Santa Fe Institute

About: Santa Fe Institute is a nonprofit organization based out in Santa Fe, New Mexico, United States. It is known for research contribution in the topics: Population & Context (language use). The organization has 558 authors who have published 4558 publications receiving 396015 citations. The organization is also known as: SFI.

Temperature dependence of trophic interactions are driven by asymmetry of species responses and foraging strategy

Abstract: Summary Environmental temperature has systematic effects on rates of species interactions, primarily through its influence on organismal physiology. We present a mechanistic model for the thermal response of consumer–resource interactions. We focus on how temperature affects species interactions via key traits – body velocity, detection distance, search rate and handling time – that underlie per capita consumption rate. The model is general because it applies to all foraging strategies: active-capture (both consumer and resource body velocity are important), sit-and-wait (resource velocity dominates) and grazing (consumer velocity dominates). The model predicts that temperature influences consumer–resource interactions primarily through its effects on body velocity (either of the consumer, resource or both), which determines how often consumers and resources encounter each other, and that asymmetries in the thermal responses of interacting species can introduce qualitative, not just quantitative, changes in consumer–resource dynamics. We illustrate this by showing how asymmetries in thermal responses determine equilibrium population densities in interacting consumer–resource pairs. We test for the existence of asymmetries in consumer–resource thermal responses by analysing an extensive database on thermal response curves of ecological traits for 309 species spanning 15 orders of magnitude in body size from terrestrial, marine and freshwater habitats. We find that asymmetries in consumer–resource thermal responses are likely to be a common occurrence. Overall, our study reveals the importance of asymmetric thermal responses in consumer–resource dynamics. In particular, we identify three general types of asymmetries: (i) different levels of performance of the response, (ii) different rates of response (e.g. activation energies) and (iii) different peak or optimal temperatures. Such asymmetries should occur more frequently as the climate changes and species' geographical distributions and phenologies are altered, such that previously noninteracting species come into contact. By using characteristics of trophic interactions that are often well known, such as body size, foraging strategy, thermy and environmental temperature, our framework should allow more accurate predictions about the thermal dependence of consumer–resource interactions. Ultimately, integration of our theory into models of food web and ecosystem dynamics should be useful in understanding how natural systems will respond to current and future temperature change.

The fractal nature of nature: power laws, ecological complexity and biodiversity

Abstract: Underlying the diversity of life and the complexity of ecology is order that reflects the operation of fundamental physical and biological processes. Power laws describe empirical scaling relationships that are emergent quantitative features of biodiversity. These features are patterns of structure or dynamics that are self-similar or fractal-like over many orders of magnitude. Power laws allow extrapolation and prediction over a wide range of scales. Some appear to be universal, occurring in virtually all taxa of organisms and types of environments. They offer clues to underlying mechanisms that powerfully constrain biodiversity. We describe recent progress and future prospects for understanding the mechanisms that generate these power laws, and for explaining the diversity of species and complexity of ecosystems in terms of fundamental principles of physical and biological science.

How dead ends undermine power grid stability

Abstract: The cheapest and thus widespread way to add new generators to a high-voltage power grid is by a simple tree-like connection scheme. However, it is not entirely clear how such locally cost-minimizing connection schemes affect overall system performance, in particular the stability against blackouts. Here we investigate how local patterns in the network topology influence a power grid's ability to withstand blackout-prone large perturbations. Employing basin stability, a nonlinear concept, we find in numerical simulations of artificially generated power grids that tree-like connection schemes--so-called dead ends and dead trees--strongly diminish stability. A case study of the Northern European power system confirms this result and demonstrates that the inverse is also true: repairing dead ends by addition of a few transmission lines substantially enhances stability. This may indicate a topological design principle for future power grids: avoid dead ends.

Variable efficacy of repeated annual influenza vaccination

Abstract: Conclusions have differed in studies that have compared vaccine efficacy in groups receiving influenza vaccine for the first time to efficacy in groups vaccinated more than once. For example, the Hoskins study [Hoskins, T. W., Davis, J. R., Smith, A. J., Miller, C. L. & Allchin, A. (1979) Lancet i, 33–35] concluded that repeat vaccination was not protective in the long term, whereas the Keitel study [Keitel, W. A., Cate, T. R., Couch, R. B., Huggins, L. L. & Hess, K. R. (1997) Vaccine 15, 1114–1122] concluded that repeat vaccination provided continual protection. We propose an explanation, the antigenic distance hypothesis, and test it by analyzing seven influenza outbreaks that occurred during the Hoskins and Keitel studies. The hypothesis is that variation in repeat vaccine efficacy is due to differences in antigenic distances among vaccine strains and between the vaccine strains and the epidemic strain in each outbreak. To test the hypothesis, antigenic distances were calculated from historical hemagglutination inhibition assay tables, and a computer model of the immune response was used to predict the vaccine efficacy of individuals given different vaccinations. The model accurately predicted the observed vaccine efficacies in repeat vaccinees relative to the efficacy in first-time vaccinees (correlation 0.87). Thus, the antigenic distance hypothesis offers a parsimonious explanation of the differences between and within the Hoskins and Keitel studies. These results have implications for the selection of influenza vaccine strains, and also for vaccination strategies for other antigenically variable pathogens that might require repeated vaccination.