Page 272 - 《高原气象》2025年第6期
P. 272
高 原 气 象 44 卷
1680
(need to) care about canopy radiation schemes in DGVMs?Ca‐ restrial carbon cycle, future plant geography and climate-carbon
veats and potential impacts[J]. Biogeosciences, 11(7): 1873- cycle feedbacks using five Dynamic Global Vegetation Models
1897. DOI: 10. 5194/bg-11-1873-2014. (DGVMs)[J]. Global Change Biology, 14(9): 2015-2039.
Loreau M, Hector A, 2001. Partitioning selection and complementari‐ DOI: 10. 1111/j. 1365-2486. 2008. 01626. x.
ty in biodiversity experiments[J]. Nature, 412(6842): 72-76. Sitch S, Smith B, Prentice I C, et al, 2003. Evaluation of ecosystem dy‐
DOI: 10. 1038/35083573. namics, plant geography and terrestrial carbon cycling in the LPJ
Lotka A J, 1925. Elements of physical biology[M]. Baltimore: Wil‐ dynamic global vegetation model[J]. Global Change Biology, 9
liams and Wilkins. (2): 161-185. DOI: 10. 1046/j. 1365-2486. 2003. 00569. x.
Marschner P, Rengel Z, 2007. Nutrient cycling in terrestrial ecosys‐ Smith B, Prentice I C, Sykes M T, 2001a. Representation of vegeta‐
tems[M]. Berlin, Heidelberg: Springer Berlin Heidelberg. tion dynamics in the modelling of terrestrial ecosystems: compar‐
Martín B D, Anthoni P, Wårlind D, et al, 2022. LPJ-GUESS/ ing two contrasting approaches within European climate space
LSMv1. 0: a next-generation land surface model with high eco‐ [J]. Global Ecology and Biogeography, 10(6): 621-637. DOI:
logical realism[J]. Geoscientific Model Development, 15(17): 10. 1046/j. 1466-822X. 2001. t01-1-00256. x.
6709-6745. DOI: 10. 5194/gmd-15-6709-2022. Smith B, Samuelsson P, Wramneby A, et al, 2011. A model of the
Medvigy D, Wofsy S C, Munger J W, et al, 2009. Mechanistic scal‐ coupled dynamics of climate, vegetation and terrestrial ecosys‐
ing of ecosystem function and dynamics in space and time: Eco‐ tem biogeochemistry for regional applications[J]. Tellus A, 63
system Demography model version 2[J]. Journal of Geophysical (1): 87-106. DOI: 10. 1111/j. 1600-0870. 2010. 00477. x.
Research: Biogeosciences, 114(G1): 2008JG000812. DOI: 10. Smith B, Wårlind D, Arneth A, et al, 2014. Implications of incorpo‐
1029/2008JG000812. rating N cycling and N limitations on primary production in an in‐
Melton J R, Arora V K, 2016. Competition between plant functional dividual-based dynamic vegetation model[J]. Biogeosciences, 11
types in the Canadian Terrestrial Ecosystem Model (CTEM) (7): 2027-2054. DOI: 10. 5194/bg-11-2027-201410. 5194/
v. 2. 0[J]. Geoscientific Model Development, 9(1): 323-361. bgd-10-18613-2013.
DOI: 10. 5194/gmd-9-323-2016. Smith B, 2001b. LPJ-GUESS-an ecosystem modelling framework
Menaut J C, Gignoux J, Prado C, et al, 1990. Tree community dy‐ [R]. Sölvegatan: Department of Physical Geography and Ecosys‐
namics in a humid savanna of the cote-d’Ivoire: modelling the ef‐ tems Analysis: 1-19.
fects of fire and competition with grass and neighbours[J]. Jour‐ Song X, Zeng X D, Zhu J W, et al, 2016. Development of an estab‐
nal of Biogeography, 17(4/5): 471. DOI: 10. 2307/2845379. lishment scheme for a DGVM[J]. Advances in Atmospheric Sci‐
Moorcroft P R, Hurtt G C, Pacala S W, 2001. A method for scaling ences, 33(7): 829-840. DOI: 10. 1007/s00376-016-5284-y.
vegetation dynamics: the ecosystem demography model (ed)[J]. Strigul N, Pristinski D, Purves D, et al, 2008. Scaling from trees to
Ecological Monographs, 71(4): 557-586. DOI: 10. 1890/0012- forests: tractable macroscopic equations for forest dynamics[J].
9615(2001)071[0557: AMFSVD]2. 0. CO; 2. Ecological Monographs, 78(4): 523-545. DOI: 10. 1890/08-
Pacala S W, Canham C D, Saponara J, et al, 1996. Forest models de‐ 0082. 1.
fined by field measurements: estimation, error analysis and dy‐ Tilman D, Knops J, Wedin D, et al, 1997. The influence of functional
namics[J]. Ecological Monographs, 66(1): 1-43. DOI: 10. diversity and composition on ecosystem processes[J]. Science,
2307/2963479. 277(5330): 1300-1302. DOI: 10. 1126/science. 277. 5330. 1300.
Pielke R A, Sr, Avissar R, et al, 1998. Interactions between the atmo‐ Turkington R, Harper J L, 1979. The growth, distribution and neigh‐
sphere and terrestrial ecosystems: influence on weather and cli‐ bour relationships of trifolium repens in a permanent pasture: II.
mate[J]. Global Change Biology, 4(5): 461-475. DOI: 10. inter-and intra-specific contact[J]. The Journal of Ecology, 67
1046/j. 1365-2486. 1998. t01-1-00176. x. (1): 219. DOI: 10. 2307/2259346.
Prentice I C, Bondeau A, Cramer W, et al, 2007. Terrestrial ecosys‐ Weng E S, Farrior C E, Dybzinski R, et al, 2017. Predicting vegeta‐
tems in a changing world[M]. Berlin, Heidelberg: Springer Ber‐ tion type through physiological and environmental interactions
lin Heidelberg, 175-192. with leaf traits: evergreen and deciduous forests in an earth sys‐
Purves D, Pacala S, 2008. Predictive models of forest dynamics[J]. Sci‐ tem modeling framework[J]. Global Change Biology, 23(6):
ence, 320(5882): 1452-1453. DOI: 10. 1126/science. 1155359. 2482-2498. DOI: 10. 1111/gcb. 13542.
Sato H, Itoh A, Kohyama T, 2007. SEIB–DGVM: a new dynamic Zeng X D, 2010. Evaluating the dependence of vegetation on climate
global vegetation model using a spatially explicit individual-based in an improved dynamic global vegetation model[J]. Advances in
approach[J]. Ecological Modelling, 200(3-4): 279-307. DOI: Atmospheric Sciences, 27(5): 977-991. DOI: 10. 1007/s00376-
10. 1016/j. ecolmodel. 2006. 09. 006. 009-9186-0.
Scheiter S, Langan L, Higgins S I, 2013. Next-generation dynamic Zeng X D, Li F, Song X, 2014. Development of the IAP dynamic
global vegetation models: learning from community ecology[J]. global vegetation model[J]. Advances in Atmospheric Sciences,
New Phytologist, 198(3): 957-969. DOI: 10. 1111/nph. 12210. 31(3): 505-514. DOI: 10. 1007/s00376-013-3155-3.
Sitch S, Huntingford C, Gedney N, et al, 2008. Evaluation of the ter‐ Zhu D, Peng S S, Ciais P, et al, 2015. Improving the dynamics of

