William F. Fagan
Other affiliations: University of Miami, Arizona State University, University of Arizona ...read more
Bio: William F. Fagan is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Population & Biological dispersal. The author has an hindex of 66, co-authored 274 publications receiving 22644 citations. Previous affiliations of William F. Fagan include University of Miami & Arizona State University.
Papers published on a yearly basis
01 Sep 2011
Max Planck Society1, National University of Cordoba2, Centre national de la recherche scientifique3, Macquarie University4, University of Paris-Sud5, University of Western Sydney6, University of Minnesota7, VU University Amsterdam8, University of Arizona9, University of California, Berkeley10, University of Guelph11, Australian National University12, University of Innsbruck13, University of Leeds14, University of Groningen15, Universidade Federal do Rio Grande do Sul16, University of Cape Town17, University of Wollongong18, New Jersey Institute of Technology19, Centro Agronómico Tropical de Investigación y Enseñanza20, Lawrence Berkeley National Laboratory21, University of Alaska Fairbanks22, University of Cambridge23, Kansas State University24, Helmholtz Centre for Environmental Research - UFZ25, Arizona State University26, University of Giessen27, Autonomous University of Barcelona28, University of Maryland, College Park29, Universidad del Tolima30, University of São Paulo31, University of La Réunion32, University of York33, University of Sydney34, Harvard University35, Goethe University Frankfurt36, University of Sheffield37, University of Ulm38, State University of Campinas39, Kenyon College40, Royal Botanic Gardens41, University of Florida42, University of Oldenburg43, University of Nebraska–Lincoln44, Tohoku University45, Northern Arizona University46, University of Wisconsin–Eau Claire47, Naturalis48, James Cook University49, Institut national de la recherche agronomique50, Newcastle University51, University of New South Wales52, Leipzig University53, Columbia University54, Estonian University of Life Sciences55, Polish Academy of Sciences56, Moscow State University57, Kyushu University58, Wageningen University and Research Centre59, Spanish National Research Council60, University of Regensburg61, University of Rennes62, Université du Québec à Trois-Rivières63, Potsdam Institute for Climate Impact Research64, Technical University of Denmark65, University of California, Los Angeles66, Hokkaido University67, Université de Sherbrooke68, Syracuse University69, Empresa Brasileira de Pesquisa Agropecuária70, University of Aberdeen71, Michigan State University72, Oak Ridge National Laboratory73, University of Leicester74, Utah State University75, Smithsonian Institution76, University of Missouri77
TL;DR: TRY as discussed by the authors is a global database of plant traits, including morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs, which can be used for a wide range of research from evolutionary biology, community and functional ecology to biogeography.
Abstract: Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.
TL;DR: In both lakes and terrestrial systems, herbivores should have low growth efficiencies when consuming autotrophs with typical carbon-to-nutrient ratios and stoichiometric constraints on herbivore growth appear to be qualitatively similar and widespread in both environments.
Abstract: Biological and environmental contrasts between aquatic and terrestrial systems have hindered analyses of community and ecosystem structure across Earth's diverse habitats. Ecological stoichiometry1,2 provides an integrative approach for such analyses, as all organisms are composed of the same major elements (C, N, P) whose balance affects production, nutrient cycling, and food-web dynamics3,4. Here we show both similarities and differences in the C:N:P ratios of primary producers (autotrophs) and invertebrate primary consumers (herbivores) across habitats. Terrestrial food webs are built on an extremely nutrient-poor autotroph base with C:P and C:N ratios higher than in lake particulate matter, although the N:P ratios are nearly identical. Terrestrial herbivores (insects) and their freshwater counterparts (zooplankton) are nutrient-rich and indistinguishable in C:N:P stoichiometry. In both lakes and terrestrial systems, herbivores should have low growth efficiencies (10–30%) when consuming autotrophs with typical carbon-to-nutrient ratios. These stoichiometric constraints on herbivore growth appear to be qualitatively similar and widespread in both environments.
TL;DR: It is hypothesized that the continuous generation of variation in the rDNA may also play a role in how species interactions develop in ecosystems under different conditions of energy input and nutrient supply.
