Spatial and Temporal Heterogeneity in Founding Patterns

A growing body of literature suggests that populations of organizations are not homogeneous, but instead comprise distinct subentities. Firms are highly dependent on their immediate institutional and competitive environments. The present paper further explores this issue by focusing on the spatial and temporal sources of industry heterogeneity. Our goal is threefold. First, we explore founding rates as a function of spatial density, arguing that density-dependent processes occur along a geographic gradient ranging from proximate, to neighboring, to more distant contexts. Second, we show how multiple, local evolutionary clocks shape such entrepreneurial activity. Third, we provide evidence on how diffusion processes are directly affected by social contagion, with new organizational forms spreading through movements of individuals. Results from data on the Dutch accounting industry corroborate these patterns of heterogeneity

Modeling the ecology and evolution of biodiversity: Biogeographical cradles, museums, and graves

Individual processes shaping geographical patterns of biodiversity are increasingly understood, but their complex interactions on broad spatial and temporal scales remain beyond the reach of analytical models and traditional experiments. To meet this challenge, we built a spatially explicit, mechanistic simulation model implementing adaptation, range shifts, fragmentation, speciation, dispersal, competition, and extinction, driven by modeled climates of the past 800,000 years in South America. Experimental topographic smoothing confirmed the impact of climate heterogeneity on diversification. The simulations identified regions and episodes of speciation (cradles), persistence (museums), and extinction (graves). Although the simulations had no target pattern and were not parameterized with empirical data, emerging richness maps closely resembled contemporary maps for major taxa, confirming powerful roles for evolution and diversification driven by topography and climate

Industrial dynamics and economic geography: a survey

We review the literature on clusters and their effects on industrial dynamics as well on various lifecycle dynamics underlying the process of cluster formation and cluster dynamics. The review shows that there is little evidence that clusters enhance firm growth and survival. In the absence of localization economies, the emergence of clusters is best understood as an evolutionary process of capability transmission between parents firms and their spinoffs. We discuss various future research avenues and call for theorising based on firm heterogeneity as well as empirical research based on common methodological standards.entry, exit, cluster, localization economies, lifecycle, firm heterogeneity

Herbicide cycling has diverse effects on evolution of resistance in Chlamydomonas reinhardtii

Cycling pesticides has been proposed as a means of retarding the evolution of resistance, but its efficacy has rarely been empirically tested. We evolved populations of Chlamydomonas reinhardtii in the presence of three herbicides: atrazine, glyphosate and carbetamide. Populations were exposed to a weekly, biweekly and triweekly cycling between all three pairwise combinations of herbicides and continuously to each of the three herbicides. We explored the impacts of herbicide cycling on the rate of resistance evolution, the level of resistance selected, the cost of resistance and the degree of generality (cross-resistance) observed. Herbicide cycling resulted in a diversity of outcomes: preventing evolution of resistance for some combinations of herbicides, having no impacts for others and increasing rates of resistance evolution in some instances. Weekly cycling of atrazine and carbetamide resulted in selection of a generalist population. This population had a higher level of resistance, and this generalist resistance was associated with a cost. The level of resistance selected did not vary amongst other regimes. Costs of resistance were generally highest when cycling was more frequent. Our data suggest that the effects of herbicide cycling on the evolution of resistance may be more complex and less favourable than generally assumed

Exploring the population genetic consequences of the colonization process with spatio-temporally explicit models: insights from coupled ecological, demographic and genetic models in montane grasshoppers

Understanding the genetic consequences of shifting species distributions is critical for evaluating the impact of climate-induced distributional changes. However, the demographic expansion associated with the colonization process typically takes place across a heterogeneous environment, with population sizes and migration rates varying across the landscape. Here we describe an approach for coupling ecological-niche models (ENMs) with demographic and genetic models to explore the genetic consequences of distributional shifts across a heterogeneous landscape. Analyses of a flightless grasshopper from the sky islands of the Rocky Mountains of North America are used to show how biologically informed predictions can be generated about the genetic consequences of a colonization process across a spatially and temporally heterogeneous landscape (i.e. the suitability of habitats for the montane species differs across the landscape and is itself not static, with the displacement of contemporary populations into glacial refugia). By using (i) ENMs for current climatic conditions and the last glacial maximum to (ii) parameterize a demographic model of the colonization process, which then (iii) informs coalescent simulations, a set of models can be generated that capture different processes associated with distributional shifts. We discuss how the proposed approach for model generation can be integrated into a statistical framework for estimating key demographic parameters and testing hypotheses about the conditions for which distributional shifts may (or may not) enhance species divergence, including the importance of habitat stability, past gene-flow among currently isolated populations, and maintenance of refugial populations in multiple geographic regions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79315/1/MEC_4702_sm_Supplemental-Tables.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/79315/2/j.1365-294X.2010.04702.x.pd

