Mahecha, M.D., Seneviratne, S.I., Zscheischler, J., Beer, C., Buchmann, N., Frank, D.C., Papale, D., Rammig, A., Smith, P., Thonicke, K., van der Velde, M., Vicca, S., Walz, A., Wattenbach, M., 2013. Climate extremes and the carbon cycle. Nature 500, 287–295. https://doi.org/10.1038/nature12350.
Crossref Google Scholar
 

Roy, D.P., Kovalskyy, V., Zhang, H.K., Vermote, E.F., Yan, L., Kumar, S.S., Egorov, A., 2016. Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity. Remote Sens. Environ. 185, 57–70. https://doi.org/10.1016/j.rse.2015.12.024.
Crossref Google Scholar
 

Ryan, M.G., Binkley, D., Fownes, J.H., 1997. Age-related decline in forest productivity: pattern and process. Adv. Ecol. Res. 27, 213–262. https://doi.org/10.1016/s0065-2504(08)60009-4.
Crossref Google Scholar
 

Shang, R., Chen, J.M., Xu, M.Z., Lin, X.D., Li, P., Yu, G.R., He, N.P., Xu, L., Gong, P., Liu, L.Y., Liu, H., Jiao, W.Z., 2023. China's current forest age structure will lead to weakened carbon sinks in the near future. Innovation 4, 100515. https://doi.org/10.1016/j.xinn.2023.100515.
Crossref Google Scholar
 

Tang, J.W., Luyssaert, S., Richardson, A.D., Kutsch, W., Janssens, I.A., 2014. Steeper declines in forest photosynthesis than respiration explain age-driven decreases in forest growth. Proc. Natl. Acad. Sci. USA 111, 8856–8860. https://doi.org/10.1073/pnas.1320761111.
Crossref Google Scholar
 

Tang, X.L., Zhao, X., Bai, Y.F., Tang, Z.Y., Wang, W.T., Zhao, Y.C., Wan, H.W., Xie, Z.Q., Shi, X.Z., Wu, B.F., Wang, G.X., Yan, J.H., Ma, K.P., Du, S., Li, S.G., Han, S.J., Ma, Y.X., Hu, H.F., He, N.P., Yang, Y.H., Han, W.X., He, H.L., Yu, G.R., Fang, J.Y., Zhou, G.Y., 2018. Carbon pools in China's terrestrial ecosystems: new estimates based on an intensive field survey. Proc. Natl. Acad. Sci. USA 115, 4021–4026. https://doi.org/10.1073/pnas.1700291115.
Crossref Google Scholar
 

Tao, Y., Tian, L., Wang, C., Dai, W., 2023. Dynamic simulation of land use and land cover and its effect on carbon storage in the Nanjing etropolitan circle under different development scenarios. Front. Ecol. Evol. 11, 1102015. https://doi.org/10.3389/fevo.2023.1102015.
Crossref Google Scholar
 

Tian, L., Liao, L.T., Tao, Y., Wu, X.C., Li, M.Y., 2023. Forest age mapping using landsat time-series stacks data based on forest disturbance and empirical relationships between age and height. Rem. Sens. 15, 2862. https://doi.org/10.3390/rs15112862.
Crossref Google Scholar
 

Tian, L., Tao, Y., Fu, W.X., Li, T., Ren, F., Li, M.Y., 2022. Dynamic simulation of land use/cover change and assessment of forest ecosystem carbon storage under climate change scenarios in Guangdong Province, China. Rem. Sens. 14, 2330. https://doi.org/10.3390/rs14102330.
Crossref Google Scholar
 

Tong, X.W., Brandt, M., Yue, Y.M., Ciais, P., Jepsen, M.R., Penuelas, J., Wigneron, J.P., Xiao, X.M., Song, X.P., Horion, S., Rasmussen, K., Saatchi, S., Fan, L., Wang, K.L., Zhang, B., Chen, Z.C., Wang, Y.H., Li, X.J., Fensholt, R., 2020. Forest management in southern China generates short term extensive carbon sequestration. Nat. Commun. 11. https://doi.org/10.1038/s41467-019-13798-8.
Crossref Google Scholar
 

