Comparison of Two Models Estimating Water Use Efficiency Based on δ<sup>13</sup>C: A Case Study of Plant Species in Leidongping, Emei Mountains of China

Miao Chen; Shun Liu; Gexi Xu; Jian Chen; Zuomin Shi

doi:10.12356/j.2096-8884.2024-0003

Article Contents

Article Navigation > Terrestrial Ecosystem and Conservation > 2024 > Accepted Manuscript

Miao Chen, Shun Liu, Gexi Xu, Jian Chen, Zuomin Shi. Comparison of Two Models Estimating Water Use Efficiency Based on δ13C: A Case Study of Plant Species in Leidongping, Emei Mountains of China[J]. Terrestrial Ecosystem and Conservation. doi: 10.12356/j.2096-8884.2024-0003

Citation:

Miao Chen, Shun Liu, Gexi Xu, Jian Chen, Zuomin Shi. Comparison of Two Models Estimating Water Use Efficiency Based on δ¹³C: A Case Study of Plant Species in Leidongping, Emei Mountains of China[J]. Terrestrial Ecosystem and Conservation. doi: 10.12356/j.2096-8884.2024-0003

Citation:

PDF( 948 KB)

Comparison of Two Models Estimating Water Use Efficiency Based on δ¹³C: A Case Study of Plant Species in Leidongping, Emei Mountains of China

doi: 10.12356/j.2096-8884.2024-0003

Miao Chen^{1, 2
,},
Shun Liu^{1, 2},
Gexi Xu^{1, 2},
Jian Chen^{1, 2},
Zuomin Shi^{1, 2, 3
,
,}

1.
Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
2.
Sichuan Miyaluo Forest Ecosystem National Observation and Research Station, Lixian County 623100, China
3.
Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China

Received Date: 2024-01-10
Accepted Date: 2024-04-30

Abstract

Abstract

Objective The study of differences between two models estimating intrinsic water use efficiency (iWUE) based on stable carbon isotope values (δ¹³C), considering leaf mesophyll conductance (g_m) or not, contributes to a better understanding of the impact of g_m on plant iWUE. Method In this study, we used different plant growth forms in the coniferous broadleaved mixed forest at Leidongping of Emei Mountains. By measuring the δ¹³C of leaves, we compared the difference in the calculated iWUE (iWUE_difference) between the early used iWUE model (iWUE_sim model, assuming g_m as infinity) and the newly proposed iWUE model with g_m effect (iWUE_mes model), and to detect whether this difference varies with plant growth forms. Result The results showed that the average iWUE_sim was 42.23±1.33 μmol·mol⁻¹, which was significantly higher than the average of iWUE_sem (28.10±0.65 μmol·mol⁻¹), with an overestimation ratio of 3.64%～72.11% (average of 49.58±1.30%). All the iWUE_sim of different growth forms of plants were significantly higher than iWUE_sem. The overestimation ratio was 3.64%～48.00% (average of 29.20±5.16%) for herbs, 13.68%～67.73% (average of 48.44±1.83%) for shrubs, and 32.04%～72.11% (average of 54.08±1.47%) for trees. In addition, the leaf functional traits also had important effects on the iWUE_difference. The leaf nitrogen content per unit area, the leaf mass per area were the main influencing factors for the variation of iWUE_difference, compared with the effects of leaf thickness, leaf dry matter content, and leaf nitrogen content per unit mass. Conclusion The assumption of g_m as infinity will lead to an overestimation of iWUE based on δ¹³C, and the effect of g_m should be considered in the future estimation of plant iWUE.
- intrinsic water-use efficiency,
- mesophyll conductance,
- stable carbon isotope,
- plant growth form,
- leaf nitrogen content per unit area,
- leaf mass per area

FullText(HTML)

References(58)