Spatial intratumoral heterogeneity and temporal clonal evolution in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is among the most common malignancies, but little is known about its spatial intratumoral heterogeneity (ITH) and temporal clonal evolutionary processes. To address this, we performed multiregion whole-exome sequencing on 51 tumor regions from 13 ESCC cases and multiregion global methylation profiling for 3 of these 13 cases. We found an average of 35.8% heterogeneous somatic mutations with strong evidence of ITH. Half of the driver mutations located on the branches of tumor phylogenetic trees targeted oncogenes, including PIK3CA, NFE2L2 and MTOR, among others. By contrast, the majority of truncal and clonal driver mutations occurred in tumor-suppressor genes, including TP53, KMT2D and ZNF750, among others. Interestingly, phyloepigenetic trees robustly recapitulated the topological structures of the phylogenetic trees, indicating a possible relationship between genetic and epigenetic alterations. Our integrated investigations of spatial ITH and clonal evolution provide an important molecular foundation for enhanced understanding of tumorigenesis and progression in ESCC

The Importance of Scale for Spatial-Confounding Bias and Precision of Spatial Regression Estimators

Residuals in regression models are often spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When unmeasured confounding introduces spatial structure into the residuals, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual: one can reduce bias by fitting a spatial model only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals are independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.Comment: Published in at http://dx.doi.org/10.1214/10-STS326 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Lower genetic diversity in the limpet Patella caerulea on urban coastal structures compared to natural rocky habitats

Human-made structures are increasingly found in marine coastal habitats. The aim of the present study was to explore whether urban coastal structures can affect the genetic variation of hard-bottom species. We conducted a population genetic analysis on the limpet Patella caerulea sampled in both natural and artificial habitats along the Adriatic coast. Five microsatellite loci were used to test for differences in genetic diversity and structure among samples. Three microsatellite loci showed strong Hardy-Weinberg disequilibrium likely linked with the presence of null alleles. Genetic diversity was significantly higher in natural habitat than in artificial habitat. A weak but significant differentiation over all limpet samples was observed, but not related to the type of habitat. While the exact causes of the differences in genetic diversity deserve further investigation, these results clearly point that the expansion of urban structures can lead to genetic diversity loss at regional scales

Size-assortative mating in simultaneous hermaphrodites: an experimental test and a meta-analysis

Assortative mating by size has been argued to be widespread in the animal kingdom. However, the strength of size-assortative mating is known to vary considerably between species and the underlying mechanisms promoting this inter-specific variation remain largely unexplored. Size-assortative mating has been proposed to be particularly strong in simultaneous hermaphrodites, i.e. organisms that produce male and female gametes at the same time. Here, we build on this hypothesis by arguing that size-assortative mating mediated by sexual selection is generally stronger in reciprocally mating hermaphrodites compared with unilaterally mating species and separate-sexed organisms. We report a series of empirical tests suggesting that size-assortative mating in the unilaterally copulating freshwater snail Physa acuta is caused by spatial clustering of similar-sized individuals and not by mate choice. In addition, we present a meta-analysis testing, for the first time, the hypothesis that sexual selection-mediated size-assortative mating is stronger in reciprocally copulating simultaneous hermaphrodites. Overall, we found significant size-assortative mating across 18 tested species and substantial inter-specific variation. Importantly, part of this variation can be explained by mating type, providing support for the hypothesis that size-assortative mating is stronger in reciprocally mating hermaphrodites compared with unilaterally mating species. We highlight potential pitfalls when testing for sexual selection-mediated size-assortative mating and discuss the need for more experimental and comparative approaches in order to resolve the observed variation in the strength of size-assortative mating among species.Fil: Graham, Stuart. Université de Montpellier. Centre d’Ecologie Fonctionnelle et Evolutive; Francia. Université Paul-Valéry Montpellier; Francia. Centre National de la Recherche Scientifique; FranciaFil: Chapuis, Elodie. Université de Montpellier. Centre d’Ecologie Fonctionnelle et Evolutive; Francia. Centre National de la Recherche Scientifique; Francia. Institut de Recherche pour le Développement,. Intéractions Plantes-Microrganismes-Environement; Francia. Université Paul-Valéry Montpellier; FranciaFil: Meconcelli, Stefania. Université de Montpellier. Centre d’Ecologie Fonctionnelle et Evolutive; Francia. Centre National de la Recherche Scientifique; Francia. Università di Torino; ItaliaFil: Bonel, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Laboratorio de Zoología de Invertebrados I; Argentina. Université de Montpellier. Centre d’Ecologie Fonctionnelle et Evolutive; Francia. Université Paul-Valéry Montpellier; FranciaFil: Sartori, Kevin. Université de Montpellier. Centre d’Ecologie Fonctionnelle et Evolutive; Francia. Centre National de la Recherche Scientifique; Francia. Université Paul-Valéry Montpellier; FranciaFil: Christophe, Ananda. Université de Montpellier. Centre d’Ecologie Fonctionnelle et Evolutive; Francia. Centre National de la Recherche Scientifique; Francia. Université Paul-Valéry Montpellier; FranciaFil: Alda, Maria del Pilar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; ArgentinaFil: Patrice David. Université de Montpellier. Centre d’Ecologie Fonctionnelle et Evolutive; Francia. Centre National de la Recherche Scientifique; Francia. Université Paul-Valéry Montpellier; FranciaFil: Janicke, Tim. Université de Montpellier. Centre d’Ecologie Fonctionnelle et Evolutive; Francia. Centre National de la Recherche Scientifique; Francia. Université Paul-Valéry Montpellier; Franci