Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest ...models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio‐temporal scales unreachable by most empirical investigations.
We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.
Using three widely applied but contrasting approaches – species distribution models, individual‐based forest models, and dynamic global vegetation models – as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.
Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.
Forest models can help understanding the processes that shape forest functioning, structure and diversity, since they can can simulate forest dynamics over spatio‐temporal scales unreachable by most empirical investigations. Here we describe the development of three widely applied but contrasting forest mo−delling approaches — species distribution models, individual‐based models and dynamic global vegetation models. We provide an overview of recent model applications and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.
Climate extremes have the potential to cause extreme responses of terrestrial ecosystem functioning. However, it is neither straightforward to quantify and predict extreme ecosystem responses, nor to ...attribute these responses to specific climate drivers. Here, we construct a factorial experiment based on a large ensemble of process-oriented ecosystem model simulations driven by a regional climate model (12 500 model years in 1985-2010) in six European regions. Our aims are to (1) attribute changes in the intensity and frequency of simulated ecosystem productivity extremes (EPEs) to recent changes in climate extremes, CO2 concentration, and land use, and to (2) assess the effect of timing and seasonal interaction on the intensity of EPEs. Evaluating the ensemble simulations reveals that (1) recent trends in EPEs are seasonally contrasting: spring EPEs show consistent trends towards increased carbon uptake, while trends in summer EPEs are predominantly negative in net ecosystem productivity (i.e. higher net carbon release under drought and heat in summer) and close-to-neutral in gross productivity. While changes in climate and its extremes (mainly warming) and changes in CO2 increase spring productivity, changes in climate extremes decrease summer productivity neutralizing positive effects of CO2. Furthermore, we find that (2) drought or heat wave induced carbon losses in summer (i.e. negative EPEs) can be partly compensated by a higher uptake in the preceding spring in temperate regions. Conversely, however, carry-over effects from spring to summer that arise from depleted soil moisture exacerbate the carbon losses caused by climate extremes in summer, and are thus undoing spring compensatory effects. While the spring-compensation effect is increasing over time, the carry-over effect shows no trend between 1985-2010. The ensemble ecosystem model simulations provide a process-based interpretation and generalization for spring-summer interacting carbon cycle effects caused by climate extremes (i.e. compensatory and carry-over effects). In summary, the ensemble ecosystem modelling approach presented in this paper offers a novel route to scrutinize ecosystem responses to changing climate extremes in a probabilistic framework, and to pinpoint the underlying eco-physiological mechanisms.
Vegetation responds to drought through a complex interplay of plant hydraulic mechanisms, posing challenges for model development and parameterization. We present a mathematical model that describes ...the dynamics of leaf water-potential over time while considering different strategies by which plant species regulate their water-potentials. The model has two parameters: the parameter
describing the adjustment of the leaf water potential to changes in soil water potential, and the parameter Δψ
describing the typical 'well-watered' leaf water potentials at non-stressed (near-zero) levels of soil water potential. Our model was tested and calibrated on 110 time-series datasets containing the leaf- and soil water potentials of 66 species under drought and non-drought conditions. Our model successfully reproduces the measured leaf water potentials over time based on three different regulation strategies under drought. We found that three parameter sets derived from the measurement data reproduced the dynamics of 53% of an drought dataset, and 52% of a control dataset root mean square error (RMSE) < 0.5 MPa). We conclude that, instead of quantifying water-potential-regulation of different plant species by complex modeling approaches, a small set of parameters may be sufficient to describe the water potential regulation behavior for large-scale modeling. Thus, our approach paves the way for a parsimonious representation of the full spectrum of plant hydraulic responses to drought in dynamic vegetation models.
Amazonian ecosystems are major biodiversity hotspots and carbon sinks that may lose species to extinction and become carbon sources due to extreme dry or warm conditions. We investigated the seasonal ...patterns of high-resolution solar-induced chlorophyll fluorescence (SIF) measured by the satellite Orbiting Carbon Observatory-2 (OCO-2) across the Amazonian ecoregions to assess the area´s phenology and extreme drought vulnerability. SIF is an indicator of the photosynthetic activity of chlorophyll molecules and is assumed to be directly related to gross primary production (GPP). We analyzed SIF variability in the Amazon basin during the period between September 2014 and December 2018. In particular, we focused on the SIF drought response under the extreme drought period during the strong El Niño in 2015–2016, as well as the 6-month drought peak period. During the drought´s peak months, the SIF decreased and increased with different intensities across the ecoregions of the Amazonian moist broadleaf forest (MBF) biome. Under a high temperature, a high vapor pressure deficit, and extreme drought conditions, the SIF presented differences from −31.1% to +17.6%. Such chlorophyll activity variations have been observed in plant-level measurements of active fluorescence in plants undergoing physiological responses to water or heat stress. Thus, it is plausible that the SIF variations in the ecoregions’ ecosystems occurred as a result of water and heat stress, and arguably because of drought-driven vegetation mortality and collateral effects in their species composition and community structures. The SIF responses to drought at the ecoregional scale indicate that there are different levels of resilience to drought across MBF ecosystems that the currently used climate- and biome-region scales do not capture. Finally, we identified monthly SIF values of 32 ecoregions, including non-MBF biomes, which may give the first insights into the photosynthetic activity dynamics of Amazonian ecoregions.
