William K. Lauenroth

Bio: William K. Lauenroth is an academic researcher from Yale University. The author has contributed to research in topics: Steppe & Bouteloua gracilis. The author has an hindex of 84, co-authored 300 publications receiving 26550 citations. Previous affiliations of William K. Lauenroth include University of Wyoming & North Dakota State University.

Quantitative effects of grazing on vegetation and soils over a global range of environments

Abstract: Multiple regression analyses were performed on a worldwide 236—site data set compiled from studies that compared species composition, aboveground net primary production (ANPP), root biomass, and soil nutrients of grazed vs. protected, ungrazed sites. The objective was to quantitatively assess factors relating to differential sensitivities of ecosystems to grazing by large herbivores. A key question in this assessment was: Do empirically based, broad—scale relationships correspond to ecological theories of plant—animal interactions and conceptual frameworks for management of the world's grazing lands? Changes in species composition with grazing were primarily a function of ANPP and the evolutionary history of grazing of the site, with level of consumption third in importance. Changes in species composition increased with increasing productivity and with longer, more intense evolutionary histories of grazing. These three variables explained >50% of the variance in the species response of grasslands or grasslands—plus—shrublands to grazing, even though methods of measurement and grazing systems varied among studies. Years of protection from grazing was a significant variable only in the model for shrublands. Similar variables entered models of change in the dominant species with grazing. As with species composition, sensitivities of change in dominant species were greater to varying ecosystem—environmental variables than to varying grazing variables, from low to high values. Increase of the dominant species under grazing were predicted under some conditions, and decreases were more likely among bunch grasses than other life—forms and more likely among perennials than annuals. The response of shrublands was different from that of grasslands, both in terms of species composition and the dominant species. Our analyses support the perception of grazing as a factor in the conversion of grasslands to less desirable shrublands, but also suggest that we may be inadvertently grazing shrublands more intensively than grasslands. Percentage differences in ANPP between grazed and ungrazed sites decreased with increasingly long evolutionary histories of grazing and increased with increasing ANPP, levels of consumption, or years of treatment. Although most effects of grazing on ANPP were negative, some were not, and the statistical models predicted increases in ANPP with grazing under conditions of long evolutionary history, low consumption, few years of treatment, and low ANPP for grasslands—plus—shrublands. The data and the models support the controversial hypothesis that grazing can increase ANPP in some situations. Similar to species variables, percentage differences in ANPP between grazed and ungrazed treatments were more sensitive to varying ecosystem—environmental variables than to varying grazing variables. Within levels not considered to be abusive "overgrazing," the geographical location where grazing occurs may be more important than how many animals are grazed or how intensively an area is grazed. Counter to the commonly held view that grazing negatively impacts root systems, there was no relationship between difference in ANPP with grazing and difference in root mass; as many positive as negative differences occurred, even though most ANPP differences were negative. Further, there was a weak relationship between change in species composition and change in ANPP, and no relationship with root mass, soil organic matter, or soil nitrogen. All three belowground variables displayed both positive and negative values in response to grazing. Current management of much of the world's grazing lands based on species composition criteria may lead to erroneous conclusions concerning the long—term ability of a system to sustain productivity.

A Generalized Model of the Effects of Grazing by Large Herbivores on Grassland Community Structure

Abstract: Current disturbance models do not adequately account for the wide range of responses by grassland plant communities to grazing by large generalist herbivores The evolutionary history of grazing, a

Primary Production of the Central Grassland Region of the United States

Abstract: Aboveground net primary production of grasslands is strongly influenced by the amount and distribution of annual precipitation. Analysis of data collected at 9500 sites throughout the central United States confirmed the overwhelming importance of water availability as a control on production. The regional spatial pattern of production reflected the east-west gradient in annual precipitation. Lowest values of aboveground net primary production were observed in the west and highest values in the east. This spatial pattern was shifted eastward during unfavorable years and westward during favorable years. Vari- ability in production among years was maximum in northern New Mexico and southwestern Kansas and decreased towards the north and south. The regional pattern of production was largely accounted for by annual precipitation. Production at the site level was explained by annual precipitation, soil water-holding capacity, and an interaction term. Our results support the inverse texture hypothesis. When precipitation is 370 mm/yr.

Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982-2006

Abstract: Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by � 60 days and in standard deviation by � 20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS

The effect of grazing on the spatial heterogeneity of vegetation

Abstract: Grazing can alter the spatial heterogeneity of vegetation, influencing ecosystem processes and biodiversity. Our objective was to identify why grazing causes increases in the spatial heterogeneity of vegetation in some cases, but decreases in others. The immediate effect of grazing on heterogeneity depends on the interaction between the spatial pattern of grazing and the pre-existing spatial pattern of vegetation. Depending on the scale of observation and on the factors that determine animal distribution, grazing patterns may be stronger or weaker than vegetation patterns, or may mirror the spatial structure of vegetation. For each possible interaction between these patterns, we make a prediction about resulting changes in the spatial heterogeneity of vegetation. Case studies from the literature support our predictions, although ecosystems characterized by strong plant-soil interactions present important exceptions. While the processes by which grazing causes increases in heterogeneity are clear, how grazing leads to decreases in heterogeneity is less so. To explore how grazing can consistently dampen the fine-scale spatial patterns of competing plant species, we built a cell-based simulation model that features two competing plant species, different grazing patterns, and different sources of vegetation pattern. Only the simulations that included neighborhood interactions as a source of vegetation pattern produced results consistent with the predictions we derived from the literature review.

The Theory of Island Biogeography

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

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Experimental Design and Data Analysis for Biologists

Abstract: An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models Multivariate techniques, including classification and ordination, are then introduced Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature The book is supported by a website that provides all data sets, questions for each chapter and links to software

Novel methods improve prediction of species' distributions from occurrence data

Abstract: Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

Effects of biodiversity on ecosystem functioning: a consensus of current knowledge

Abstract: Humans are altering the composition of biological communities through a variety of activities that increase rates of species invasions and species extinctions, at all scales, from local to global. These changes in components of the Earth's biodiversity cause concern for ethical and aesthetic reasons, but they also have a strong potential to alter ecosystem properties and the goods and services they provide to humanity. Ecological experiments, observations, and theoretical developments show that ecosystem properties depend greatly on biodiversity in terms of the functional characteristics of organisms present in the ecosystem and the distribution and abundance of those organisms over space and time. Species effects act in concert with the effects of climate, resource availability, and disturbance regimes in influencing ecosystem properties. Human activities can modify all of the above factors; here we focus on modification of these biotic controls. The scientific community has come to a broad consensus on many aspects of the re- lationship between biodiversity and ecosystem functioning, including many points relevant to management of ecosystems. Further progress will require integration of knowledge about biotic and abiotic controls on ecosystem properties, how ecological communities are struc- tured, and the forces driving species extinctions and invasions. To strengthen links to policy and management, we also need to integrate our ecological knowledge with understanding of the social and economic constraints of potential management practices. Understanding this complexity, while taking strong steps to minimize current losses of species, is necessary for responsible management of Earth's ecosystems and the diverse biota they contain.