COEXISTENCE: HOW TO IDENTIFY TROPHIC TRADE-OFFS

Analyses of growth response to resource availability are the basis for inter- preting whether trophic trade-offs contribute to diversity. If different species respond most to resources that are limiting at different times, then those differences may trade off with other trophic or life-history traits that, together, help to maintain diversity. The statistical models used to infer trophic differences do not accommodate uncertainty in resources and variability in how individuals use resources. We provide hierarchical models for resource- growth responses that accommodate stochasticity in parameters and in data, despite the fact that causes are typically unknown. A complex joint posterior distribution taken over > 102 parameters is readily integrated to provide a comprehensive accounting of uncertainty in the growth response, together with a small number of hyperparameters that summarize the population response. An application involving seedling growth response to light avail- ability shows that large trophic differences among species suggested by traditional models can be an artifact of the assumption that all individuals respond identically. The hierarchical analysis indicates broad trophic overlap, with the implication that slow dynamics play a more important role in preserving diversity than is widely believed.

[1]  Dani Gamerman,et al.  Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference , 1997 .

[2]  H. Godfray,et al.  Host-feeding strategies of parasitoid wasps , 1993, Evolutionary Ecology.

[3]  C. Krebs,et al.  What Drives the 10-year Cycle of Snowshoe Hares? , 2001 .

[4]  T. Sharkey,et al.  Contribution of Metabolites of Photosynthesis to Postillumination CO(2) Assimilation in Response to Lightflects. , 1986, Plant physiology.

[5]  D. Tilman Competition and Biodiversity in Spatially Structured Habitats , 1994 .

[6]  James S. Clark,et al.  UNCERTAINTY AND VARIABILITY IN DEMOGRAPHY AND POPULATION GROWTH: A HIERARCHICAL APPROACH , 2003 .

[7]  Richard Levins,et al.  Coexistence in a Variable Environment , 1979, The American Naturalist.

[8]  S. E. Hills,et al.  Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling , 1990 .

[9]  F. Stuart Chapin,et al.  The Ecology and Economics of Storage in Plants , 1990 .

[10]  S Pacala,et al.  Long-Term Studies of Vegetation Dynamics , 2001, Science.

[11]  L. Oksanen,et al.  Are lemmings prey or predators? , 2000, Nature.

[12]  C. S. Holling The components of prédation as revealed by a study of small-mammal prédation of the European pine sawfly. , 1959 .

[13]  D. Ellsworth,et al.  Possible explanation of the disparity between the in vitro and in vivo measurements of Rubisco activity: a study in loblolly pine grown in elevated pCO2. , 2001, Journal of experimental botany.

[14]  Craig Loehle,et al.  Tree life history strategies: the role of defenses , 1988 .

[15]  Adrian F. M. Smith,et al.  Sampling-Based Approaches to Calculating Marginal Densities , 1990 .

[16]  John A. Silander,et al.  Sapling growth as a function of resources in a north temperate forest , 1994 .

[17]  S. Pacala,et al.  Forest models defined by field measurements : Estimation, error analysis and dynamics , 1996 .

[18]  Robert W. Pearcy,et al.  The functional morphology of light capture and carbon gain in the Redwood forest understorey plant Adenocaulon bicolor Hook , 1998 .

[19]  D. Ellsworth Seasonal CO(2) assimilation and stomatal limitations in a Pinus taeda canopy. , 2000, Tree physiology.

[20]  A. Gelfand,et al.  Identifiability, Improper Priors, and Gibbs Sampling for Generalized Linear Models , 1999 .

[21]  Aaron M. Ellison,et al.  AN INTRODUCTION TO BAYESIAN INFERENCE FOR ECOLOGICAL RESEARCH AND ENVIRONMENTAL , 1996 .

[22]  A. Glimskär,et al.  Relative Nitrogen Limitation at Steady-state Nutrition as a Determinant of Plasticity in Five Grassland Plant Species , 1999 .

[23]  James S. Clark,et al.  Disturbance and tree life history on the shifting mosaic landscape , 1991 .

[24]  R. Kobe LIGHT GRADIENT PARTITIONING AMONG TROPICAL TREE SPECIES THROUGH DIFFERENTIAL SEEDLING MORTALITY AND GROWTH , 1999 .

[25]  N. Tumosa,et al.  Relationships between growth, photosynthesis and competitive interactions for a C3 and C4 plant , 1981, Oecologia.

[26]  Bradley P. Carlin,et al.  BAYES AND EMPIRICAL BAYES METHODS FOR DATA ANALYSIS , 1996, Stat. Comput..

[27]  D. Tilman Plant Strategies and the Dynamics and Structure of Plant Communities. (MPB-26), Volume 26 , 1988 .

[28]  R. Paine Food Web Complexity and Species Diversity , 1966, The American Naturalist.

[29]  Taylor,et al.  Dynamical role of predators in population cycles of a forest insect: An experimental test , 1999, Science.

[30]  S. Hubbell,et al.  The unified neutral theory of biodiversity and biogeography at age ten. , 2011, Trends in ecology & evolution.

[31]  C. Canham,et al.  Sapling growth in response to light and nitrogen availability in a southern New England forest , 2000 .

[32]  F. Bazzaz The Physiological Ecology of Plant Succession , 1979 .

[33]  J. Connell,et al.  Mechanisms of Succession in Natural Communities and Their Role in Community Stability and Organization , 1977, The American Naturalist.

[34]  S. Pacala,et al.  Herbivores and Plant Diversity , 1992, The American Naturalist.

[35]  R. May,et al.  Stability and Complexity in Model Ecosystems , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[36]  S. Running,et al.  Temporal and Spatial Variations in the Water Status of Forest Trees , 1978 .

[37]  Jay M. Ver Hoef,et al.  Parametric Empirical Bayes Methods for Ecological Applications , 1996 .

[38]  David B. Dunson,et al.  Bayesian Data Analysis , 2010 .