Integrating parameter uncertainty of a process-based model in assessments of climate change effects on forest productivity

Reyer, Christopher P. O.; Flechsig, Michael; Lasch-Born, Petra; Oijen, Marcel van

doi:10.1007/s10584-016-1694-1

Cited by 29 publications

(31 citation statements)

References 26 publications

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“…These outputs suggest that across the studied elevation gradients, species that are able to tolerate longer dry periods could increase their growth rate in contrast to less drought-tolerant species. It should be noted that our modelling framework not only is taking into account the uncertainty of vegetation processes (Reyer et al 2016) by including variation in growth and mortality, but also enables tree populations to shift their functional characteristics. This is particularly important in terms of adaptation to changing biotic and abiotic conditions.…”

Section: Discussionmentioning

confidence: 99%

Predicting species dominance shifts across elevation gradients in mountain forests in Greece under a warmer and drier climate

Fyllas¹,

Christopoulou²,

Galanidis

et al. 2017

Reg Environ Change

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The Mediterranean Basin is expected to face warmer and drier conditions in the future, following projected increases in temperature and declines in precipitation. The aim of this study is to explore how forests dominated by Abies borisii-regis, Abies cephalonica, Fagus sylvatica, Pinus nigra and Quercus frainetto will respond under such conditions. We combined an individual-based model (GREFOS), with a novel tree ring data set in order to constrain tree diameter growth and to account for inter-and intraspecific growth variability. We used wood density data to infer tree longevity, taking into account inter-and intraspecific variability. The model was applied at three 500-m-wide elevation gradients at Taygetos in Peloponnese, at Agrafa on Southern Pindos and at Valia Kalda on Northern Pindos in Greece. Simulations adequately represented species distribution and abundance across the elevation gradients under current climate. We subsequently used the model to estimate species and functional trait shifts under warmer and drier future conditions based on the IPCC A1B scenario. In all three sites, a retreat of less drought-tolerant species and an upward shift of more drought-tolerant species were simulated. These shifts were also associated with changes in two key functional traits, in particular maximum radial growth rate and wood density. Drought-tolerant species presented an increase in their average maximal growth and decrease in their average wood density, in contrast to less droughttolerant species.

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Section: Discussionmentioning

confidence: 99%

Predicting species dominance shifts across elevation gradients in mountain forests in Greece under a warmer and drier climate

Fyllas¹,

Christopoulou²,

Galanidis

et al. 2017

Reg Environ Change

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“…At the same time (6), this method avoids extreme and implausible results that can be obtained by improbable non-functional parameter combinations, which might emerge from a multiple parameterization and lead to overestimation of the model sensitivity. Such anomalous parameter combinations are difficult to reject a priori, or from expert judgment, especially under climate change scenarios (Wramneby et al 2008, Reyer et al 2016.…”

Section: Sensitivity Analysismentioning

confidence: 99%

The sensitivity of the forest carbon budget shifts across processes along with stand development and climate change

Collalti

Thornton

Cescatti

et al. 2019

Ecological Applications

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The future trajectory of atmospheric CO2 concentration depends on the development of the terrestrial carbon sink, which in turn is influenced by forest dynamics under changing environmental conditions. An in‐depth understanding of model sensitivities and uncertainties in non‐steady‐state conditions is necessary for reliable and robust projections of forest development and under scenarios of global warming and CO2 enrichment. Here, we systematically assessed if a biogeochemical process‐based model (3D‐CMCC‐CNR), which embeds similarities with many other vegetation models, applied in simulating net primary productivity (NPP) and standing woody biomass (SWB), maintained a consistent sensitivity to its 55 input parameters through time, during forest ageing and structuring as well as under climate change scenarios. Overall, the model applied at three contrasting European forests showed low sensitivity to the majority of its parameters. Interestingly, model sensitivity to parameters varied through the course of >100 yr of simulations. In particular, the model showed a large responsiveness to the allometric parameters used for initialize forest carbon and nitrogen pools early in forest simulation (i.e., for NPP up to ~37%, 256 g C·m−2·yr−1 and for SWB up to ~90%, 65 Mg C/ha, when compared to standard simulation), with this sensitivity decreasing sharply during forest development. At medium to longer time scales, and under climate change scenarios, the model became increasingly more sensitive to additional and/or different parameters controlling biomass accumulation and autotrophic respiration (i.e., for NPP up to ~30%, 167 g C·m−2·yr−1 and for SWB up to ~24%, 64 Mg C/ha, when compared to standard simulation). Interestingly, model outputs were shown to be more sensitive to parameters and processes controlling stand development rather than to climate change (i.e., warming and changes in atmospheric CO2 concentration) itself although model sensitivities were generally higher under climate change scenarios. Our results suggest the need for sensitivity and uncertainty analyses that cover multiple temporal scales along forest developmental stages to better assess the potential of future forests to act as a global terrestrial carbon sink.

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“…Yet, the development of DVMs is challenging since many processes are involved and interact across temporal and spatial scales (Bugmann 2001, Keane et al 2001, Price et al 2001). Thus, large uncertainties remain regarding the quantification of the ecological processes that govern forest dynamics, including both structural and parameter‐related uncertainties (Fortin et al 2009, Hlásny et al 2014, Horemans et al 2016, Reyer et al 2016, Neumann et al 2017, Huber et al 2018, Bugmann et al 2019). Not surprisingly, a plethora of model formulations are used in DVMs, but they are rarely benchmarked rigorously.…”

Section: Introductionmentioning

confidence: 99%

Capturing ecological processes in dynamic forest models: why there is no silver bullet to cope with complexity

2020

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Integrating parameter uncertainty of a process-based model in assessments of climate change effects on forest productivity

Cited by 29 publications

References 26 publications

Predicting species dominance shifts across elevation gradients in mountain forests in Greece under a warmer and drier climate

Predicting species dominance shifts across elevation gradients in mountain forests in Greece under a warmer and drier climate

The sensitivity of the forest carbon budget shifts across processes along with stand development and climate change

Capturing ecological processes in dynamic forest models: why there is no silver bullet to cope with complexity

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