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Dynamic global vegetation models are a common tool to assess the effect of climate and land use change on vegetation. Though most applications of dynamic global vegetation models use plant functional types, some also simulate species occurrences. While the current development aims to include more processes, e.g. the nitrogen cycle, the models still typically assume an ample seed supply allowing all species to establish once the climate conditions are suitable. Pollen studies have shown that a number of plant species lag behind in occupying climatological suitable areas (e.g. after a change in the climate) as they need to arrive at and establish in the newly suitable areas. Previous attempts to implement migration in dynamic vegetation models have allowed for the simulation of either only small areas or have been implemented as a post-process, not allowing for feedbacks within the vegetation. Here we present two novel methods simulating migrating and interacting tree species which have the potential to be used for simulations of large areas. Both distribute seeds between grid cells, leading to individual establishment. The first method uses an approach based on fast Fourier transforms, while in the second approach we iteratively shift the seed production matrix and disperse seeds with a given probability. While the former method is computationally faster, it does not allow for modification of the seed dispersal kernel parameters with respect to terrain features, which the latter method allows. We evaluate the increase in computational demand of both methods. Since dispersal acts at a scale no larger than 1 km, all dispersal simulations need to be performed at maximum at that scale. However, with the currently available computational power it is not feasible to simulate the local vegetation dynamics of a large area at that scale. We present an option to decrease the required computational costs through a reduction in the number of grid cells for which the local dynamics are simulated only along migration transects. Evaluation of species patterns and migration speeds shows that simulating along transects reduces migration speed, and both methods applied on the transects produce reasonable results. Furthermore, using the migration transects, both methods are sufficiently computationally efficient to allow for large-scale DGVM simulations with migration.

A great deal of biodiversity can be found in private forests, and protecting it requires taking into consideration the preferences of key stakeholders. In this study, we examine and compare the valuation of forest attributes across the general public, private non-industrial forest owners and forest officials in Sweden by conducting a choice experiment. Our results indicate that citizens have a positive valuation of biodiversity protection. Moreover, their valuation is statistically higher than those of forest owners, implying that there is room for compensation. Interestingly, our results suggest that both forest owners and forest officials have a strong orientation towards production, with higher valuation than the general public of the common management practice of similar age and clear felling. Even though the Swedish Forestry Act regards production and environmental goals as equally important, we find that forest officials prefer management practices that promote production rather than biodiversity protection. JEL: D61, Q23, Q51, Q58

International audience; AimVegetation dynamics and the competitive interactions involved are assumed to restrict the ability of species to migrate. But in most migration modelling approaches disturbance‐driven succession and competition processes are reduced to simple assumptions or are even missing. The aim of this study was to test a combination of a migration model and a dynamic vegetation model to estimate the migration of tree species controlled by climate, environment and local species dynamics such as succession and competition.LocationEurope.MethodsTo estimate the effect of vegetation dynamics on the migration of European beech and Norway spruce, we developed a post‐process migration tool (LPJ‐CATS). This tool integrates outputs of the migration model CATS and the dynamic vegetation model LPJ‐GUESS. The model LPJ‐CATS relies on a linear dependency between the dispersal kernel and migration rate and is based on the assumption that competition reduces fecundity.ResultsSimulating potential migration rates with the CATS model, which does not account for competition and disturbance, resulted in mean Holocene migration rates of 435 ± 55 and 330 ± 95 m year−1 for the two species Picea abies and Fagus sylvatica, respectively. With LPJ‐CATS, these mean migration rates were reduced to 250 ± 75 and 170 ± 60 m year−1 for spruce and beech, respectively. Moreover, LPJ‐CATS simulated migration pathways of these two species that generally comply well with those documented in the palaeo‐records.Main conclusionsOur ‘hybrid’ modelling approach allowed for the simulation of generally realistic Holocene migration rates and pathways of the two study species on a continental scale. It suggests that competition can considerably modify spread rates, but also the magnitude of its effect depends on how close climate conditions are to the niche requirements of a particular species.

Fire is the most important ecological and forest disturbance agent worldwide, is a major way by which carbon is transferred from the land to the atmosphere, and is globally a significant source of greenhouse gases and aerosols. Wildfires across all major biome types globally consume about 5% of net annual terrestrial primary production per annum, and release about 2-4 Pg C per annum, of which approximately 0.6 Pg C comes from tropical deforestation and below-ground peat fires. The global figure is equivalent to about 20-30% of global emissions from fossil fuels. Tropical savannas comprise the largest areas burned and greatest emissions sources from vegetation wildfires. Fires in Mediterranean forests and shrublands, tropical forests and boreal forests are also significant sources of emissions because they are generally characterised by much higher fuel loads per unit area compared with grasslands. Improved satellite data and sophisticated biogeochemical modeling enables emis-sions assessments on a global scale with fine spatial and temporal resolution. Emissions estimates are still comparable to those based on older inventory-based techniques, but uncertainties remain large. Fires increase during El Niño periods because parts of the tropics where humans use fire as a tool for deforestation experience drought conditions. These spikes contribute to the inter-annual variability of CO2 and CH4 observed in the atmosphere. Recently developed dynamic fire-vegetation models are capable of simulating the extent of wildfires as well as their emissions of CO2 and other greenhouse gases for ambient as well as for projected climatic conditions. The performance of fire-vegetation models however needs to be strongly improved and validated.

The focus of this thesis lies on the functional analysis and modelling of vegetation. A statistical method for the optimisation of plant functional types is developed in the first part. The fourth corner method by Pierre Legendre et al. was adapted to the task of grouping of plant functional types. New null models are developed for this randomisation method and their statistical properties are investigated. The mechanistical model LEGOMODEL is used to simulate the succession of plant functional types using the 'Leaf-Height-Seed Scheme'. This classification scheme uses only the plant traits specific leaf area, plant height and seed weight. A trait hierarchy for the assembly of plant communities is formed in gradients of fertility and disturbance. The third part applies the developed method to a field experiment following the succession of plant communities over four years in gradients of fertility and disturbance. The plant traits canopy height, life cycle and spacer length are sufficient to form a statistical significant functional grouping of the plant species incorporated in the experiment.