Abstract: Ecological stoichiometry is the study of the balance of multiple chemical elements in ecological interactions. This paper reviews recent findings in this area and seeks to broaden the stoichiometric concept for use in evolutionary studies, in integrating ecological dynamics with cellular and genetic mechanisms, and in developing a unified means for studying diverse organisms in diverse habitats. This broader approach would then be considered “biological stoichiometry”. Evidence supporting a hypothesised connection between the C:N:P stoichiometry of an organism and its growth rate (the “growth rate hypothesis”) is reviewed. Various data indicate that rapidly growing organisms commonly have low biomass C:P and N:P ratios. Evidence is then discussed suggesting that low C:P and N:P ratios in rapidly growing organisms reflect increased allocation to P-rich ribosomal RNA (rRNA), as rapid protein synthesis by ribosomes is required to support fast growth. Indeed, diverse organisms (bacteria, copepods, fishes, others) exhibit increased RNA levels when growing actively. This implies that evolutionary processes that generate, directly or indirectly, variation in a major life history trait (specific growth rate) have consequences for ecological dynamics due to their effects on organismal elemental composition. Genetic mechanisms by which organisms generate high RNA, high growth rate phenotypes are discussed next, focusing on the structure and organisation of the ribosomal RNA genes (the “rDNA”). In particular, published studies of a variety of taxa suggest an association between growth rate and variation in the length and content of the intergenic spacer (IGS) region of the rDNA tandem repeat unit. In particular, under conditions favouring increased growth or yield, the number of repeat units (“enhancers”) increases (and the IGS increases in length), and transcription rates of rRNA increase. In addition, there is evidence in the literature that increased numbers of copies of rDNA genes are associated with increased growth and production. Thus, a combination of genetic mechanisms may be responsible for establishing the growth potential, and thus the RNA allocation and C:N:P composition, of an organism. Furthermore, various processes, during both sexual and asexual reproduction, can generate variation in the rDNA to provide the raw material for selection and to generate ecologically significant variation in C:N:P stoichiometry. This leads us to hypothesize that the continuous generation of such variation may also play a role in how species interactions develop in ecosystems under different conditions of energy input and nutrient supply.
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements.
Abstract: Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
TL;DR: The close relationship between P and RNA contents indicates that ribosomes themselves represent a biogeochemically significant repository of P in ecosystems and that allocation of P to ribosome generation is a central process in biological production in ecological systems.
Abstract: Biological stoichiometry provides a mechanistic theory linking cellular and biochemical features of co-evolving biota with constraints imposed by ecosystem energy and nutrient inputs. Thus, understanding variation in biomass carbon : nitrogen : phosphorus (C : N : P) stoichiometry is a major priority for integrative biology. Among various factors affecting organism stoichiometry, differences in C : P and N : P stoichiometry have been hypothesized to reflect organismal P-content because of altered allocation to P-rich ribosomal RNA at different growth rates (the growth rate hypothesis, GRH). We tested the GRH using data for microbes, insects, and crustaceans and we show here that growth, RNA content, and biomass P content are tightly coupled across species, during ontogeny, and under physiological P limitation. We also show, however, that this coupling is relaxed when P is not limiting for growth. The close relationship between P and RNA contents indicates that ribosomes themselves represent a biogeochemically significant repository of P in ecosystems and that allocation of P to ribosome generation is a central process in biological production in ecological systems.
TL;DR: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols used xiii 1.
Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to
TL;DR: This work has developed a quantitative theory for how metabolic rate varies with body size and temperature, and predicts how metabolic theory predicts how this rate controls ecological processes at all levels of organization from individuals to the biosphere.
Abstract: Metabolism provides a basis for using first principles of physics, chemistry, and biology to link the biology of individual organisms to the ecology of populations, communities, and ecosystems. Metabolic rate, the rate at which organisms take up, transform, and expend energy and materials, is the most fundamental biological rate. We have developed a quantitative theory for how metabolic rate varies with body size and temperature. Metabolic theory predicts how metabolic rate, by setting the rates of resource uptake from the environment and resource allocation to survival, growth, and reproduction, controls ecological processes at all levels of organization from individuals to the biosphere. Examples include: (1) life history attributes, including devel- opment rate, mortality rate, age at maturity, life span, and population growth rate; (2) population interactions, including carrying capacity, rates of competition and predation, and patterns of species diversity; and (3) ecosystem processes, including rates of biomass production and respiration and patterns of trophic dynamics. Data compiled from the ecological literature strongly support the theoretical predictions. Even- tually, metabolic theory may provide a conceptual foundation for much of ecology, just as genetic theory provides a foundation for much of evolutionary biology.
01 Jan 2016
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