References

[1]	曹生奎, 冯起, 司建华, 等, 2009. 植物叶片水分利用效率研究综述[J]. 生态学报, 29(7): 3882-3892. doi: 10.3321/j.issn:1000-0933.2009.07.051
[2]	管增艳, 石松林, 金亚宁, 等, 2023. 四川峨眉山不同年龄冷杉径向生长对气候变化的响应差异[J]. 山地学报, 41(1): 56-67.
[3]	任书杰, 于贵瑞, 2011. 中国区域478种C₃植物叶片碳稳定性同位素组成与水分利用效率[J]. 植物生态学报, 35(2): 119-124.
[4]	史作民, 冯秋红, 程瑞梅, 等, 2010. 叶肉细胞导度研究进展[J]. 生态学报, 30(17): 4792-4803.
[5]	Adams III W W, Terashima I, 2018. The leaf: a platform for performing photosynthesis[M]. Heidelberg: Springer.
[6]	Adams M A, Buckley T N, Turnbull T L, 2019. Rainfall drives variation in rates of change in intrinsic water use efficiency of tropical forests[J]. Nature Communications, 10(1): 3661. doi: 10.1038/s41467-019-11679-8
[7]	Adams M A, Buckley T N, Turnbull T L, 2020. Diminishing CO₂-driven gains in water-use efficiency of global forests[J]. Nature Climate Change, 10(5): 466-471. doi: 10.1038/s41558-020-0747-7
[8]	Adams M A, Turnbull T L, Sprent J I, et al, 2016. Legumes are different: Leaf nitrogen, photosynthesis, and water use efficiency[J]. Proceedings of the National Academy of Sciences of the United States of America, 113: 4098-4103.
[9]	Belmecheri S, Lavergne A, 2020. Compiled records of atmospheric CO₂ concentrations and stable carbon isotopes to reconstruct climate and derive plant ecophysiological indices from tree rings[J]. Dendrochronologia, 63: 125748. doi: 10.1016/j.dendro.2020.125748
[10]	Bernacchi C J, Singsaas E L, Pimentel C, et al, 2001. Improved temperature response functions for models of Rubisco-limited photosynthesis[J]. Plant, Cell and Environment, 24: 253-259.
[11]	Brüggemann N, Gessler A, Kayler Z, et al, 2011. Carbon allocation and carbon isotope fluxes in the plant-soil-atmosphere continuum: a review[J]. Biogeosciences, 8: 3457-3489. doi: 10.5194/bg-8-3457-2011
[12]	Bussotti F, Pollastrini M, 2015. Evaluation of leaf features in forest trees: methods, techniques, obtainable information and limits[J]. Ecological Indicators, 52: 219-230. doi: 10.1016/j.ecolind.2014.12.010
[13]	Chen L, Flynn D F B, Zhang X, et al, 2014. Divergent patterns of foliar ¹³C and ¹⁵N in Quercus aquifolioides with an altitudinal transect on the Tibetan Plateau: an integrated study based on multiple key leaf functional traits[J]. Journal of Plant Ecology, 8: 303-312.
[14]	Chen M, Shi Z M, Liu S, et al, 2023. Leaf functional traits have more contributions than climate to the variations of leaf stable carbon isotope of different plant functional types on the eastern Qinghai–Tibetan Plateau[J]. Science of the Total Environment, 14: 974316.
[15]	Craig H, 1957. Isotopic standards for carbon and oxygen and correction factors for mass-spectrometric analysis of carbon dioxide[J]. Geochimica et Cosmochimica Acta, 12: 133-149. doi: 10.1016/0016-7037(57)90024-8
[16]	Cooley S S, Fisher J B, Goldsmith G R, 2022. Convergence in water use efficiency within plant functional types across contrasting climates[J]. Nature Plants, 8: 341-345. doi: 10.1038/s41477-022-01131-z
[17]	Cornelissen J H C, Lavorel S, Garnier E, et al, 2003. A handbook of protocols for standardised and easy measurement of plant functional traits worldwide[J]. Australian Journal of Botany, 51: 335-380. doi: 10.1071/BT02124
[18]	Cornwell W K, Wright I J, Turner J, et al, 2018. Climate and soils together regulate photosynthetic carbon isotope discrimination within C₃ plants worldwide[J]. Global Ecology and Biogeography, 27: 1056-1067. doi: 10.1111/geb.12764
[19]	Dawson T E, Mambelli S, Plamboeck A H, et al, 2002. Stable Isotopes in Plant Ecology[J]. Annual Review of Ecology and Systematics, 33: 507-559. doi: 10.1146/annurev.ecolsys.33.020602.095451
[20]	Diefendorf A F, Mueller K E, Wing S L, 2010. Global patterns in leaf ¹³C discrimination and implications for studies of past and future climate[J]. Proceedings of the National Academy of Sciences of the United States of America, 107: 5738-5743.
[21]	Evans J R, 1989. Photosynthesis and nitrogen relationships in leaves of C₃ plants[J]. Oecologia, 78: 9-19. doi: 10.1007/BF00377192
