Progress in DGVMs: a comment on &amp;quot;Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis&amp;quot; by Verheijen et al. (2013)

Higgins, Steven I.; Langan, Liam; Scheiter, Simon

doi:10.5194/bg-11-4357-2014

Cited by 7 publications

(8 citation statements)

References 9 publications

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“…A recent forest carbon density map (Thurner et al, 2014) for Northern Hemisphere boreal and temperate forests (30-80 • N), derived from radar remote sensing of growing-stock volume (GSV), was used to evaluate modeled forest biomass. For soil carbon stocks, the simulated soil carbon density was compared with the Harmonized World Soil Database (HWSD; 0-1 m depth, FAO/IIASA/ISRIC/ISSCAS/JRC, 2012) and the Northern Circumpolar Soil Carbon Database (NCSCD; Hugelius et al, 2013). Since the model results for soil carbon are not fully comparable to NCSCD due to lack of peatland carbon accumulation and cryoturbation processes in ORC-HL, metrics were not applied to soil carbon for establishing a model score.…”

Section: Evaluation Data Setsmentioning

confidence: 99%

“…The spatial patterns of soil carbon density simulated by OLD and NEW (0-2 m depth) are shown in Fig. 11c, compared with those from HWSD (0-1 m depth; FAO/IIASA/ISRIC/ISSCAS/JRC, 2012) and NCSCD (0-1 m depth; Hugelius et al, 2013). Over the grid cells present in NCSCD, the total soil carbon is 285 Pg in HWSD, markedly lower than that in NCSCD (460 Pg C for the upper meter of soil), indicating large uncertainties in the empirical soil carbon data.…”

Section: Soil Carbonmentioning

confidence: 99%

“…For example, Verheijen et al (2013) conducted a variable trait simulation with the JSBACH DGVM for three leaf traits (specific leaf area, and the constants defining the maximum rate of photosynthesis, v cmax ,j max ), showing significant difference in predicted dominant PFTs compared with fixed trait simulation. Higgins et al (2014), however, pointed out the inherent limitations in Verheijen et al (2013) using a statistical method to parameterize plant trait diversity and proposed that the focus should not be on trait values, but rather on the tradeoffs between traits (Scheiter et al, 2013). In this study, we will use a fixed trait approach to describe the characteristics of each PFT in ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems;the PFTs are listed in Table 1).…”

Section: Introductionmentioning

confidence: 99%

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Improving the dynamics of Northern Hemisphere high-latitude vegetation in the ORCHIDEE ecosystem model

Zhu

Peng²,

Ciais³

et al. 2015

Geosci. Model Dev.

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International audienceProcesses that describe the distribution of vegetation and ecosystem succession after disturbance are an important component of dynamic global vegetation models (DGVMs). The vegetation dynamics module (ORC-VD) within the process-based ecosystem model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) has not been updated and evaluated since many years and is known to produce unrealistic results. This study presents a new parameterization of ORC-VD for mid-to high-latitude regions in the Northern Hemisphere, including processes that influence the existence, mortality and competition between tree functional types. A new set of metrics is also proposed to quantify the performance of ORC-VD, using up to five different data sets of satellite land cover, forest biomass from remote sensing and inventories, a data-driven estimate of gross primary productivity (GPP) and two gridded data sets of soil organic carbon content. The scoring of ORC-VD derived from these metrics integrates uncertainties in the observational data sets. This multi-data set evaluation framework is a generic method that could be applied to the evaluation of other DGVM models. The results of the original ORC-VD published in 2005 for mid-to high-latitudes and of the new parameterization are evaluated against the above-described data sets. Significant improvements were found in the model-ing of the distribution of tree functional types north of 40 • N. Three additional sensitivity runs were carried out to separate the impact of different processes or drivers on simulated vegetation distribution, including soil freezing which limits net primary production through soil moisture availability in the root zone, elevated CO 2 concentration since 1850, and the effects of frequency and severity of extreme cold events during the spin-up phase of the model

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Section: Evaluation Data Setsmentioning

confidence: 99%

Section: Soil Carbonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improving the dynamics of Northern Hemisphere high-latitude vegetation in the ORCHIDEE ecosystem model

Zhu

Peng²,

Ciais³

et al. 2015

Geosci. Model Dev.

