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 & Complex network. The organization has 558 authors who have published 4558 publications receiving 396015 citations. The organization is also known as: SFI.

Open Science principles for accelerating trait-based science across the Tree of Life

Abstract: Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Interspecific integration of trait dimensions at local scales: the plant phenotype as an integrated network

Abstract: Summary Plant phenotypic diversity is shaped by the interplay of trade-offs and constraints in evolution. Closely integrated groups of traits (i.e. trait dimensions) are used to classify plant phenotypic diversity into plant strategies, but we do not know the degree of interdependence among trait dimensions. To assess how selection has shaped the phenotypic space, we examine whether trait dimensions are independent. We gathered data on saplings of 24 locally coexisting tree species in a temperate forest, and examined the correlation structure of 20 leaf, branch, stem and root traits. These traits fall into three well-established trait dimensions (the leaf economic spectrum, the wood spectrum and Corner's Rules) that characterize vital plant functions: resource acquisition, sap transport, mechanical support and canopy architecture. Using ordinations, network analyses and Mantel tests, we tested whether the sapling phenotype of these tree species is organized along independent trait dimensions. Across species, the sapling phenotype is not structured into clear trait dimensions. The trait relationships defining trait dimensions are either weak or absent and do not dominate the correlation structure of the sapling phenotype as a whole. Instead traits from the three commonly recognized trait dimensions are organized into an integrated trait network. The effect of phylogeny on trait correlations is minimal. Our results indicate that trait dimensions apparent in broad-based interspecific surveys do not hold up among locally coexisting species. Furthermore, architectural traits appear central to the phenotypic network, suggesting a pivotal role for branching architecture in linking resource acquisition, mechanical support and hydraulic functions. Synthesis. Our study indicates that local and global patterns of phenotypic integration differ and calls into question the use of trait dimensions at local scales. We propose that a network approach to assessing plant function more effectively reflects the multiple trade-offs and constraints shaping the phenotype in locally co-occurring species.

Self-Organized Criticality, Evolution and the Fossil Extinction Record

Abstract: Statistical analysis indicates that the fossil extinction record is compatible with a distribution of extinction events whose frequency is related to their size by a power law with exponent т ≈ 2. This result is in agreement with predictions based on self-organized critical models of extinction, and might well be taken as evidence of critical behaviour in terrestrial evolution. We argue however that there is a much simpler explanation for the appearance of a power law in terms of extinctions caused by stresses (either biotic or abiotic) to which species are subjected by their environment. We give an explicit model of this process and discuss its properties and implications for the interpretation of the fossil record.

A measure of landscapes

Abstract: This paper introduces a statistical fitness landscape analysis, based on Weinberger's random walk method and on a time series analysis known as the Box-Jenkins approach, to measure and express the correlation structure of fitness landscapes. The analysis has some additions to and advantages over previous methods for measuring this structure. The analysis is demonstrated on fitness landscapes constructed with Kauffman's NK-model, using two operators (point mutation and a form of crossover) and a combination of the two. Furthermore, the predictive value of the method is shown.

When do generalized entropies apply? How phase space volume determines entropy

Abstract: We show how the dependence of phase space volume Ω(N) on system size N uniquely determines the extensive entropy of a classical system. We give a concise criterion when this entropy is not of Boltzmann-Gibbs type but has to assume a generalized (non-additive) form. We show that generalized entropies can only exist when the dynamically (statistically) relevant fraction of degrees of freedom in the system vanishes in the thermodynamic limit. These are systems where the bulk of the degrees of freedom is frozen and statistically inactive. Systems governed by generalized entropies are therefore systems whose phase space volume effectively collapses to a lower-dimensional "surface". We illustrate these results in three concrete examples: accelerating random walks, a microcanonical spin system on networks and constrained binomial processes. These examples suggest that a wide class of systems with "surface-dominant" statistics might in fact require generalized entropies, including self-organized critical systems such as sandpiles, anomalous diffusion, and systems with topological defects such as vortices, domains, or instantons.