Abstract. Terrestrial biosphere models typically abstract the immense diversity of vegetation forms and functioning into a relatively small set of predefined semi-empirical plant functional types (PFTs). There is growing evidence, however, from the field ecology community as well as from modelling studies that current PFT schemes may not adequately represent the observed variations in plant functional traits and their effect on ecosystem functioning. In this paper, we introduce the Jena Diversity-Dynamic Global Vegetation Model (JeDi-DGVM) as a new approach to terrestrial biosphere modelling with a richer representation of functional diversity than traditional modelling approaches based on a small number of fixed PFTs. JeDi-DGVM simulates the performance of a large number of randomly generated plant growth strategies, each defined by a set of 15 trait parameters which characterize various aspects of plant functioning including carbon allocation, ecophysiology and phenology. Each trait parameter is involved in one or more functional trade-offs. These trade-offs ultimately determine whether a strategy is able to survive under the climatic conditions in a given model grid cell and its performance relative to the other strategies. The biogeochemical fluxes and land surface properties of the individual strategies are aggregated to the grid-cell scale using a mass-based weighting scheme. We evaluate the simulated global biogeochemical patterns against a variety of field and satellite-based observations following a protocol established by the Carbon-Land Model Intercomparison Project. The land surface fluxes and vegetation structural properties are reasonably well simulated by JeDi-DGVM, and compare favourably with other state-of-the-art global vegetation models. We also evaluate the simulated patterns of functional diversity and the sensitivity of the JeDi-DGVM modelling approach to the number of sampled strategies. Altogether, the results demonstrate the parsimonious and flexible nature of a functional trade-off approach to global vegetation modelling, i.e. it can provide more types of testable outputs than standard PFT-based approaches and with fewer inputs. The approach implemented here in JeDi-DGVM sets the foundation for future applications that will explore the impacts of explicitly resolving diverse plant communities, allowing for a more flexible temporal and spatial representation of the structure and function of the terrestrial biosphere.

Dynamic Global Vegetation Models (DGVMs) typically abstract the immense diversity of vegetation forms and functioning into a relatively small set of predefined semi-empirical Plant Functional Types (PFTs). There is growing evidence, however, from the field ecology community as well as from modelling studies that current PFT schemes may not adequately represent the observed variations in plant functional traits and their effect on ecosystem functioning. In this paper, we introduce the Jena Diversity DGVM (JeDi-DGVM) as a new approach to global vegetation modelling with a richer representation of functional diversity than traditional modelling approaches based on a small number of fixed PFTs. <br></br> JeDi-DGVM simulates the performance of a large number of randomly-generated plant growth strategies (PGSs), each defined by a set of 15 trait parameters which characterize various aspects of plant functioning including carbon allocation, ecophysiology and phenology. Each trait parameter is involved in one or more functional trade-offs. These trade-offs ultimately determine whether a PGS is able to survive under the climatic conditions in a given model grid cell and its performance relative to the other PGSs. The biogeochemical fluxes and land-surface properties of the individual PGSs are aggregated to the grid cell scale using a mass-based weighting scheme. <br></br> Simulated global biogeochemical and biogeographical patterns are evaluated against a variety of field and satellite-based observations following a protocol established by the Carbon-Land Model Intercomparison Project. The land surface fluxes and vegetation structural properties are reasonably well simulated by JeDi-DGVM, and compare favorably with other state-of-the-art terrestrial biosphere models. This is despite the parameters describing the ecophysiological functioning and allometry of JeDi-DGVM plants evolving as a function of vegetation survival in a given climate, as opposed to typical approaches that fix land surface parameters derived from observational datasets for each PFT. The approach implemented here in JeDi-DGVM sets the foundation for future applications that will explore the impacts of explicitly resolving diverse plant communities, allowing for a more flexible temporal and spatial representation of the structure and function of the terrestrial biosphere

