Population and community ecology (original) (raw)

Deviations from predictions of the metabolic theory of ecology can be explained by violations of assumptions

Ecology, 2010

The metabolic theory of ecology (MTE) is based on models derived from the first principles of thermodynamics and biochemical kinetics. The MTE predicts that the relationship between temperature and species richness of ectotherms should show a specific slope. Testing the validity of this model, however, depends on whether empirical data do not violate assumptions and are obtained within contour conditions. When dealing with richness gradients, the MTE must be empirically tested only for ectothermic organisms at high organization levels and when their body size as well as abundance does not vary with temperature gradients. Here we evaluate whether the magnitude of the deviations in slope expected from the MTE to empirical data for New World amphibians is due to the violations of model assumptions and to lack of generality due to restricting contour conditions. We found that the MTE correctly predicted biodiversity patterns only at higher levels of organization and when assumptions of the basic model were not violated. Approximately 60% of the deviations from the MTE-predicted slope across amphibian families were due to violations of the model assumptions. The hypothesis that richness patterns are a function of environmental temperature is too restrictive and does not take complex environmental and ecological processes into account. However, our results suggest that it may be possible to obtain multiple derivations of the MTE equation if idiosyncrasies in spatial and biological/ ecological issues that are essential to understanding biodiversity patterns are considered.

Testing Metabolic Theory of Ecology on the local scale: a preliminary study

Ecological Questions, 2012

Data on the density and the body mass of a single community of soil fauna were collected and metabolic rates were calculated from the literature data to test some predictions of the metabolic theory of ecology on the local scale. Part of the results are in accordance with the theory: power functions were found between the metabolic rate and the body mass, and between the density and the body mass. These two relationships have opposite exponents inducing that total population energy use is independent of the body mass. However, the exponents of the relationships were significantly different from the predicted values of |3/4|. The metabolic rate -body mass relationships yielded an exponent >0.8, while the density -body mass relationships yielded an exponent <-0.85. Our results indicate that the metabolic theory of ecology does not hold at the local level. Few studies have been carried out on the local scale and further analysis is required to validate this controversial but promising theory.

Testing the metabolic theory of ecology

Ecology Letters, 2012

The metabolic theory of ecology (MTE) predicts the effects of body size and temperature on metabolism through considerations of vascular distribution networks and biochemical kinetics. MTE has also been extended to characterise processes from cellular to global levels. MTE has generated both enthusiasm and controversy across a broad range of research areas. However, most efforts that claim to validate or invalidate MTE have focused on testing predictions. We argue that critical evaluation of MTE also requires strong tests of both its theoretical foundations and simplifying assumptions. To this end, we synthesise available information and find that MTE's original derivations require additional assumptions to obtain the full scope of attendant predictions. Moreover, although some of MTE's simplifying assumptions are well supported by data, others are inconsistent with empirical tests and even more remain untested. Further, although many predictions are empirically supported on average, work remains to explain the often large variability in data. We suggest that greater effort be focused on evaluating MTE's underlying theory and simplifying assumptions to help delineate the scope of MTE, generate new theory and shed light on fundamental aspects of biological form and function.

A GLOBAL EVALUATION OF METABOLIC THEORY AS AN EXPLANATION FOR TERRESTRIAL SPECIES RICHNESS GRADIENTS

Ecology, 2007

We compiled 46 broadscale data sets of species richness for a wide range of terrestrial plant, invertebrate, and ectothermic vertebrate groups in all parts of the world to test the ability of metabolic theory to account for observed diversity gradients. The theory makes two related predictions: (1) In-transformed richness is linearly associated with a linear, inverse transformation of annual temperature, and (2) the slope of the relationship is near -0.65. Of the 46 data sets, 14 had no significant relationship; of the remaining 32, nine were linear, meeting prediction 1. Model I (ordinary least squares, OLS) and model II (reduced major axis, RMA) regressions then tested the linear slopes against prediction 2. In the 23 data sets having nonlinear relationships between richness and temperature, split-line regression divided the data into linear components, and regressions were done on each component to test prediction 2 for subsets of the data. Of the 46 data sets analyzed in their entirety using OLS regression one was consistent with metabolic theory (meeting both predictions), and one was possibly consistent. Using RMA regression, no data sets were consistent. Of 67 analyses of prediction 2 using OLS regression on all linear data sets and subsets, two were consistent with the prediction, and four were possibly consistent. Using RMA regression, one was consistent (albeit weakly), and four were possibly consistent. We also found that the relationship between richness and temperature is both taxonomically and geographically conditional, and there is no evidence for a universal response of diversity to temperature. Meta-analyses confirmed significant heterogeneity in slopes among data sets, and the combined slopes across studies were significantly lower than the range of slopes predicted by metabolic theory based on both OLS and RMA regressions. We conclude that metabolic theory, as currently formulated, is a poor predictor of observed diversity gradients in most terrestrial systems.

TOWARD A METABOLIC THEORY OF ECOLOGY

Ecology, 2004

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 development 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.

Statistical modelling of communities and ecosystems using the LAMDA software tool

Environmental Modelling & Software, 2010

Understanding species interactions is critical to discovering community dynamics. Recently, statistical methods for estimating species interaction strengths from time series data have been developed based on multivariate auto-regressive first-order, or MAR(1), models. However, the complex coding required presents a substantial barrier for most ecologists. We have developed LAMBDA, a software program that allows users to easily fit MAR(1) models to multi-species time series data. The LAMBDA package covers: data input and transformation, selection of the interactions to include via a search algorithm and model selection, estimation of interaction parameters via conditional least squares (CLS) regression or two different maximum-likelihood (ML) algorithms, estimation of confidence intervals via bootstrapping, and computation of community stability properties using the estimated model. We describe performance tests on the variability of estimates, computation speed, and CLS versus ML estimation using simulated data.

Linking community size structure and ecosystem functioning using metabolic theory

Understanding how biogeochemical cycles relate to the structure of ecological communities is a central research question in ecology. Here we approach this problem by focusing on body size, which is an easily measured species trait that has a pervasive influence on multiple aspects of community structure and ecosystem functioning. We test the predictions of a model derived from metabolic theory using data on ecosystem metabolism and community size structure. These data were collected as part of an aquatic mesocosm experiment that was designed to simulate future environmental warming. Our analyses demonstrate significant linkages between community size structure and ecosystem functioning, and the effects of warming on these links. Specifically, we show that carbon fluxes were significantly influenced by seasonal variation in temperature, and yielded activation energies remarkably similar to those predicted based on the temperature dependencies of individual-level photosynthesis and respiration. We also show that community size structure significantly influenced fluxes of ecosystem respiration and gross primary production, particularly at the annual time-scale. Assessing size structure and the factors that control it, both empirically and theoretically, therefore promises to aid in understanding links between individual organisms and biogeochemical cycles, and in predicting the responses of key ecosystem functions to future environmental change.

Generalized linear and generalized additive models in studies of species distributions: setting the scene

Ecological Modelling, 2002

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs /GAMs modeling: from species distribution to environmental management , held in Riederalp, Switzerland, 6 Á/11 August 2001.We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling.