Normative productivity of the global vegetation

<p>Abstract</p> <p>Background</p> <p>The biosphere models of terrestrial productivity are essential for projecting climate change and assessing mitigation and adaptation options. Many of them have been developed in connection to the International Geosphere-Biosphere Program (IGBP) that backs the work of the Intergovernmental Panel on Climate Change (IPCC). In the end of 1990s, IGBP sponsored release of a data set summarizing the model outputs and setting certain norms for estimates of terrestrial productivity. Since a number of new models and new versions of old models were developed during the past decade, these normative data require updating.</p> <p>Results</p> <p>Here, we provide the series of updates that reflects evolution of biosphere models and demonstrates evolutional stability of the global and regional estimates of terrestrial productivity. Most of them fit well the long-living Miami model. At the same time we call attention to the emerging alternative: the global potential for net primary production of biomass may be as high as 70 PgC y^-1, the productivity of larch forest zone may be comparable to the productivity of taiga zone, and the productivity of rain-green forest zone may be comparable to the productivity of tropical rainforest zone.</p> <p>Conclusion</p> <p>The departure from Miami model's worldview mentioned above cannot be simply ignored. It requires thorough examination using modern observational tools and techniques for model-data fusion. Stability of normative knowledge is not its ultimate goal – the norms for estimates of terrestrial productivity must be evidence-based.</p

Phylogenetic tree building in the genomic age

Knowing phylogenetic relationships among species is fundamental for many studies in biology. An accurate phylogenetic tree underpins our understanding of the major transitions in evolution such as the emergence of new body plans or metabolism and is key to inferring the origin of new genes, detecting molecular adaptation, understanding morphological character evolution, and reconstructing demographic changes in recently diverged species. While data are ever more plentiful and powerful analysis methods are available, there remain many challenges to reliable tree building. Here we discuss the major steps of phylogenetic analysis, including identification of orthologous genes or proteins, multiple sequence alignment and choice of substitution models and inference methodologies. Understanding different sources of errors and strategies to mitigate them is essential for assembling an accurate tree of life

Inferring Orthology and Paralogy.

The distinction between orthologs and paralogs, genes that started diverging by speciation versus duplication, is relevant in a wide range of contexts, most notably phylogenetic tree inference and protein function annotation. In this chapter, we provide an overview of the methods used to infer orthology and paralogy. We survey both graph-based approaches (and their various grouping strategies) and tree-based approaches, which solve the more general problem of gene/species tree reconciliation. We discuss conceptual differences among the various orthology inference methods and databases and examine the difficult issue of verifying and benchmarking orthology predictions. Finally, we review typical applications of orthologous genes, groups, and reconciled trees and conclude with thoughts on future methodological developments