Modularity of trophic network is driven by phylogeny and migration in a steppe ecosystem

Evidence is mounting that the structures of trophic networks are governed by migratory movements of interacting species and also by their phylogenetic relationships. Using the largest available trophic network of a large steppe ecosystem, we tested that steppe trophic networks including migratory species are associated with (i) migratory strategy and (ii) phylogenetic relatedness of interacting species: (1) whole graph-level metrics, estimated as modularity, and (2) species-level network metrics, measured as node degree (number of interacting partners), and centrality metrics. We found that (1) a substantial number of links were established by migrant taxa; (2) the phylogenetic signal in network structure was moderate for both consumer and prey nodes; (3) both consumer and prex phylogenies affected modularity, which was modulated by migration strategy; and (4) all species-level graph properties significantly differed between networks including and excluding migratory taxa. In sum, here we show that the structure of steppe trophic networks is primarily governed by migratory strategies and to a lesser extent, by phylogenetic relatedness, using the largest available food web representative for steppe ecology and migration biology

Data-driven network alignment

Biological network alignment (NA) aims to find a node mapping between species' molecular networks that uncovers similar network regions, thus allowing for transfer of functional knowledge between the aligned nodes. However, current NA methods do not end up aligning functionally related nodes. A likely reason is that they assume it is topologically similar nodes that are functionally related. However, we show that this assumption does not hold well. So, a paradigm shift is needed with how the NA problem is approached. We redefine NA as a data-driven framework, TARA (daTA-dRiven network Alignment), which attempts to learn the relationship between topological relatedness and functional relatedness without assuming that topological relatedness corresponds to topological similarity, like traditional NA methods do. TARA trains a classifier to predict whether two nodes from different networks are functionally related based on their network topological patterns. We find that TARA is able to make accurate predictions. TARA then takes each pair of nodes that are predicted as related to be part of an alignment. Like traditional NA methods, TARA uses this alignment for the across-species transfer of functional knowledge. Clearly, TARA as currently implemented uses topological but not protein sequence information for this task. We find that TARA outperforms existing state-of-the-art NA methods that also use topological information, WAVE and SANA, and even outperforms or complements a state-of-the-art NA method that uses both topological and sequence information, PrimAlign. Hence, adding sequence information to TARA, which is our future work, is likely to further improve its performance

Technological relatedness and regional branching

The relatedness between the technologies used among firms in a region is thought to affect the nature and scope of knowledge spillovers. In this paper, we set out how the concepts of technological relatedness and related variety have enriched recent literature in economic geography. First, applying the notion of related variety has led to new insights in the externalities literature. There is increasing evidence that regions with different but technologically related activities (related variety) benefit more from spillovers. Second, the technological relatedness concept has provided additional insights to the question whether extra-regional linkages matter for regional growth: it is not inflows of extra-regional knowledge per se, but inflows of knowledge that are related to the existing knowledge base of regions that might be crucial. Third, the concept of relatedness has found its way in network analysis. There is evidence that collaborative research projects tend to create more new knowledge when they consist of agents that bring in related competences. Linking network dynamics to the industry life-cycle approach, one expects that cognitive proximity levels between cluster firms will increase over time, with detrimental effects on their performance levels. Fourth, the cluster literature often regards labor mobility as a key mechanism through which knowledge diffuses, but no attention has been paid to relatedness until recently. And fifth, studies demonstrate that countries and regions tend to expand into sectors that are closely related to their existing activities. To the extent that new industries emerge from related industries, the sectoral composition of a regional economy affects the diversification opportunities of regions in the long run. This process of sectoral branching occurs primarily at the regional level, because it becomes manifest through a number of knowledge transfer mechanisms (i.e. spinoff activity, firm diversification, labor mobility and networking) that tend to be geographically bounded.evolutionary economic geography, technological relatedness, regional branching, related variety

Industry diversity, competition and firm relatedness: The impact on employment before and after the 2008 global financial crisis

Industry diversity, competition and firm relatedness: the impact on employment before and after the 2008 global financial crisis. Regional Studies. This study investigates the extent to which indicators of external-scale economies impacted employment growth in Canada over the period 2004–11. It focuses on knowledge spillovers between firms while accounting for Marshallian specialization, Jacobs’ diversity and competition by industry, as well as related and unrelated firm varieties in terms of employment and sales. It is found that the employment growth effects of local competition and diversity are positive, while the effect of Marshallian specialization is negative. Diversification is found to be particularly important for employment growth during the global financial crisis and immediately thereafter

The role of industry, occupation, and location specific knowledge in the survival of new firms

How do regions acquire the knowledge they need to diversify their economic activities? How does the migration of workers among firms and industries contribute to the diffusion of that knowledge? Here we measure the industry, occupation, and location-specific knowledge carried by workers from one establishment to the next using a dataset summarizing the individual work history for an entire country. We study pioneer firms--firms operating in an industry that was not present in a region--because the success of pioneers is the basic unit of regional economic diversification. We find that the growth and survival of pioneers increase significantly when their first hires are workers with experience in a related industry, and with work experience in the same location, but not with past experience in a related occupation. We compare these results with new firms that are not pioneers and find that industry-specific knowledge is significantly more important for pioneer than non-pioneer firms. To address endogeneity we use Bartik instruments, which leverage national fluctuations in the demand for an activity as shocks for local labor supply. The instrumental variable estimates support the finding that industry-related knowledge is a predictor of the survival and growth of pioneer firms. These findings expand our understanding of the micro-mechanisms underlying regional economic diversification events

Friendship and Natural Selection

More than any other species, humans form social ties to individuals who are neither kin nor mates, and these ties tend to be with similar people. Here, we show that this similarity extends to genotypes. Across the whole genome, friends' genotypes at the SNP level tend to be positively correlated (homophilic); however, certain genotypes are negatively correlated (heterophilic). A focused gene set analysis suggests that some of the overall correlation can be explained by specific systems; for example, an olfactory gene set is homophilic and an immune system gene set is heterophilic. Finally, homophilic genotypes exhibit significantly higher measures of positive selection, suggesting that, on average, they may yield a synergistic fitness advantage that has been helping to drive recent human evolution