01747nam a2200157   4500008004100000020001500041245003600056210003600092250000800128260003700136520132400173653001201497653001101509100002501520856004401545       2008                        eng d  a069112522800aEcological Models and Data in R0 aEcological Models and Data in R  a508  bPrinceton University PresscJuly3 a\_Ecological Models and Data in R\_ is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive experience teaching these techniques to graduate students in ecology, Benjamin Bolker shows how to choose among and construct statistical models for data, estimate their parameters and confidence limits, and interpret the results. The book also covers statistical frameworks, the philosophy of statistical modeling, and critical mathematical functions and probability distributions. It requires no programming background–only basic calculus and statistics. * Practical, beginner-friendly introduction to modern statistical techniques for ecology using the programming language R * Step-by-step instructions for fitting models to messy, real-world data * Balanced view of different statistical approaches * Wide coverage of techniques–from simple (distribution fitting) to complex (state-space modeling) * Techniques for data manipulation and graphical display * Companion Web site with data and R code for all examples10aecology10amodels1 aBolker, Benjamin, M.  uhttp://www.worldcat.org/isbn/069112522802378nas a2200265   4500008004100000245009300041210006900134260004100203300001400244490000600258520156500264653001901829653000801848653000901856653001201865653001501877100002301892700002901915700002301944700002601967700002501993700002202018700002102040856005102061       2009                        eng d00aA Disease-Mediated Trophic Cascade in the Serengeti and its Implications for Ecosystem C0 aDiseaseMediated Trophic Cascade in the Serengeti and its Implica  bPublic Library of SciencecSeptember  ae1000210+0 v73 aTree cover is a fundamental structural characteristic and driver of ecosystem processes in terrestrial ecosystems, and trees are a major global carbon (C) sink. Fire and herbivores have been hypothesized to play dominant roles in regulating trees in African savannas, but the evidence for this is conflicting. Moving up a trophic scale, the factors that regulate fire occurrence and herbivores, such as disease and predation, are poorly understood for any given ecosystem. We used a Bayesian state-space model to show that the wildebeest population irruption that followed disease (rinderpest) eradication in the Serengeti ecosystem of East Africa led to a widespread reduction in the extent of fire and an ongoing recovery of the tree population. This supports the hypothesis that disease has played a key role in the regulation of this ecosystem. We then link our state-space model with theoretical and empirical results quantifying the effects of grazing and fire on soil carbon to predict that this cascade may have led to important shifts in the size of pools of C stored in soil and biomass. Our results suggest that the dynamics of herbivores and fire are tightly coupled at landscape scales, that fire exerts clear top-down effects on tree density, and that disease outbreaks in dominant herbivores can lead to complex trophic cascades in savanna ecosystems. We propose that the long-term status of the Serengeti and other intensely grazed savannas as sources or sinks for C may be fundamentally linked to the control of disease outbreaks and poaching.10aclimate-change10aco210afire10agrazing10avegetation1 aHoldo, Ricardo, M.1 aSinclair, Anthony, R. E.1 aDobson, Andrew, P.1 aMetzger, Kristine, L.1 aBolker, Benjamin, M.1 aRitchie, Mark, E.1 aHolt, Robert, D.  uhttp://dx.doi.org/10.1371/journal.pbio.1000210