van der Sande, M.T., Powers, J.S., Kuyper, T.W., Norden, N., Salgado-Negret, B., de Almeida, J.S., Bongers, F., Delgado, D., Dent, D.H., Derroire, G., Santo, M.M.D., Dupuy, J.M., Fernandes, G.W., Finegan, B., Gavito, M.E., Hernández-Stefanoni, J.L., Jakovac, C.C., Jones, I.L., Veloso, M.D.M., Meave, J.A., Mora, F., Muñoz, R., Pérez-Cárdenas, N., Piotto, D., Alvarez-Dávila, E., Caceres-Siani, Y., Dalban-Pilon, C., Dourdain, A., Du, D.V., Villalobos, D.G., Nunes, Y.R.F., Sanchez-Azofeifa, A., Poorter, L., 2023. Soil resistance and recovery during neotropical forest succession. Philos. T. R. Soc. B. 378, 20210074. https://doi.org/10.1098/rstb.2021.0074.
Crossref Google Scholar
 

Veldman, J.W., Overbeck, G.E., Negreiros, D., Mahy, G., Le Stradic, S., Fernandes, G.W., Durigan, G., Buisson, E., Putz, F.E., Bond, W.J., 2015. Where tree planting and forest expansion are bad for biodiversity and ecosystem services. Bioscience 65, 1011–1018. https://doi.org/10.1093/biosci/biv118.
Crossref Google Scholar
 

Vermote, E., Justice, C., Claverie, M., Franch, B., 2016. Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sens. Environ. 185, 46–56. https://doi.org/10.1016/j.rse.2016.04.008.
Crossref Google Scholar
 

Volkova, L., Roxburgh, S.H., Weston, C.J., Benyon, R.G., Sullivan, A.L., Polglase, P.J., 2018. Importance of disturbance history on net primary productivity in the world's most productive forests and implications for the global carbon cycle. Global Change Biol. 24, 4293–4303. https://doi.org/10.1111/gcb.14309.
Crossref Google Scholar
 

Wang, B., Huang, J.Y., Yang, X.S., Zhang, B.A., Liu, M.C., 2010. Estimation of biomass, net primary production and net ecosystem production of China's forests based on the 1999-2003 National Forest Inventory. Scand. J. For. Res. 25, 544–553. https://doi.org/10.1080/02827581.2010.524891.
Crossref Google Scholar
 

Wang, J.L., Li, Q.K., Fu, X.L., Dai, X.Q., Kou, L., Xu, M.J., Chen, S.F., Chen, F.S., Wang, H.M., 2019. Mechanisms driving ecosystem carbon sequestration in a Chinese fir plantation: nitrogen versus phosphorus fertilization. Eur. J. For. Res. 138, 863–873. https://doi.org/10.1007/s10342-019-01208-z.
Crossref Google Scholar
 

Wang, S.H., Zhang, Y.G., Ju, W.M., Chen, J.M., Ciais, P., Cescatti, A., Sardans, J., Janssens, I.A., Wu, M.S., Berry, J.A., Campbell, E., Fernández-Martínez, M., Alkama, R., Sftch, S., Friedlingstein, P., Smith, W.K., Yuan, W.P., He, W., Lombardozzi, D., Kautz, M., Zhu, D., Lienert, S., Kato, E., Poulter, B., Sanders, T.G.M., Krüger, I., Wang, R., Zeng, N., Tian, H.Q., Vuichard, N., Jain, A.K., Wiltshire, A., Haverd, V., Goll, D.S., Peñuelas, J., 2020. Recent global decline of CO2 fertilization effects on vegetation photosynthesis. Science 370, 1295–1300. https://doi.org/10.1126/science.abb7772.
Crossref Google Scholar
 

Wang, S.Q., Zhou, L., Chen, J.M., Ju, W.M., Feng, X.F., Wu, W.X., 2011. Relationships between net primary productivity and stand age for several forest types and their influence on China's carbon balance. J. Environ. Manag. 92, 1651–1662. https://doi.org/10.1016/j.jenvman.2011.01.024.
Crossref Google Scholar
 

Wulder, M.A., Roy, D.P., Radeloff, V.C., Loveland, T.R., Anderson, M.C., Johnson, D.M., Healey, S., Zhu, Z., Scambos, T.A., Pahlevan, N., Hansen, M., Gorelick, N., Crawford, C.J., Masek, J.G., Hermosilla, T., White, J.C., Belward, A.S., Schaaf, C., Woodcock, C.E., Huntington, J.L., Lymburner, L., Hostert, P., Gao, F., Lyapustin, A., Pekel, J.F., Strobl, P., Cook, B.D., 2022. Fifty years of Landsat science and impacts. Remote Sens. Environ. 280, 113195. https://doi.org/10.1016/j.rse.2022.113195.
Crossref Google Scholar
 

