Page 274 - 《高原气象》2025年第6期

高 原 气 象 44 卷
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ly shaping global vegetation distribution patterns. Clarifying the differences in how these mechanisms are repre‐
sented is critical for reducing uncertainty in ecosystem modeling and improving prediction accuracy. This review
systematically examines the representations of vegetation competition and coexistence in DGVMs， classifying
them into implicit and explicit approaches. Drawing on both model-based analyses and a comprehensive literature
survey， the study explore their potential impacts on simulations and compare the advantages and disadvantages
of each approach. Three key findings emerge： （1） the primary distinction between implicit and explicit represen‐
tations lies in assumptions about vegetation structure. Implicit approaches typically assume a homogeneous cano‐
py and treat plant functional types （PFTs） as independent and non-overlapping units. This simplification limits
the ability to simulate direct resource competition， relying instead on heuristic strategies such as competitive
ranking to adjust PFT cover fractions. Although computationally efficient， this approach often neglects the com‐
plexity of plant interactions. In contrast， explicit representations characterize three-dimensional vegetation struc‐
ture and its environmental interactions， enabling direct simulation of fine-scale competition processes and pro‐
ducing more dynamic outcomes that reflect continuous resource partitioning rather than fixed hierarchies.
（2） The representation of competition significantly affects community-level simulations. Three comparative ex‐
periments— models with versus without competition， implicit versus explicit schemes， and sensitivity tests of
implicit parameters— demonstrate that different formulations can cause substantial differences in spatial distribu‐
tion and carbon biomass， with discrepancies reaching up to 48. 6%. In implicit models based on the Lotka-Volter‐
ra framework， the form of the resource-density relationship plays a pivotal role in determining coexistence. Non‐
linear formulations better refelct plant "clustering" effects， promoting multispecies coexistence， while linear as‐
sumptions tend to eliminate non-dominant PFTs， resulting in unrealistic monocultures.（3） This review also high‐
lights the trade-offs between modeling approaches. Implicit schemes are widely used in large-scale Earth system
models due to their simplicity and computational efficiency， but may introduce systematic biases， such as overes‐
timating the productivity of shaded plants. Explicit approaches offer a more mechanistic representation of plant
competition and individual-level clustering， aligned more closely with ecological theory， yet are limited by high‐
er computational demands and uncertainty in parameterization. Finally， the review concludes by outlining sever‐
al future directions for DGVM development， including enhancing model intercomparison projects， constructing
benchmark datasets on vegetation structure and distribution， and gradually integrating explicit competition
schemes under controlled uncertainty. These efforts could deepen our understanding of plant community dynam‐
ics and carbon cycle responses under climate change， thereby supporting more robust scientific foundations for
climate change policy.
Key words： Dynamic Global Vegetation Model； vegetation competition and coexistence； model uncertainty；
canopy structure