The evolution, complexity and diversity of models of long‐term forest dynamics

Bugmann, Harald; Seidl, Rupert

doi:10.1111/1365-2745.13989

Cited by 41 publications

(28 citation statements)

References 131 publications

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“…2016; Davies-Barnard et al . 2020; Bugmann & Seidl 2022). With the advent of demographic representations in global vegetation and terrestrial carbon cycle models, there is a need for constraining alternative process representations with observations.…”

Section: Discussionmentioning

confidence: 99%

“…The G-B relationships and the STL shifts described here are relevant for the C cycle dynamics and the propagation of effects by increased photosynthesis and growth to the scale of a forest stand. How the processes are represented in vegetation models will determine the accuracy of predictions of forest responses under elevated CO2 and other environmental changes (Andresen et al 2016;Davies-Barnard et al 2020;Bugmann & Seidl 2022). With the advent of demographic representations in global vegetation and terrestrial carbon cycle models, there is a need for constraining alternative process representations with observations.…”

Section: Growth Enhancements Lead To Biomass Incrementsmentioning

confidence: 99%

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Tree growth enhancement drives a persistent biomass gain in unmanaged temperate forests

Marqués

Weng

Bugmann

et al. 2022

Preprint

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While enhanced tree growth over the last decades has been reported in forests across the globe, it remains unclear whether it drives persistent biomass increases of the stands, particularly in mature forests. Enhanced tree growth and stand-level biomass are often linked with a simultaneous increase in density-driven mortality and a reduction in tree longevity. Identifying empirical evidence regarding the balance between these processes is challenging due to the confounding effects of stand history, management, and environmental changes. Here, we investigate the link between growth and biomass via the shift in the negative relationship between average tree size and stand density (tree number). We find increasing stand density for a given tree size in unmanaged closed-canopy forests in Switzerland over the past six decades and a positive relationship between growth and stand density - qualitatively consistent with simulations by a mechanistic, cohort-resolving ecosystem model (LM3-PPA). Model simulations show that, in the absence of other disturbances, enhanced growth persistently increases biomass stocks despite simultaneous decreases in carbon residence time and tree longevity, independent of assumptions about the drivers of tree mortality. However, the magnitude of simulated changes critically depends on the shape of the mortality parameterizations. Our analyses reconcile reports of growth-induced reductions of tree longevity with model predictions of persistent biomass increases, and with our finding of a trend towards denser forests in response to growth - also in mature stands.

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Section: Discussionmentioning

confidence: 99%

Section: Growth Enhancements Lead To Biomass Incrementsmentioning

confidence: 99%

Tree growth enhancement drives a persistent biomass gain in unmanaged temperate forests

Marqués

Weng

Bugmann

et al. 2022

Preprint

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“…Forest models have a long tradition in analysing the impact of climate change on forest structure, species composition and biogeochemical cycles (e.g. [31][32][33][34]). As pointed out by Maréchaux et al [35], forest models are also able to conduct virtual experiments beyond empirical investigations [36][37][38], as well as to test assumptions about ecological processes [39,40].…”

Section: Limitationsmentioning

confidence: 99%

A new approach to derive productivity of tropical forests using radar remote sensing measurements

