Simulating tree growth response to climate change in structurally diverse oak and beech forests

Wergifosse, Louis de; André, Frédéric; Goosse, Hugues; Boczoń, Andrzej; Cecchini, Sébastien; Ciceu, Albert; Collalti, Alessio; Cools, Nathalie; D’Andrea, Ettore; Vos, Bruno De; Hamdi, Rafiq; Ingerslev, Morten; Knudsen, Martin; Kowalska, Anna; Leca, Ştefan; Matteucci, Giorgio; Nord‐Larsen, Thomas; Sanders, Tanja G. M.; Schmitz, Andreas; Termonia, Piet; Vanguelova, Elena; Schaeybroeck, Bert Van; Verstraeten, Arne; Vesterdal, Lars; Jonard, Mathieu

doi:10.1016/j.scitotenv.2021.150422

Cited by 28 publications

(18 citation statements)

References 117 publications

(132 reference statements)

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“…Although the response of vegetation NPP to climate change has become a hot topic in global change research, most of them focus on grassland or forest ecosystems (de Wergifosse et al., 2022; Machado‐Silva et al., 2021; Nanzad et al., 2021; Zarei et al., 2021). Until recently, there have been relatively few studies on the response of marsh vegetation NPP to climatic change (Hirota et al., 2007; Mao et al., 2015).…”

Section: Introductionmentioning

confidence: 99%

Asymmetric Impacts of Diurnal Warming on Vegetation Carbon Sequestration of Marshes in the Qinghai Tibet Plateau

Shen

Liu

Zhang

et al. 2022

Global Biogeochemical Cycles

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Wetlands are one of the three major ecosystems in the world. Wetlands account for only 4%-6% of the global area , but the wetland's carbon reserves account for 12%-24% of the total terrestrial carbon reserves in the world (Shukla et al., 2019). Marshes are the main type of wetland and marsh vegetation plays an important role in carbon sequestration in marsh ecosystems (Yuan & Yuan, 2017). Net primary productivity (NPP) is an important indicator of carbon sequestration capacity (Nayak et al., 2010;Pachavo & Murwira, 2014;Reyer et al., 2014) and is widely used to understand carbon storage in marsh ecosystems (Alongi, 2020;Mngadi et al., 2022;Zhang et al., 2014). Studies have shown that climate variation can change vegetation coverage,

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Section: Introductionmentioning

confidence: 99%

Asymmetric Impacts of Diurnal Warming on Vegetation Carbon Sequestration of Marshes in the Qinghai Tibet Plateau

Shen

Liu

Zhang

et al. 2022

Global Biogeochemical Cycles

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“…The documented age trend in site productivity is likely due to the effect of climate and environmental change, and has been observed for different species and biomes (di Filippo et al, 2010;Nunes et al, 2015;de Wergifosse et al, 2022). The influence of non-static factors, such as increasing nitrogen deposition and rising temperatures and CO 2 concentrations, has been recognized as the main cause of site productivity increases (Nunes et al, 2015;de Wergifosse et al, 2022). Site index is a good indicator of the effect of climate change on tree growth and site productivity (Socha et al, 2016;Pau et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

“…Thus, the development of country scale geocentric SI models for oak could partly close this knowledge gap and contribute to our understanding of the impact of multiple environmental factors on site productivity for this important forest-forming tree species. Reliable determination of site productivity is critical for effective forest management in changing climate conditions (Bontemps & Bouriaud, 2014;Sharma et al, 2015;Sharma & Parton, 2018de Wergifosse et al, 2022). Therefore, the study of factors affecting site productivity for oak stands is of great importance, both from practical and scientific points of view.…”

Section: Introductionmentioning

confidence: 99%

Drivers of site productivity for oak in Poland

Viet¹,

Tymińska-Czabańska²,

Socha³

2022

Dendrobiology

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The site index (SI) is the most commonly used and representative measure of the phytocentric approach; it evaluates the site productivity based on the stand height and age. In the case of mixed stands with complex structures, phytocentric methods are very limited, while in non-forest areas, they are not applicable. In situations where the applicability of phytocentric methods is limited, the site productivity is determined by geocentric methods. Geocentric methods allow direct modelling of site productivity, expressed by SI predicted from various environmental variables. The aim of this study was to develop a geocentric model for oak. Site productivity expressed by SI was described by the environmental variables and stand characteristics. To develop the SI model, we used the data from 2490 NFI plots with dominant oak species (Quercus sessilis and Quercus robur). A generalized additive model was used in modelling site productivity. We documented a significant relationship between SI and the environmental variables, age of stands and stand density. Furthermore, the site productivity for oak is shaped by climate factors, soil type, geology, and altitude. The model developed based on the geocentric method, explained 55.1% of the variation of SI

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“…Mechanistic models are often regarded as having a larger degree of uncertainty than empirical models -due to their larger number of parameters (Adams et al, 2013), but mechanistic models of vegetation dynamics can achieve good performance when calibrated for specific stands and parameter estimates are carefully chosen for target species (de Wergifosse et al, 2022;Forrester et al, 2021). In the case of mechanistic trait-enabled models, one can expect substantial biases with respect to the prediction forest dynamics because key parameters of demographic processes are unlikely to be matched by observable database traits.…”

Section: The Value Of Trait-enabled Models For the Projection Of Fore...mentioning

confidence: 99%

MEDFATE 2.8.1: A trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales

Cáceres

Molowny‐Horas

Cabon

et al. 2022

Preprint

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Abstract. 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 discard taxonomic identity, but this strategy ignores the phylogenetic signal of trait variation and cannot be employed when predictions for specific taxa are needed, 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 while adopting alternative 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 (v. 2.8.1), 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 data were used to obtain some empirical parameter estimates, a large proportion of physiological, morphological, and anatomical parameters were mapped 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 filled using imputation procedures based on trait coordination, taxonomic averages or both. The model properly simulated observed historical basal area changes, with a 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, estimation procedures 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 population-structured models for regional-level projections of forest function and dynamics.

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Simulating tree growth response to climate change in structurally diverse oak and beech forests

Cited by 28 publications

References 117 publications

Asymmetric Impacts of Diurnal Warming on Vegetation Carbon Sequestration of Marshes in the Qinghai Tibet Plateau

Asymmetric Impacts of Diurnal Warming on Vegetation Carbon Sequestration of Marshes in the Qinghai Tibet Plateau

Drivers of site productivity for oak in Poland

MEDFATE 2.8.1: A trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales

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