[22]	Farquhar G D, 1984. On the nature of carbon isotope discrimination in C₄ species[J]. Australian Journal of Plant Physiology, 10(2): 205-226.
[23]	Farquhar G D, Ehleringer J R, Hubick K T, 1989. Carbon Isotope Discrimination and Photosynthesis[J]. Annual Review of Plant Physiology and Plant Molecular Biology, 40: 503-537. doi: 10.1146/annurev.pp.40.060189.002443
[24]	Farquhar G D, Cernusak L A, 2012. Ternary effects on the gas exchange of isotopologues of carbon dioxide[J]. Plant, Cell & Environment, 35(7): 1221-1231.
[25]	Farquhar G D, O’Leary M, Berry J, 1982. On the Relationship between carbon isotope discrimination and the intercellular carbon dioxide concentration in leaves[J]. Australian Journal of Plant Physiology, 9: 121-137.
[26]	Flexas J M, Ribas-Carbo A, Diaz-Espejo J, 2008. Mesophyll conductance to CO₂: current knowledge and future prospects[J]. Plant Cell and Environment, 31: 602-621. doi: 10.1111/j.1365-3040.2007.01757.x
[27]	Frank D C, Poulter B, Saurer M, et al, 2015. Water-use efficiency and transpiration across European forests during the Anthropocene[J]. Nature Climate Change, 5(6): 579-583. doi: 10.1038/nclimate2614
[28]	Gago J, Carriquí M, Nadal M, et al, 2019. Photosynthesis Optimized across Land Plant Phylogeny[J]. Trends in Plant Science, 24: 947-958. doi: 10.1016/j.tplants.2019.07.002
[29]	Ghimire B, Riley W J, Koven C D, et al, 2017. A global trait-based approach to estimate leaf nitrogen functional allocation from observations[J]. Ecological Applications, 27: 1421-1434. doi: 10.1002/eap.1542
[30]	Gong X Y, Ma W T, Yu Y Z, et al, 2022. Overestimated gains in water-use efficiency by global forests[J]. Globle Change Biology, 28(16): 4923-4934. doi: 10.1111/gcb.16221
[31]	Hultine K R, Marshall J D, 2000. Altitude trends in conifer leaf morphology and stable carbon isotope composition[J]. Oecologia, 123: 32-40. doi: 10.1007/s004420050986
[32]	Knauer J, Zaehle S, De Kauwe M G, et al, 2019. Effects of mesophyll conductance on vegetation responses to elevated CO₂ concentrations in a land surface model[J]. Global Change Biology, 25: 1820-1838. doi: 10.1111/gcb.14604
[33]	Knight J D, Livingston N J, Kessel C, 1994. Carbon isotope discrimination and water-use efficiency of six crops grown under wet and dryland conditions[J]. Plant, Cell and Environment, 17(2): 173-179.
[34]	Kohn M J, 2010. Carbon isotope compositions of terrestrial C₃ plants as indicators of (paleo)ecology and (paleo)climate[J]. Proceedings of the National Academy of Sciences of the United States of America, 107: 19691-19695.
[35]	Lai J, Zou Y, Zhang S, et al, 2022. glmm. hp: an R package for computing individual effect of predictors in generalized linear mixed models[J]. Journal of Plant Ecology, 15: 1302-1307. doi: 10.1093/jpe/rtac096
[36]	Lin X, Wu B, Wang J, et al, 2023. Effects of geographical and climatic factors on the intrinsic water use efficiency of tropical plants: evidence from leaf ¹³C[J]. Plants, 12(4): 951. doi: 10.3390/plants12040951
[37]	Lin Y S, Medlyn B E, Duursma R A, et al, 2015. Optimal stomatal behaviour around the world[J]. Nature Climate Change, 5: 459-464. doi: 10.1038/nclimate2550
[38]	Liu C, He N, Zhang J, et al, 2017. Variation of stomatal traits from cold temperate to tropical forests and association with water use efficiency[J]. Functional Ecology, 32(1): 20-28.
[39]	Liu C, Li Y, Xu L, et al, 2019. Variation in leaf morphological, stomatal, and anatomical traits and their relationships in temperate and subtropical forests[J]. Scientific Reports, 9: 5803. doi: 10.1038/s41598-019-42335-2
[40]	Ma W T, Tcherkez G, Wang X M, et al, 2020. Accounting for mesophyll conductance substantially improves ¹³C‐based estimates of intrinsic water‐use efficiency[J]. New Phytologist, 229(3): 1326-1338.
[41]	Mathias J M, Hudiburg T W. 2022. isocalcR: An R package to streamline and standardize stable isotope calculations in ecological research[J]. Globle Change Biology, 28: 7428-7436.
