Biology subjects

Bugmann, H.

Publications and source records attributed to Bugmann, H..

5 recordsLinked to original sources

bioRxiv2026

Loss of competitive strength in European conifer species under climate change

Climate change is expected to alter species assemblages by affecting the outcome of competition between species. Investigating processes of competition remains challenging particularly in tree communities, as they unfold over extensive spatio-temporal scales. Here, we developed a deep-learning approach to leverage a novel database of 135 million simulated local-scale tree responses to climate across continental Europe to investigate changes in the competitiveness of nine major tree species under different scenarios of climate change. Specifically, we trained a Deep Neural Network on local process model projections to investigate climate change effects on indicators of competitive strength and species dominance. We found decreasing competitive strength for all investigated evergreen coniferous species across their distribution, while major deciduous broadleaved species such as Quercus robur and Fagus sylvatica increased in competitiveness. Changes in tree species competition with climate differed locally, but most investigated species lost competitive strength at their warm range edges. As a consequence of these changes, up to 19% of Europes forests could experience a change in the dominant tree species until the end of the 21st century. Our results suggest a profound climate-induced reassembly of Europes forests and identify areas that may require specific attention in forest policy and management.

ecology↗

bioRxiv2025

Predicting drought-induced tree mortality in Swiss beech forests hinges upon predisposing and inciting factors

The increase in the frequency and severity of drought-induced tree mortality in many European low-elevation forests poses considerable challenges to forest management and requires an understanding of its causes. We propose a novel framework for integrating the factors underlying drought-induced tree mortality in a dynamic vegetation model. We evaluate whether this framework accurately reproduces drought-related mortality in six mesic beech-dominated stands in 2018-2020, and over multiple years in a xeric Scots pine-dominated stand in Switzerland. Additionally, we investigate its behavior along a large climatic gradient in central Europe. We employ a three-step approach. First, we evaluate multiple drought indices for capturing tree growth responses to extreme drought. We find that in contrast to widespread indices such as SPI and SPEI, the ForClim drought index captures growth responses to drought intensity during summer, the growing period, and annually. Second, we assess in detail the capability of the ForClim soil moisture model to simulate soil water dynamics, comparing it to the mechanistic soil-vegetation-atmosphere model LWFBrook90. The ForClim soil moisture model adequately simulates soil water dynamics, particularly in extreme drought years. Third, based on Manions Decline Disease Theory, we develop a novel mortality sub-model that combines predisposing and inciting factors. Its integration in ForClim captures drought-induced mortality events in the mesic beech forests as well as the multi-year mortality at the xeric Scots pine-dominated stand. Along a climatic gradient in central Europe, the model provides good quantifications of Potential Natural Vegetation. The novel framework to capture drought-related tree mortality is simple yet produces accurate results. The underlying hypothesis regarding the factors leading to drought-induced tree mortality is promising but requires further tests for its generality.

ecology↗

bioRxiv2024

Management recommendations for Alpine protection forests: the importance of regeneration quality and initial stand composition

The protection of infrastructure against gravitational natural hazards is one of the most important ecosystem services (ES) of mountain forests in Alpine countries. For a continuous provision of this ES, forests need to have a high protective effect, e.g., high canopy cover and/or stem numbers, while being resistant to and resilient after disturbances by being well-structured and stable, having a species composition adapted to the local site conditions and sufficient regeneration, all on a relatively small spatial scale. While "natural" forests may fulfill these prerequisites without human intervention, management history and high levels of ungulate browsing have produced unsustainable stand structures in many protection forests that need to be improved by management. The general principles of protection forest management are well established, but there are no quantitative, science-based recommendations for management regimes, i.e., specific sequences of interventions, that ensure a continuous protective quality. Our goal was to derive such recommendations for different stand types across three elevational zones, from mixed forests of the upper montane to spruce forests of the subalpine zone. We used an updated version of the model ProForM to simulate stand development under different levels of ungulate browsing, testing a large number of management regimes that vary in the spatial aggregation of tree removal, the intensity and interval of the interventions. We investigated the influence of browsing pressure and management on the protective quality using Boosted Regression Trees and Beta regression. High levels of ungulate browsing had such a strong negative effect on the protective quality that it could not be improved through forest management. This underlines the need for maintaining ungulate densities in Alpine forests at levels that allow for the successful regeneration of all key tree species. In stands that are influenced less by browsing, the protective quality can be improved through management in many cases, with specific management recommendations differing mostly depending on the initial stand conditions and, to a lesser extent, on the elevational zone. Well-structured stands provide a high protective quality without management interventions during at least a century across all elevational zones. In young and in mature stands, we generally recommend management regimes with relatively long return intervals of 30 to 40 years and low intervention intensities of 10 to 20% basal area removal.

ecology↗

bioRxiv2022

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

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.

ecology↗

bioRxiv2020

Beyond forest succession: a gap model to study ecosystem functioning and tree community composition under climate change

Climate change impacts forest functioning and dynamics, and large uncertainties remain regarding the interactions between species composition, demographic processes, and environmental drivers. There are few robust tools available to link these processes, which precludes accurate projections and recommendations for long-term forest management. Forest gap-models present a balance between complexity and generality and are widely used in predictive forest ecology. However, their relevance to tackle questions about the links between species composition, climate and forest functioning is unclear. In this regard, demonstrating the ability of gap-models to predict the growth of forest stands at the annual time scale - representing a sensitive and integrated signal of tree functioning and mortality risk - appears as a fundamental step. In this study, we aimed at assessing the ability of a gap-model to accurately predict forest growth in the short-term and potential community composition in the long-term, across a wide range of species and environmental conditions. To do so, we present the gap-model ForCEEPS, calibrated using an original parameterization procedure for the main tree species in France. ForCEEPS was shown to satisfactorily predict forest annual growth (averaged over a few years) at the plot level from mountain to Mediterranean climates, regardless the species. Such an accuracy was not gained at the cost of losing precision for long-term predictions, as the model showed a strong ability to predict potential community composition along a gradient of sites with contrasted conditions. The mechanistic relevance of ForCEEPS parameterization was explored by showing the congruence between the values of key model parameter and species functional traits. We further showed that accounting for the spatial configuration of crowns within forest stands, the effects of climatic constraints and the variability of shade tolerances in the species community are all crucial to better predict short-term productivity with gap-models. The dual ability of predicting short-term functioning and long-term community composition, as well as the balance between generality and realism (i.e., predicting accuracy) of the new generation of gap-models may open great perspectives for the exploration of the biodiversity-ecosystem functioning relationships, species coexistence mechanisms, and the impacts of climate change on forest ecosystems.

ecology↗