Showing papers by "Brian J. Enquist published in 2009"

Opposing assembly mechanisms in a Neotropical dry forest: implications for phylogenetic and functional community ecology

Abstract: Species diversity is promoted and maintained by ecological and evolutionary processes operating on species attributes through space and time. The degree to which variability in species function regulates distribution and promotes coexistence of species has been debated. Previous work has attempted to quantify the relative importance of species function by using phylogenetic relatedness as a proxy for functional similarity. The key assumption of this approach is that function is phylogenetically conserved. If this assumption is supported, then the phylogenetic dispersion in a community should mirror the functional dispersion. Here we quantify functional trait dispersion along several key axes of tree life-history variation and on multiple spatial scales in a Neotropical dry-forest community. We next compare these results to previously reported patterns of phylogenetic dispersion in this same forest. We find that, at small spatial scales, coexisting species are typically more functionally clustered than expected, but traits related to adult and regeneration niches are overdispersed. This outcome was repeated when the analyses were stratified by size class. Some of the trait dispersion results stand in contrast to the previously reported phylogenetic dispersion results. In order to address this inconsistency we examined the strength of phylogenetic signal in traits at different depths in the phylogeny. We argue that: (1) while phylogenetic relatedness may be a good general multivariate proxy for ecological similarity, it may have a reduced capacity to depict the functional mechanisms behind species coexistence when coexisting species simultaneously converge and diverge in function; and (2) the previously used metric of phylogenetic signal provided erroneous inferences about trait dispersion when married with patterns of phylogenetic dispersion.

A general quantitative theory of forest structure and dynamics

Abstract: We present the first part of a quantitative theory for the structure and dynamics of forests at demographic and resource steady state The theory uses allometric scaling relations, based on metabolism and biomechanics, to quantify how trees use resources, fill space, and grow These individual-level traits and properties scale up to predict emergent properties of forest stands, including size–frequency distributions, spacing relations, resource flux rates, and canopy configurations Two insights emerge from this analysis: (i) The size structure and spatial arrangement of trees in the entire forest are emergent manifestations of the way that functionally invariant xylem elements are bundled together to conduct water and nutrients up from the trunks, through the branches, to the leaves of individual trees (ii) Geometric and dynamic properties of trees in a forest and branches in trees scale identically, so that the entire forest can be described mathematically and behaves structurally and functionally like a scaled version of the branching networks in the largest tree This quantitative framework uses a small number of parameters to predict numerous structural and dynamical properties of idealized forests

Extensions and evaluations of a general quantitative theory of forest structure and dynamics

Abstract: Here, we present the second part of a quantitative theory for the structure and dynamics of forests under demographic and resource steady state. The theory is based on individual-level allometric scaling relations for how trees use resources, fill space, and grow. These scale up to determine emergent properties of diverse forests, including size-frequency distributions, spacing relations, canopy configurations, mortality rates, population dynamics, successional dynamics, and resource flux rates. The theory uniquely makes quantitative predictions for both stand-level scaling exponents and normalizations. We evaluate these predictions by compiling and analyzing macroecological datasets from several tropical forests. The close match between theoretical predictions and data suggests that forests are organized by a set of very general scaling rules. Our mechanistic theory is based on allometric scaling relations, is complementary to "demographic theory," but is fundamentally different in approach. It provides a quantitative baseline for understanding deviations from predictions due to other factors, including disturbance, variation in branching architecture, asymmetric competition, resource limitation, and other sources of mortality, which are not included in the deliberately simplified theory. The theory should apply to a wide range of forests despite large differences in abiotic environment, species diversity, and taxonomic and functional composition.

Taking species abundance distributions beyond individuals

Abstract: The species abundance distribution (SAD) is one of the few universal patterns in ecology. Research on this fundamental distribution has primarily focused on the study of numerical counts, irrespective of the traits of individuals. Here we show that considering a set of Generalized Species Abundance Distributions (GSADs) encompassing several abundance measures, such as numerical abundance, biomass and resource use, can provide novel insights into the structure of ecological communities and the forces that organize them. We use a taxonomically diverse combination of macroecological data sets to investigate the similarities and differences between GSADs. We then use probability theory to explore, under parsimonious assumptions, theoretical linkages among them. Our study suggests that examining different GSADs simultaneously in natural systems may help with assessing determinants of community structure. Broadening SADs to encompass multiple abundance measures opens novel perspectives in biodiversity research and warrants future empirical and theoretical developments.

Advancing the metabolic theory of biodiversity.

