Mapping biodiversity value worldwide: combining higher-taxon richness from different groups

Maps of large-scale biodiversity are urgently needed to guide conservation, and yet complete enumeration of organisms is impractical at present. One indirect approach is to measure richness at higher taxonomic ranks, such as families. The difficulty is how to combine information from different groups on numbers of higher taxa, when these taxa may in effect have been defined in different ways, particularly for more distantly related major groups. In this paper, the regional family richness of terrestrial and freshwater seed plants, amphibians, reptiles and mammals is mapped worldwide by combining: (i) absolute family richness; (ii) proportional family richness; and (iii) proportional family richness weighted for the total species richness in each major group. The assumptions of the three methods and their effects on the results are discussed, although for these data the broad pattern is surprisingly robust with respect to the method of combination. Scores from each of the methods of combining families are used to rank the top five richness hotspots and complementary areas, and hotspots of endemism are mapped by unweighted combination of range-size rarity scores

Habitat conversion and global avian biodiversity loss

The magnitude of the impacts of human activities on global biodiversity has been documented at several organizational levels. However, although there have been numerous studies of the effects of local-scale changes in land use (e.g. logging) on the abundance of groups of organisms, broader continental or global-scale analyses addressing the same basic issues remain largely wanting. None the less, changing patterns of land use, associated with the appropriation of increasing proportions of net primary productivity by the human population, seem likely not simply to have reduced the diversity of life, but also to have reduced the carrying capacity of the environment in terms of the numbers of other organisms that it can sustain. Here, we estimate the size of the existing global breeding bird population, and then make a first approximation as to how much this has been modified as a consequence of land-use changes wrought by human activities. Summing numbers across different land-use classes gives a best current estimate of a global population of less than 100 billion breeding bird individuals. Applying the same methodology to estimates of original land-use distributions suggests that conservatively this may represent a loss of between a fifth and a quarter of pre-agricultural bird numbers. This loss is shared across a range of temperate and tropical land-use types

Reproductive consequences of natal dispersal in a highly philopatric seabird

Natal and breeding dispersal have a major impact on gene flow and population structure. We examined the consequences of natal dispersal on the reproductive success (proportion of pairs rearing chicks) of colonial-breeding Thick-billed murres (Uria lomvia). Reproductive success increased with distance dispersed for the first and second breeding attempt. The increase in breeding success leveled off at natal dispersal distances above 7 m. Our results were consistent with the idea that the relationship between dispersal and reproductive success is caused by site availability and mate choice as birds willing to disperse farther had a greater choice of potential sites and mates. This hypothesis was supported by the fact that birds dispersing farther were more likely to pair with an experienced breeder, which increases the likelihood of breeding success for young breeders. Explanations for increasing breeding success with increased dispersal based on inbreeding effects were unlikely because most breeding failures were caused by egg loss rather than infertility or nestling death. However, we could not explain why >50% of birds return within 3 m of the natal site, despite having an up to 50% lower reproductive success than birds dispersing 7 m or mor

The distribution of species range size: a stochastic process

The major role played by environmental factors in determining the geographical range sizes of species raises the possibility of describing their long-term dynamics in relatively simple terms, a goal which has hitherto proved elusive. Here we develop a stochastic differential equation to describe the dynamics of the range size of an individual species based on the relationship between abundance and range size, derive a limiting stationary probability model to quantify the stochastic nature of the range size for that species at steady state, and then generalize this model to the species-range size distribution for an assemblage. The model fits well to several empirical datasets of the geographical range sizes of species in taxonomic assemblages, and provides the simplest explanation of species-range size distributions to date

Information content-based gene ontology semantic similarity approaches: toward a unified framework theory

Several approaches have been proposed for computing term information content (IC) and semantic similarity scores within the gene ontology (GO) directed acyclic graph (DAG). These approaches contributed to improving protein analyses at the functional level. Considering the recent proliferation of these approaches, a unified theory in a well-defined mathematical framework is necessary in order to provide a theoretical basis for validating these approaches. We review the existing IC-based ontological similarity approaches developed in the context of biomedical and bioinformatics fields to propose a general framework and unified description of all these measures. We have conducted an experimental evaluation to assess the impact of IC approaches, different normalization models, and correction factors on the performance of a functional similarity metric. Results reveal that considering only parents or only children of terms when assessing information content or semantic similarity scores negatively impacts the approach under consideration. This study produces a unified framework for current and future GO semantic similarity measures and provides theoretical basics for comparing different approaches. The experimental evaluation of different approaches based on different term information content models paves the way towards a solution to the issue of scoring a term’s specificity in the GO DAG

Information content-based gene ontology functional similarity measures: which one to use for a given biological data type?

The current increase in Gene Ontology (GO) annotations of proteins in the existing genome databases and their use in different analyses have fostered the improvement of several biomedical and biological applications. To integrate this functional data into different analyses, several protein functional similarity measures based on GO term information content (IC) have been proposed and evaluated, especially in the context of annotation-based measures. In the case of topology-based measures, each approach was set with a specific functional similarity measure depending on its conception and applications for which it was designed. However, it is not clear whether a specific functional similarity measure associated with a given approach is the most appropriate, given a biological data set or an application, i.e., achieving the best performance compared to other functional similarity measures for the biological application under consideration. We show that, in general, a specific functional similarity measure often used with a given term IC or term semantic similarity approach is not always the best for different biological data and applications. We have conducted a performance evaluation of a number of different functional similarity measures using different types of biological data in order to infer the best functional similarity measure for each different term IC and semantic similarity approach. The comparisons of different protein functional similarity measures should help researchers choose the most appropriate measure for the biological application under consideration

Ecosystem service provision by road verges

This is the final version. Available on open access from Wiley via the DOI in this record.1. Roads form a vast, rapidly-growing global network that has diverse, detrimental ecological impacts. However, the habitats that border roads (‘road verges’) form a parallel network that might help mitigate these impacts and provide additional benefits (ecosystem services; ES). 2. We evaluate the capacity of road verges to provide ES by reviewing existing research and considering their relevant characteristics; area, connectivity, shape, and contextual ES supply and demand. We consider the present situation, and how this is likely to change based on future projections for growth in road extent, traffic densities and urban populations. 3. Road verges provide a wide range of ES, including biodiversity provision, regulating services (e.g. air and water filtration) and cultural services (e.g. health and aesthetic benefits by providing access to nature), but also displace other habitats and provide ecosystem disservices (e.g. allergens and damage to infrastructure). Globally, road verges may currently cover 270,000 km2 and store 0.015 Gt C year-1 , which will further increase with 70% projected growth in the global road network. 4. Road verges are well-placed to mitigate traffic pollution and address demand for ES in surrounding ES-impoverished landscapes, thereby improving human health and wellbeing in urban areas, and improving agricultural production and sustainability in farmland. Demand for ES provided by road verges will likely increase due to projected growth in traffic densities and urban populations, though traffic pollution will be reduced by technological advances (e.g. electric vehicles). Road verges form a highly-connected network, which may enhance ES provision but facilitate the dispersal of invasive species and increase vehicle-wildlife collisions. 5. Synthesis and applications. Road verges offer a significant opportunity to mitigate the negative ecological effects of roads and to address demand for ES in surrounding ES-impoverished landscapes. Their capacity to provide ES might be enhanced considerably if they were strategically designed and managed for environmental outcomes, namely by optimizing the selection, position and management of plant species and habitats. Specific opportunities include reducing mowing frequencies and planting trees in large verges. Road verge management for ES must consider safety guidelines, financial costs and ecosystem disservices, but is likely to provide long-term financial returns if environmental benefits are taken into account.Natural Environment Research Counci

Birds and people in Europe

At a regional scale, species richness and human population size are frequently positively correlated across space. Such patterns may arise because both species richness and human density increase with energy availability. If the species-energy relationship is generated through the 'more individuals' hypothesis, then the prediction is that areas with high human densities will also support greater numbers of individuals from other taxa. We use the unique data available for the breeding birds in Europe to test this prediction. Overall regional densities of bird species are higher in areas with more people; species of conservation concern exhibit the same pattern. Avian density also increases faster with human density than does avian biomass, indicating that areas with a higher human density have a higher proportion of small-bodied individuals. The analyses also underline the low numbers of breeding birds in Europe relative to humans, with a median of just three individual birds per person, and 4 g of bird for every kilogram of human

Generation and Analysis of Large-Scale Data-Driven Mycobacterium tuberculosis Functional Networks for Drug Target Identification

Technological developments in large-scale biological experiments, coupled with bioinformatics tools, have opened the doors to computational approaches for the global analysis of whole genomes. This has provided the opportunity to look at genes within their context in the cell. The integration of vast amounts of data generated by these technologies provides a strategy for identifying potential drug targets within microbial pathogens, the causative agents of infectious diseases. As proteins are druggable targets, functional interaction networks between proteins are used to identify proteins essential to the survival, growth, and virulence of these microbial pathogens. Here we have integrated functional genomics data to generate functional interaction networks between Mycobacterium tuberculosis proteins and carried out computational analyses to dissect the functional interaction network produced for identifying drug targets using network topological properties. This study has provided the opportunity to expand the range of potential drug targets and to move towards optimal target-based strategies