[42]	Medlyn B E, De Kauwe M G, Lin Y S, et al, 2017. How do leaf and ecosystem measures of water-use efficiency compare[J]. New Phytologist, 216(3): 758-770. doi: 10.1111/nph.14626
[43]	Midolo G, De Frenne P, Hölzel N, et al, 2019. Global patterns of intraspecific leaf trait responses to elevation[J]. Global Change Biology, 25: 2485-2498. doi: 10.1111/gcb.14646
[44]	Moldover M R, Trusler J P M, Edwards T J, et al, 1988. Measurement of the universal gas constant R using a spherical acoustic resonator[J]. Physical Review Letters, 60(4): 249-252. doi: 10.1103/PhysRevLett.60.249
[45]	Murphy B P, Bowman D M J S, 2009. The carbon and nitrogen isotope composition of Australian grasses in relation to climate[J]. Functional Ecology, 23(6): 1040-1049. doi: 10.1111/j.1365-2435.2009.01576.x
[46]	Onoda Y, Hikosaka K, Hirose T. 2004. Allocation of nitrogen to cell walls decreases photosynthetic nitrogen-use efficiency[J]. Functional Ecology, 18: 419-425.
[47]	Onoda Y, Wright I J, Evans J R, et al, 2017. Physiological and structural tradeoffs underlying the leaf economics spectrum[J]. New Phytologist, 214: 1447-1463. doi: 10.1111/nph.14496
[48]	Peguero-Pina J J, Siso S, Flexas J, et al, 2017. Coordinated modifications in mesophyll conductance, photosynthetic potentials and leaf nitrogen contribute to explain the large variation in foliage net assimilation rates across Quercus ilex provenances[J]. Tree Physiology, 37: 1084-1094. doi: 10.1093/treephys/tpx057
[49]	Pérez-Harguindeguy N, Díaz S, Garnier E, et al, 2013. New handbook for standardised measurement of plant functional traits worldwide[J]. Australian Journal of Botany, 61: 167-234. doi: 10.1071/BT12225
[50]	Peri P L, Ladd B, Pepper D A, et al, 2012. Carbon (δ¹³C) and nitrogen (δ¹⁵N) stable isotope composition in plant and soil in Southern Patagonia’s native forests[J]. Global Change Biology, 18: 311-321. doi: 10.1111/j.1365-2486.2011.02494.x
[51]	Rao Z, Guo W, Cao J, et al, 2017. Relationship between the stable carbon isotopic composition of modern plants and surface soils and climate: a global review[J]. Earth-Science Reviews, 165: 110-119. doi: 10.1016/j.earscirev.2016.12.007
[52]	Stangl Z R, Tarvainen L, Wallin G, et al, 2019. Diurnal variation in mesophyll conductance and its influence on modelled water-use efficiency in a mature boreal Pinus sylvestris stand[J]. Photosynthesis Research, 141(1): 53-63. doi: 10.1007/s11120-019-00645-6
[53]	Stocker B, Wang H, Smith N, et al, 2019. P-model v1.0: an optimalitybased light use efficiency model for simulating ecosystem gross primary production[J]. Geoscientific Model Development Discussion, 37: 1-59.
[54]	Tang S, Lai Y, Tang X, et al, 2021. Multiple environmental factors regulate the large-scale patterns of plant water use efficiency and nitrogen availability across China’s forests[J]. Environmental Research Letters, 16(3): 34026. doi: 10.1088/1748-9326/abe3bb
[55]	Voelker S L, Brooks J R, Meinzer F C, et al, 2016. A dynamic leaf gas-exchange strategy is conserved in woody plants under changing ambient CO₂: evidence from carbon isotope discrimination in paleo and CO₂ enrichment studies[J]. Global Change Biology, 22(2): 889-902. doi: 10.1111/gcb.13102
[56]	Wang J, Wen X, 2022. Limiting resource and leaf functional traits jointly determine distribution patterns of leaf intrinsic water use efficiency along aridity gradients[J]. Frontiers in Plant Science, 13: 909603. doi: 10.3389/fpls.2022.909603
[57]	Wang X, Chen G, Wu M, et al, 2023. Differences in the patterns and mechanisms of leaf and ecosystem-scale water use efficiencies on the Qinghai-Tibet Plateau[J]. Catena, 222: 106874. doi: 10.1016/j.catena.2022.106874
[58]	Zhang Y J, Cao K F, Sack L, et al, 2015. Goldstein G. Extending the generality of leaf economic design principles in the cycads, an ancient lineage[J]. New Phytologist, 206: 817-829. doi: 10.1111/nph.13274