Abstract: A component of metabolic scaling theory has worked towards understanding the influence of metabolism over the generation and maintenance of biodiversity. Specific models within this 'metabolic theory of biodiversity' (MTB) have addressed temperature gradients in speciation rate and species richness, but the scope of MTB has been questioned because of empirical departures from model predictions. In this study, we first show that a generalized MTB is not inconsistent with empirical patterns and subsequently implement an eco-evolutionary MTB which has thus far only been discussed qualitatively. More specifically, we combine a functional trait (body mass) approach and an environmental gradient (temperature) with a dynamic eco-evolutionary model that builds on the current MTB. Our approach uniquely accounts for feedbacks between ecological interactions (size-dependent competition and predation) and evolutionary rates (speciation and extinction). We investigate a simple example in which temperature influences mutation rate, and show that this single effect leads to dynamic temperature gradients in macroevolutionary rates and community structure. Early in community evolution, temperature strongly influences speciation and both speciation and extinction strongly influence species richness. Through time, niche structure evolves, speciation and extinction rates fall, and species richness becomes increasingly independent of temperature. However, significant temperature-richness gradients may persist within emergent functional (trophic) groups, especially when niche breadths are wide. Thus, there is a strong signal of both history and ecological interactions on patterns of species richness across temperature gradients. More generally, the successful implementation of an eco-evolutionary MTB opens the perspective that a process-based MTB can continue to emerge through further development of metabolic models that are explicit in terms of functional traits and environmental gradients.

Above-ground forest biomass is not consistently related to wood density in tropical forests

Abstract: Aim It is increasingly accepted that the mean wood density of trees within a forest is tightly coupled to above-ground forest biomass. It is unknown, however, if a positive relationship between forest biomass and mean community wood density is a general phenomenon across forests. Understanding spatial variation in biomass as a function of wood density both within and among forests is important for predicting changes in stored carbon in response to global change, and here we evaluated the generality of a positive biomass‐wood density relationship within and among six tropical forests. Location Costa Rica, Panama, Puerto Rico and Ecuador.

Improved abundance prediction from presence-absence data

Abstract: Aim Many ecological surveys record only the presence or absence of species in the cells of a rectangular grid. Ecologists have investigated methods for using these data to predict the total abundance of a species from the number of grid cells in which the species is present. Our aim is to improve such predictions by taking account of the spatial pattern of occupied cells, in addition to the number of occupied cells. Innovation We extend existing prediction models to include a spatial clustering variable. The extended models can be viewed as combining two macroecological regularities, the abundance‐occupancy regularity and a spatial clustering regularity. The models are estimated using data from five tropical forest censuses, including three Panamanian censuses (4, 6 and 50 ha), one Costa Rican census (16 ha) and one Puerto Rican census (16 ha). A serpentine grassland census (8 × 8 m) from northern California is also studied. Main conclusions Taking account of the spatial clustering of occupied cells improves abundance prediction from presence‐absence data, reducing the mean square error of log-predictions by roughly 54% relative to a benchmark Poisson predictor and by roughly 34% relative to current prediction methods. The results have high statistical significance.

Controls on Radial Growth of Mountain Big Sagebrush and Implications for Climate Change

Abstract: Mountain big sagebrush (Artemisia tridentata Nutt. ssp. vaseyana) covers large areas in arid regions of western North America. Climate-change models predict a decrease in the range of sagebrush, but few studies have examined details of predicted changes on sagebrush growth and the potential impacts of these changes on the commu- nity. We analyzed effects of temperature, precipitation, and snow depth on sagebrush annual ring width for 1969 to 2007 in the Gunnison Basin of Colorado. Temperature at all times of year except winter had negative correlations with ring widths; summer temperature had the strongest negative relationship. Ring widths correlated positively with precipita- tion in various seasons except summer; winter precipitation had the strongest relationship with growth. Maximum snow depth also correlated positively and strongly with ring width. Multiple regressions showed that summer temperature and either winter precipitation or maximum snow depth, which recharges deeper soil horizons, are both important in controlling growth. Overall, water stress and perhaps especially maximum snow depth appear to limit growth of this species. With predicted increases in temperature and probable reduced snow depth, sagebrush growth rates are likely to decrease. If so, sagebrush populations and cover may decline, which may have substantial effects on community com- position and carbon balance.

Comment on Coomes et al. 'Scaling of xylem vessels and veins within the leaves of oak species'.

Abstract: [Coomes et al. (2008)][1] purport to test the predictions of the plant scaling model of [West et al. (1999)][2] by examining the scaling of xylem dimensions in 10 species of oaks ( Quercus spp.). While we commend their efforts to gather much needed data on the scaling of xylem dimensions in leaves,

PERSPECTIVE Taking species abundance distributions beyond individuals

Abstract: The species abundance distribution (SAD) is one of the few universal patterns in ecology. Research on this fundamental distribution has primarily focused on the study of numerical counts, irrespective of the traits of individuals. Here we show that considering a set of Generalized Species Abundance Distributions (GSADs) encompassing several abundance measures, such as numerical abundance, biomass and resource use, can provide novel insights into the structure of ecological communities and the forces that organize them. We use a taxonomically diverse combination of macroecological data sets to investigate the similarities and differences between GSADs. We then use probability theory to explore, under parsimonious assumptions, theoretical linkages among them. Our study suggests that examining different GSADs simultaneously in natural systems may help with assessing determinants of community structure. Broadening SADs to encompass multiple abundance measures opens novel perspectives in biodiversity research and warrants future empirical and theoretical developments.