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“…The drawbacks underlying the PFT approach have been recently recognized (Kleidon & Mooney, ; Lavorel & Garnier, ; Kleidon et al ., ; Lavorel et al ., ; Prentice et al ., ; Reich et al ., ; Thuiller et al ., ; Ordoñez et al ., ; Williams et al ., ; Harrison et al ., ; Quillet et al ., ; McMahon et al ., ; van Bodegom et al ., , ; Stoy et al ., ; Wullschleger et al ., ; Anderegg, ). The importance of representing plant trait diversity within models has been also highlighted using statistical tools (Pappas et al ., , for a detailed sensitivity analysis of a DGVM), or by embedding trait variability in vegetation models (Wang et al ., ), or ESMs (Verheijen et al ., , but see Higgins et al., ).…”

Section: Introductionmentioning

confidence: 99%

Modeling terrestrial carbon and water dynamics across climatic gradients: does plant trait diversity matter?

2015

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SummaryPlant trait diversity in many vegetation models is crudely represented using a discrete classification of a handful of 'plant types' (named plant functional types; PFTs). The parameterization of PFTs reflects mean properties of observed plant traits over broad categories ignoring most of the inter-and intraspecific plant trait variability.Taking advantage of a multivariate leaf-trait distribution (leaf economics spectrum), as well as documented plant drought strategies, we generate an ensemble of hypothetical species with coordinated attributes, rather than using few PFTs. The behavior of these proxy species is tested using a mechanistic ecohydrological model that translates plant traits into plant performance. Simulations are carried out for a range of climates representative of different elevations and wetness conditions in the European Alps. Using this framework we investigate the sensitivity of ecosystem response to plant trait diversity and compare it with the sensitivity to climate variability.Plant trait diversity leads to highly divergent vegetation carbon dynamics (fluxes and pools) and to a lesser extent water fluxes (transpiration). Abiotic variables, such as soil water content and evaporation, are only marginally affected.These results highlight the need for revising the representation of plant attributes in vegetation models. Probabilistic approaches, based on observed multivariate whole-plant trait distributions, provide a viable alternative.

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“…In most DGVMs, the traits for a given PFT are fixed, but Verheijen et al (2013) conducted a variable trait simulation with the JSBACH model for three leaf traits (Specific Leaf Area, and the constants defining the maximum rate of photosynthesis, v cmax , j max ) based on observed trait-climate relationships, emphasizing the need for climate-dependent and regional trait-variation modeling. Higgins et al (2014) pointed out the inherent limitations in Verheijen et al (2013) using a statistical method to parameterize plant trait diversity, and proposed that the focus should not be on trait values, but rather on the trade-offs between traits (Scheiter et al, 2013). In this study, we will use a fixed trait approach to describe the characteristics of each PFT in ORCHIDEE (the PFTs are listed in Table 1).…”

Section: Introductionmentioning

confidence: 99%

Improving the dynamics of northern vegetation in the ORCHIDEE ecosystem model

Zhu¹,

Peng²,

Ciais³

et al. 2015

Preprint

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Abstract. Processes that describe the distribution of vegetation and ecosystem succession after disturbance are an important component of dynamic global vegetation models (DGVMs). The vegetation dynamics module (ORC-VD) within the process-based ecosystem model ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) has not been updated and evaluated since many years and does not match the progress in modeling the rest of the physical and biogeochemical processes. Therefore, ORC-VD is known to produce unrealistic results. This study presents a new parameterization of ORC-VD for mid-to-high latitude regions in the Northern Hemisphere, including processes that influence the existence, mortality and competition between tree functional types. A new set of metrics is also proposed to quantify the performance of ORC-VD, using up to five different datasets of satellite land cover, forest biomass from remote sensing and inventories, a data-driven estimate of gross primary productivity (GPP) and two gridded datasets of soil organic carbon content. The scoring of ORC-VD derived from these metrics integrates uncertainties in the observational datasets. This multi-dataset evaluation framework is a generic method that could be applied to the evaluation of other DGVM models. The results of the original ORC-VD published in 2005 for mid-to-high latitudes and of the new parameterization are evaluated against the above-described datasets. Significant improvements were found in the modeling of the distribution of tree functional types north of 40° N. Three additional sensitivity runs were carried out to separate the impact of different processes or drivers on simulated vegetation distribution, including soil freezing which limits net primary production through soil moisture availability in the root zone, elevated CO2 concentration since 1850, and the return frequency of cold climate extremes causing tree mortality during the spin-up phase of the model.

show abstract

Progress in DGVMs: a comment on "Impacts of trait variation through observed trait–climate relationships on performance of an Earth system model: a conceptual analysis" by Verheijen et al. (2013)

Cited by 7 publications

References 9 publications

Improving the dynamics of Northern Hemisphere high-latitude vegetation in the ORCHIDEE ecosystem model

Improving the dynamics of Northern Hemisphere high-latitude vegetation in the ORCHIDEE ecosystem model

Modeling terrestrial carbon and water dynamics across climatic gradients: does plant trait diversity matter?

Improving the dynamics of northern vegetation in the ORCHIDEE ecosystem model

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