Along with the accumulation of atmospheric greenhouse gases, particularly carbon dioxide, the loss of primary forests and other natural ecosystems is a major disruption of the Earth's system and is ...causing global concern. Quantifying planetary warming from carbon emissions, global climate models highlight natural forests' high carbon storage potential supporting conservation policies. However, some model outcomes effectively deprioritize conservation of boreal and temperate forests by suggesting that increased albedo upon deforestation could cool the planet. A potential conflict of global cooling vs. regional forest conservation could harm environmental policies. Here we present theoretical and observational evidence to demonstrate that, compared to the carbon-related warming, modeling skills for assessing climatic impacts of deforestation is low. We argue that estimates for deforestation-induced global cooling result from the models' limited capacity to account for the global effect of cooling from evapotranspiration of intact forests. Specifically, transpiration of trees can change the greenhouse effect via small modifications of the vertical temperature profile. However, due to their convective parameterization (which postulates a certain critical temperature profile), global climate models do not properly capture this effect. This may lead to an underestimation of warming from the loss of forest evapotranspiration in both high and low latitudes. As a result, conclusions about deforestation-induced global cooling are not robust and could result in action that immediately worsened global warming. To avoid deepening the environmental crisis, these conclusions should not inform policies of vegetation cover management, especially as studies from multiple fields are accumulating that better quantify the stabilizing impact of natural ecosystems evolved to maintain environmental homeostasis. Given the critical state and our limited understanding of both climate and ecosystems, an optimal policy with immediate benefits would be a global moratorium on the exploitation of all natural forests.
Background
Forests mitigate climate change by reducing atmospheric
CO
2
-concentrations through the carbon sink in the forest and in wood products, and substitution effects when wood products replace ...carbon-intensive materials and fuels. Quantifying the carbon mitigation potential of forests is highly challenging due to the influence of multiple important factors such as forest age and type, climate change and associated natural disturbances, harvest intensities, wood usage patterns, salvage logging practices, and the carbon-intensity of substituted products. Here, we developed a framework to quantify the impact of these factors through factorial simulation experiments with an ecosystem model at the example of central European (Bavarian) forests.
Results
Our simulations showed higher mitigation potentials of young forests compared to mature forests, and similar ones in broad-leaved and needle-leaved forests. Long-lived wood products significantly contributed to mitigation, particularly in needle-leaved forests due to their wood product portfolio, and increased material usage of wood showed considerable climate benefits. Consequently, the ongoing conversion of needle-leaved to more broad-leaved forests should be accompanied by the promotion of long-lived products from broad-leaved species to maintain the product sink. Climate change (especially increasing disturbances) and decarbonization were among the most critical factors influencing mitigation potentials and introduced substantial uncertainty. Nevertheless, until 2050 this uncertainty was narrow enough to derive robust findings. For instance, reducing harvest intensities enhanced the carbon sink in our simulations, but diminished substitution effects, leading to a decreased total mitigation potential until 2050. However, when considering longer time horizons (i.e. until 2100), substitution effects became low enough in our simulations due to expected decarbonization such that decreasing harvests often seemed the more favorable solution.
Conclusion
Our results underscore the need to tailor mitigation strategies to the specific conditions of different forest sites. Furthermore, considering substitution effects, and thoroughly assessing the amount of avoided emissions by using wood products, is critical to determine mitigation potentials. While short-term recommendations are possible, we suggest risk diversification and methodologies like robust optimization to address increasing uncertainties from climate change and decarbonization paces past 2050. Finally, curbing emissions reduces the threat of climate change on forests, safeguarding their carbon sink and ecosystem services.
Enhancing the capacity of social‐ecological systems (SES) to adapt to climate change is of crucial importance. While gradual climate change impacts have been the main focus of much recent research, ...much less is known about how SES are impacted by climate extremes and how they adapt. Here, based on an advanced conceptualization of social‐ecological resilience, performed by an interdisciplinary group of scientists, we outline three major challenges for operationalizing the resilience concept with particular focus on climate extremes. First, we discuss the necessary steps required to identify and measure relevant variables for capturing the full response spectrum of the coupled social and ecological components of SES. Second, we examine how climate extreme impacts on coupling flows in SES can be quantified by learning from past societal transitions or adaptations to climate extremes and resulting changes in ecosystem service supply. Last, we explore how to identify management options for maintaining and enhancing social‐ecological resilience under a changing regime of climate extremes. We conclude that multiple pathways within adaptation and mitigation strategies which enhance the adaptive capacity of SES to absorb climate extremes will open the way toward a sustainable future.
