7.01.05 - Modelling and risk assessment
Unit 7.01.05 has been set up to meet the multi-faceted forest health challenge by combining new experts and approaches (e.g., modelling, in-field surveys, space observations) to i) develop hierarchical modelling framework to quantify and forecast climate change impacts on forest health indicators and to ii) guide management decisions and efficient policy recommendations toward increased health, sustainability and productivity forest resilience worldwide.
This unit will develop more realistic projections of forest and their health under future climate change through ideal chemical-transport models, fully coupled with dynamic vegetation models, simulating the full range of climatic and other environmental conditions, and interactions, under which plant species could establish, grow, reproduce and persist. The unit outputs will enable: i) a better understanding of the processes involved in the interaction and feedbacks between air pollution and climate change impacts on forests; ii) a spatio-temporal monitoring to facilitate early detection of forest health threats, intervention and adaptive silviculture and iii) a precise understanding of their impacts on society.
State of Knowledge
Forest ecosystems face increasing and emerging threats, including resurgence of diseases and pests, climate and land use changes, air pollution, and the synergistic effects of these combined challenges affecting the sustainable management of forests and other natural and semi-natural ecosystems. Change in climate, air quality and land use have large effects on plant species distributions, plant community composition and diversity, vegetation structure, productivity and cycling of carbon, nutrients and water. Moreover, management-relevant projections suffer from substantial uncertainties with regard to input data, model structure and model parameters.
The combined effects of stressors may significantly differ from the sum of the separate effects. Reliable quantitative predictions of future climate and air pollutant scenarios, and associated impacts on ecosystems, are urgently required for risk assessment of high biodiversity forest ecosystems (e.g., tropical, Mediterranean) and under-investigated areas of the world (e.g., Africa, South America, Asia). In field surveys are expected to provide field validation to models and reduce the uncertainties in estimates of the effects of stresses induced by air pollution and climate change on vegetation (Sicard et al., 2016a).
Analyses of large scale monitoring data sets show significant effects of atmospheric deposition on nutrient-acidity status in terms of elevated nitrogen and sulphur or sulphate concentrations in forest foliage and soil solution and related soil acidification in terms of elevated aluminum and/or base cation leaching from the forest ecosystem. Relationships of air pollution with crown condition, however, appear to be weak and limited in time and space, while climatic factors appear to be more important drivers. Regarding forest growth, monitoring results indicate a clear fertilization effect of N deposition on European forests but the field evidence for impacts of ambient ozone exposure on tree growth is less clear than results obtained from ozone exposure experiments (e.g., De vries et al., 2014a)
At present, limited models can evaluate the combined effects of past and expected future changes in climatic variables (precipitation and temperature), CO2 concentrations, nitrogen deposition and ozone exposure on forest productivity and related Carbon sequestration in trees and soils. Furthermore, very few models also account for the possible limitation of forests growth by other major nutrients, i.e. calcium, magnesium, potassium and phosphorus.
Unit 7.01.05 focusses on the further development of models and the use of a combination of experimental data and monitoring data sets for validation purposes of regional and global scale models. This is particularly true for physiological and environmental parameters describing the water, carbon and nutrient cycles. Furthermore, we aim to improve exposure estimates on forests, such as N deposition and ozone exposure. We thus promote and strengthen the development harmonization, coupling and further development of climate and air quality models to perform high resolution multi-model simulations of the deposition/exposure of nitrogen oxides, sulfur, ammonia, tropospheric ozone
Additionally, we recognize that resolution is lost as models attempt to recreate major ecosystem processes, and therefore may be insensitive to subtle but potentially important signs of climate induced shifts in ecosystem structure and function. Therefore, model output will be combined with field based observations to better assess ecosystem risk.