Xia, X.S., Ren, P.Y., Wang, X.H., Liu, D., Chen, X.Z., Dan, L., He, B., He, H.L., Ju, W.M., Liang, M.Q., Lu, X.J., Peng, J., Qin, Z.C., Xia, J.Z., Zheng, B., Wei, J., Yue, X., Yu, G.R., Piao, S.L., Yuan, W.P., 2024. The carbon budget of China: 1980-2021. Sci. Bull. 69, 114–124. https://doi.org/10.1016/j.scib.2023.11.016.
Crossref Google Scholar
 

Xiao, J.F., 2014. Satellite evidence for significant biophysical consequences of the "grain for green" program on the loess plateau in China. J. Geophys. Res-Biogeo. 119, 2261–2275. https://doi.org/10.1002/2014jg002820.
Crossref Google Scholar
 

Xu, H., Yue, C., Zhang, Y., Liu, D., Piao, S., 2023. Forestation at the right time with the right species can generate persistent carbon benefits in China. Proc. Natl. Acad. Sci. USA 120, e2304988120. https://doi.org/10.1073/pnas.2304988120.
Crossref 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, 3907–3925. https://doi.org/10.5194/essd-13-3907-2021.
Crossref Google Scholar
 

Yu, C., Wang, B., Liu, H., Yang, X.S., Xiu, Z.Z., 2014. Dynamic change of net production and mean net primary productivity of Chian's forests. For. Res. 27, 542–550. https://doi.org/10.13275/j.cnki.lykxyj.2014.04.016.
Crossref Google Scholar
 

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

Yu, Z., Dong, Y., Lu, C., Agathokleous, E., Zhang, L., Liu, S., Zhou, G.Y., 2023. China's forestation on marginal land was less efficient in carbon sequestration compared with non-marginal land. One Earth 11, 6. https://doi.org/10.1016/j.oneear.2023.11.006.
Crossref Google Scholar
 

Zhang, C.H., Ju, W.M., Chen, J.M., Li, D.Q., Wang, X.Q., Fan, W.Y., Li, M.S., Zan, M., 2014. Mapping forest stand age in China using remotely sensed forest height and observation data. J. Geophys. Res-Biogeo. 119, 1163–1179. https://doi.org/10.1002/2013jg002515.
Crossref Google Scholar
 

Zhang, S., Hao, X., Zhao, Z., Zhang, J., Fan, X., Li, X., 2023. Natural vegetation succession under climate change and the combined effects on net primary productivity. Earth's Future 11, e2023EF003903. https://doi.org/10.1029/2023EF003903.
Crossref Google Scholar
 

Zhang, Y., Yao, Y.T., Wang, X.H., Liu, Y.W., Piao, S.L., 2017. Mapping spatial distribution of forest age in China. Earth Space Sci. 4, 108–116. https://doi.org/10.1002/2016ea000177.
Crossref Google Scholar
 

Zhang, Y.C., Piao, S.L., Sun, Y., Rogers, B.M., Li, X.Y., Lian, X., Liu, Z.H., Chen, A.P., Peñuelas, J., 2022. Future reversal of warming-enhanced vegetation productivity in the Northern Hemisphere. Nat. Clim. Change 12, 581–586. https://doi.org/10.1038/s41558-022-01374-w.
Crossref Google Scholar
 

Zhu, K., Song, Y.L., Qin, C., 2019. Forest age improves understanding of the global carbon sink. Proc. Natl. Acad. Sci. USA 116, 3962–3964. https://doi.org/10.1073/pnas.1900797116.
Crossref Google Scholar
Forest Ecosystems
Volume 11 Issue 5,
October 2024
Article number: 100228
DOI: 10.1016/j.fecs.2024.100228
Cite this article:
Tian L, Tao Y, Joanna S, et al. How forest age impacts on net primary productivity: Insights from future multi-scenarios. Forest Ecosystems, 2024, 11(5): 100228. https://doi.org/10.1016/j.fecs.2024.100228

114

Views

3

Downloads

1

Crossref

2

Web of Science

2

Scopus

0

CSCD

Altmetrics
Received: 25 March 2024
Revised: 16 June 2024
Accepted: 17 July 2024
Published: 19 July 2024
© 2024 The Authors.

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