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An introduction to the journal is presented in which the editor discusses an article on the impact of natural drought in Amazon, the quality of various global circulation models (GCMs) climate situations which are employed to drive dynamic global vegetation models (DGVMs), and the mechanisms involve in DGVM processes.

•Second-generation Dynamic Global Vegetation Models (DGVMs) have recently been developed that explicitly represent the ecological dynamics of disturbance, vertical competition for light, and succession. Here, we introduce a modified second-generation DGVM and examine how the representation of demographic processes operating at two-dimensional spatial scales not represented by these models can influence predicted community structure, and responses of ecosystems to climate change. •The key demographic processes we investigated were seed advection, seed mixing, sapling survival, competitive exclusion and plant mortality. We varied these parameters in the context of a simulated Amazon rainforest ecosystem containing seven plant functional types (PFTs) that varied along a trade-off surface between growth and the risk of starvation induced mortality. •Varying the five unconstrained parameters generated community structures ranging from monocultures to equal co-dominance of the seven PFTs. When exposed to a climate change scenario, the competing impacts of CO2 fertilization and increasing plant mortality caused ecosystem biomass to diverge substantially between simulations, with mid-21st century biomass predictions ranging from 1.5 to 27.0 kg C m−2. •Filtering the results using contemporary observation ranges of biomass, leaf area index (LAI), gross primary productivity (GPP) and net primary productivity (NPP) did not substantially constrain the potential outcomes. We conclude that demographic processes represent a large source of uncertainty in DGVM predictions. [ABSTRACT FROM AUTHOR]

Measurements of the net CO2 flux between terrestrial ecosystems and the atmosphere using the eddy covariance technique have the potential to underpin our interpretation of regional CO2 source–sink patterns, CO2 flux responses to forcings, and predictions of the future terrestrial C balance. Information contained in FLUXNET eddy covariance data has multiple uses for the development and application of global carbon models, including evaluation/validation, calibration, process parameterization, and data assimilation. This paper reviews examples of these uses, compares global estimates of the dynamics of the global carbon cycle, and suggests ways of improving the utility of such data for global carbon modelling. Net ecosystem exchange of CO2 (NEE) predicted by different terrestrial biosphere models compares favourably with FLUXNET observations at diurnal and seasonal timescales. However, complete model validation, particularly over the full annual cycle, requires information on the balance between assimilation and decomposition processes, information not readily available for most FLUXNET sites. Site history, when known, can greatly help constrain the model-data comparison. Flux measurements made over four vegetation types were used to calibrate the land-surface scheme of the Goddard Institute for Space Studies global climate model, significantly improving simulated climate and demonstrating the utility of diurnal FLUXNET data for climate modelling. Land-surface temperatures in many regions cool due to higher canopy conductances and latent heat fluxes, and the spatial distribution of CO2 uptake provides a significant additional constraint on the realism of simulated surface fluxes. FLUXNET data are used to calibrate a global production efficiency model (PEM). [ABSTRACT FROM AUTHOR]

The author reflects regarding the conservation of biodiversity. He various factors that contributes to the biodiversity destruction which include the global scale travel of plants and people and intervention of human for the replacement of natural vegetation. He mentions that the result for the molecular approaches application to diversity which provided qualified and quantified hypotheses in geographical locations and species variety can help to give clarity for biodiversity conservation.