Plain Language Summary
Ecosystems and society are closely coupled and are both affected by climate change. Climate extremes are expected to occur more often and/or get more intense under climate change. We ask the following question: How can ecosystems and society, which can be described as so‐called social‐ecological systems, withstand climate extremes and can therefore become more resilient? To achieve this, we use the concept of social‐ecological resilience and identify three challenges that scientists, decision makers, and practitioners need to work on to improve the adaptive capacity of social‐ecological systems to climate extremes. We need to describe and measure the main drivers of climate extremes that impact ecosystems and society and those variables that describe the adaptive capacity and all possible responses of ecosystems and society. Ecosystems and society are coupled: Ecosystems provide ecosystem services to society, and society manages ecosystems. These coupling flows also change under the impact of climate extremes. We still do not fully understand how climate extremes impact these coupling flows or how they can be measured. Because society has influenced ecosystems for many centuries and millennia in many regions of the world, these coupling flows also often have a long history; as such we cannot expect ecosystems and society to adapt to climate extremes separately. We can learn about impacts from past extreme events to continuously improve the management of ecosystems and increase the adaptive capacity of social‐ecological systems. Such management options range from adaptations of land management to institutional practices which are often necessary in order to be useful in helping the affected region immediately after a climate extreme event.
Key Points
Climate extremes impact the resilience of social‐ecological systems; their adaptation requires knowledge on ecological and social mechanisms
Relevant ecological and social variables document the impact of climate extremes on the coupling flows, enabling management options
Three challenges remain to advance our understanding on adapting social‐ecological systems for a resilient and sustainable future
We present a simple method of probabilistic risk analysis for ecosystems. The only requirements are time series-modelled or measured-of environment and ecosystem variables. Risk is defined as the ...product of hazard probability and ecosystem vulnerability. Vulnerability is the expected difference in ecosystem performance between years with and without hazardous conditions. We show an application to drought risk for net primary productivity of coniferous forests across Europe, for both recent and future climatic conditions.
Fifteen years after the heavy storm “Vivian”, it is still not clear how succession in subalpine forests that were affected by the storm will continue and when regrowing forests will provide effective ...protection from natural hazards such as avalanches. We used a simulation model to evaluate forest succession, forest structure and the protective effect in subalpine blowdown areas after 50 simulation years under different scenarios. The scenarios included the effects of different management strategies such as clearing the fallen logs or leaving the sites untouched (“uncleared”), variations in seed supply, and ungulate browsing. The simulation results indicated that forest structure was heterogeneous after 50 years, with a high amount of trees between 11 and 100 cm height, and a low amount of trees taller than 1 m. The number of trees
>
5 m, which is important for the protective effect of a site, was lower at uncleared areas if the area was covered with high amounts of fallen logs, but diversity of microsites was higher than at cleared areas. We found that it is particularly important that abundant seed supply occurs within the first few years after the blowdown at cleared sites, because in later stages there was high competition by tall herbs, which prevented the establishment of tree regeneration. Larger time lags between seed years in the simulations led to retarded tree regeneration. Particularly at cleared sites, ungulate browsing retarded tree regeneration. In contrast, uncleared sites had a higher potential to recover from high browsing pressure due to a high amount of favourable microsites that are provided by decaying logs. These results of our model simulations may help understanding the dynamics of forest regeneration and providing perspectives for management after blowdown events.
Tropical vegetation biomass represents a key component of the carbon stored in global forest ecosystems. Estimates of aboveground biomass commonly rely on measurements of tree size (diameter and ...height) and then indirectly relate, via allometric relationships and wood density, to biomass sampled from a relatively small number of harvested and weighed trees. Recently, however, novel in situ remote sensing techniques have been proposed, which may provide nondestructive alternative approaches to derive biomass estimates. Nonetheless, we still lack knowledge of the measurement uncertainties, as both the calibration and validation of estimates using different techniques and instruments requires consistent assessment of the underlying errors. To that end, we investigate different approaches estimating the tropical aboveground biomass in situ. We quantify the total and systematic errors among measurements obtained from terrestrial light detection and ranging (LiDAR), hypsometer-based trigonometry, and traditional forest inventory. We show that laser-based estimates of aboveground biomass are in good agreement (<10% measurement uncertainty) with traditional measurements. However, relative uncertainties vary among the allometric equations based on the vegetation parameters used for parameterization. We report the error metrics for measurements of tree diameter and tree height and discuss the consequences for estimated biomass. Despite methodological differences detected in this study, we conclude that laser-based electronic devices could complement conventional measurement techniques, thereby potentially improving estimates of tropical vegetation biomass.
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