Aim Two of the oldest observations in plant geography are the increase in plant diversity from the poles towards the tropics and the global geographic distribution of vegetation physiognomy (biomes). The objective of this paper is to use a processbased vegetation model to evaluate the relationship between modelled and observed global patterns of plant diversity and the geographic distribution of biomes. LocationThe global terrestrial biosphere. MethodsWe implemented and tested a novel vegetation model aimed at identifying strategies that enable plants to grow and reproduce within particular climatic conditions across the globe. Our model simulates plant survival according to the fundamental ecophysiological processes of water uptake, photosynthesis, reproduction and phenology. We evaluated the survival of an ensemble of 10,000 plant growth strategies across the range of global climatic conditions. For the simulated regional plant assemblages we quantified functional richness, functional diversity and functional identity.Results A strong relationship was found (correlation coefficient of 0.75) between the modelled and the observed plant diversity. Our approach demonstrates that plant functional dissimilarity increases and then saturates with increasing plant diversity. Six of the major Earth biomes were reproduced by clustering grid cells according to their functional identity (mean functional traits of a regional plant assemblage). These biome clusters were in fair agreement with two other global vegetation schemes: a satellite image classification and a biogeography model (kappa statistics around 0.4). Main conclusionsOur model reproduces the observed global patterns of plant diversity and vegetation physiognomy from the number and identity of simulated plant growth strategies. These plant growth strategies emerge from the first principles of climatic constraints and plant functional trade-offs. Our study makes important contributions to furthering the understanding of how climate affects patterns of plant diversity and vegetation physiognomy from a process-based rather than a phenomenological perspective.

The novel non-synonymous mutations found in this study enrich the knowledge about the genetic alterations of TK and DNA pol genes in ACV-resistant clinical HSV strains. Together with data from the literature, the findings justify the generation of a HSV database that contains resistance mutations associated with ACV resistance phenotype.

The 43 novel non-synonymous mutations enrich the knowledge about the natural genetic polymorphism of TK and DNA pol in clinical HSV strains. The findings have to be considered for genotypic analysis of HSV in case of clinical resistance.

Abstract. While the regional climate is the primary selection pressure for whether a plant strategy can survive, however, competitive interactions strongly affect the relative abundances of plant strategies within communities. Here, we investigate the relative importance of competition and perturbations on the development of vegetation community structure. To do so, we develop DIVE (Dynamics and Interactions of VEgetation), a simple general model that links plant strategies to their competitive dynamics, using growth and reproduction characteristics that emerge from climatic constraints. The model calculates population dynamics based on establishment, mortality, invasion and exclusion in the presence of different strengths of perturbations, seed and resource competition. The highest levels of diversity were found in simulations without competition as long as mortality is not too high. However, reasonable successional dynamics were only achieved when resource competition is considered. Under high levels of competition, intermediate levels of perturbations were required to obtain coexistence. Since succession and coexistence are observed in plant communities, we conclude that the DIVE model with competition and intermediate levels of perturbation represents an adequate way to model population dynamics. Because of the simplicity and generality of DIVE, it could be used to understand vegetation structure and functioning at the global scale and the response of vegetation to global change.

Aim: Projections of future climate change suggest that regional climates may evolve to states that are unlike any climate regime found on Earth today. These climates will impose novel constraints on plant species, and are likely to give rise to plant associations that are compositionally unlike any found on Earth today. Here, we explore whether the geographical distribution of previously mapped no-analogue climates corresponds to the geographical distribution of simulated no-analogue vegetation under scenarios of global warming. Location: Global landmasses. Methods: We used JeDi, a process-based vegetation model that accounts for ecophysiological trade-offs in plant growth and survival, to identify the assembly of plant functional types into no-analogue associations under scenarios of global warming. We compared the geographical distribution of these no-analogue vegetation types with those of no-analogue climates derived from seasonal temperature and precipitation. To better understand the climatic causes that lead to no-analogue vegetation, we performed a set of JeDi simulation experiments and compared them, as well as selected climate indices, with the geographical distribution of no-analogue vegetation. Finally, we explored the changes in plant characteristics leading to no-analogue vegetation composition. Results: In our model simulations, a no-analogue vegetation type emerged in Northern Eurasia due to the interacting effects of rising temperatures and the prolongation of the growing season, combined with stable patterns in the seasonal insolation cycle. Future tropical biomes experiencing novel temperature and precipitation regimes however, resemble contemporary vegetation despite significant losses of plant diversity. Main conclusions: Our modelling study shows how no-analogue vegetation can emerge in response to novel climates produced by rising temperatures and stable insolation, while also suggesting that no-analogue climates do not necessarily lead to no-analogue vegetation types. This result underlines the importance of considering plant diversity and the need to integrate ecophysiological knowledge through process-orientated models when projecting future vegetation. © 2013 John Wiley & Sons Ltd

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