MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
<p>Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity, which requires moving away from broadly defined functional types. Different approaches have been adopted in the last years to incorporate a...
Main Authors: | , , , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2023-06-01
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Series: | Geoscientific Model Development |
Online Access: | https://gmd.copernicus.org/articles/16/3165/2023/gmd-16-3165-2023.pdf |
Summary: | <p>Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional
diversity, which requires moving away from broadly defined functional types. Different approaches have been adopted in the last years to incorporate
a trait-based perspective into modeling exercises. A common parametrization strategy involves using trait data to represent functional variation
between individuals while discarding taxonomic identity. However, this strategy ignores the phylogenetic signal of trait variation and cannot be
employed when predictions for specific taxa are needed, such as in applications to inform forest management planning. An alternative strategy
involves adapting the taxonomic resolution of model entities to that of the data source employed for large-scale initialization and estimating
functional parameters from available plant trait databases, adopting diverse solutions for missing data and non-observable parameters. Here we
report the advantages and limitations of this second strategy according to our experience in the development of MEDFATE (version 2.9.3), a novel
cohort-based and trait-enabled model of forest dynamics, for its application over a region in the western Mediterranean Basin. First, 217 taxonomic
entities were defined according to woody species codes of the Spanish National Forest Inventory. While forest inventory records were used to obtain
some empirical parameter estimates, a large proportion of physiological, morphological, and anatomical parameters were matched to measured plant
traits, with estimates extracted from multiple databases and averaged at the required taxonomic level. Estimates for non-observable key parameters
were obtained using meta-modeling and calibration exercises. Missing values were addressed using imputation procedures based on trait covariation,
taxonomic averages or both. The model properly simulated observed historical changes in basal area, with a<span id="page3166"/> performance similar to an empirical model
trained for the same region. While strong efforts are still required to parameterize trait-enabled models for multiple taxa, and to incorporate
intra-specific trait variability, estimation procedures such as those presented here can be progressively refined, transferred to other regions or
models and iterated following data source changes by employing automated workflows. We advocate for the adoption of trait-enabled and
population-structured models for regional-level projections of forest function and dynamics.</p> |
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ISSN: | 1991-959X 1991-9603 |