Henniger,

Huth,

Bohn

2023

R. Soc. open sci.

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Deriving gross & net primary productivity (GPP & NPP) and carbon turnover time of forests from remote sensing remains challenging. This study presents a novel approach to estimate forest productivity by combining radar remote sensing measurements, machine learning and an individual-based forest model. In this study, we analyse the role of different spatial resolutions on predictions in the context of the Radar BIOMASS mission (by ESA). In our analysis, we use the forest gap model FORMIND in combination with a boosted regression tree (BRT) to explore how spatial biomass distributions can be used to predict GPP, NPP and carbon turnover time ( τ ) at different resolutions. We simulate different spatial biomass resolutions (4 ha, 1 ha and 0.04 ha) in combination with different vertical resolutions (20, 10 and 2 m). Additionally, we analysed the robustness of this approach and applied it to disturbed and mature forests. Disturbed forests have a strong influence on the predictions which leads to high correlations ( R 2 > 0.8) at the spatial scale of 4 ha and 1 ha. Increased vertical resolution leads generally to better predictions for productivity (GPP & NPP). Increasing spatial resolution leads to better predictions for mature forests and lower correlations for disturbed forests. Our results emphasize the value of the forthcoming BIOMASS satellite mission and highlight the potential of deriving estimates for forest productivity from information on forest structure. If applied to more and larger areas, the approach might ultimately contribute to a better understanding of forest ecosystems.

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“…Simulation modelling is a powerful tool to quantitatively assess potential future forest trajectories (Thrippleton et al, 2020). Process‐based models that assess the impacts of climate change have matured considerably over the past decades (Bugmann & Seidl, 2022), and are increasingly applied also in the context of restoration management (Kobayashi et al, 2022; Shackelford et al, 2021). One advantage of simulation modelling is that it allows the evaluation of active restoration strategies against the alternative strategy of passive restoration, quantifying long‐term trajectories of ecosystem development with and without restoration measures.…”

Section: Introductionmentioning

confidence: 99%

“…Process-based models that assess the impacts of climate change have matured considerably over the past decades (Bugmann & Seidl, 2022), and are increasingly applied also in the context of restoration management (Kobayashi et al, 2022;Shackelford et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Climate change accelerates ecosystem restoration in the mountain forests of Central Europe

Dollinger,

Rammer,

Seidl

2023

Journal of Applied Ecology

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Restoring degraded forest ecosystems is an important element in the ongoing challenge to sustain the integrity and functioning of the biosphere. However, the evaluation of restoration success is hampered by long lead times of management measures in forests. Moreover, forest change is accelerating also in the absence of management because of ongoing climate change. Yet, because a counterfactual is frequently missing, it remains unclear whether restoration measures are aided or impeded by climate change. Here, we analysed the pace and success of forest restoration under climate change, combining field data and simulation modelling. We focused on the management zone of Berchtesgaden National Park (BGNP), Germany, where restoration aims to restore homogeneous Norway spruce (Picea abies) forests to structurally diverse mixed mountain forests. We evaluated three alternative restoration strategies: Two active strategies focused on planting the currently underrepresented silver fir (Abies alba) and European beech (Fagus sylvatica) but differing in the creation of gap‐cuts, and a third passive restoration strategy without interventions. Strategies were simulated with the forest landscape model iLand from 2020 to 2100 under different climate scenarios (historic, RCP 2.6, 4.5, and 8.5). The forests of BGNP developed into structurally diverse and mixed forests under all evaluated management strategies, and differences between active and passive restoration were generally small. While restoration goals for forest structure were largely met by 2100, forest composition remained far from target in all strategies. Climate change aided restoration by significantly increasing the prevalence of silver fir and European beech (+104.2% to +258.6%). Field data on short‐term restoration effects were in line with simulated long‐term trajectories. Synthesis and applications: We here show that forest restoration efforts in Central European mountain forests will likely be accelerated by climate change. Nonetheless, the slow pace of restoration underscores the need for taking action. Our study highlights that active restoration measures such as tree planting can bring the system closer to restoration targets. However, it also demonstrates that passive restoration (no intervention) is a viable option for management, highlighting the need to evaluate restoration measures against the counterfactual of a no intervention strategy.

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The evolution, complexity and diversity of models of long‐term forest dynamics

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 41 publications

References 131 publications

Tree growth enhancement drives a persistent biomass gain in unmanaged temperate forests

Tree growth enhancement drives a persistent biomass gain in unmanaged temperate forests

A new approach to derive productivity of tropical forests using radar remote sensing measurements

Climate change accelerates ecosystem restoration in the mountain forests of Central Europe

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