Multi-model analysis of tree competition along environmental gradients in southern New England forests.

Robust predictions of competitive interactions among canopy trees and variation in tree growth along environmental gradients represent key challenges for the management of mixed-species, uneven-aged forests. We analyzed the effects of competition on tree growth along environmental gradients for eight of the most common tree species in southern New England and southeastern New York using forest inventory and analysis (FIA) data, information theoretic decision criteria, and multi-model inference to evaluate models. The suite of models estimated growth of individual trees as a species-specific function of average potential diameter growth, tree diameter at breast height, local environmental conditions, and crowding by neighboring trees. We used ordination based on the relative basal area of species to generate a measure of site conditions in each plot. Two ordination axes were consistent with variation in species abundance along moisture and fertility gradients. Estimated potential growth varied along at least one of these axes for six of the eight species; peak relative abundance of less shade-tolerant species was in all cases displaced away from sites where they showed maximum potential growth. Our crowding functions estimate the strength of competitive effects of neighbors; only one species showed support for the hypothesis that all species of competitors have equivalent effects on growth. The relative weight of evidence (Akaike weights) for the best models varied from a low of 0.207 for Fraxinus americana to 0.747 for Quercus rubra. In such cases, model averaging provides a more robust platform for prediction than that based solely on the best model. We show that predictions based on the selected best models dramatically overestimated differences between species relative to predictions based on the averaged set of models.     

Neighborhood analyses of canopy tree competition along environmental gradients in New England forests.

We use permanent-plot data from the USDA Forest Service's Forest Inventory and Analysis (FIA) program for an analysis of the effects of competition on tree growth along environmental gradients for the 14 most abundant tree species in forests of northern New England, USA. Our analysis estimates actual growth for each individual tree of a given species as a function of average potential diameter growth modified by three sets of scalars that quantify the effects on growth of (1) initial target tree size (dbh), (2) local environmental conditions, and (3) crowding by neighboring trees. Potential growth of seven of the 14 species varied along at least one of the two environmental axes identified by an ordination of relative abundance of species in plots. The relative abundances of a number of species were significantly displaced from sites where they showed maximum potential growth. In all of these cases, abundance was displaced to the more resource-poor end of the environmental gradient (either low fertility or low moisture). The pattern was most pronounced among early successional species, whereas late-successional species reached their greatest abundance on sites where they also showed the highest growth in the absence of competition. The analysis also provides empirical estimates of the strength of intraspecific and interspecific competitive effects of neighbors. For all but one of the species, our results led us to reject the hypothesis that all species of competitors have equivalent effects on a target species. Most of the individual pairwise interactions were strongly asymmetric. There was a clear competitive hierarchy among the four most shade-tolerant species, and a separate competitive hierarchy among the shade-intolerant species. Our results suggest that timber yield following selective logging will vary dramatically depending on the configuration of the residual canopy, because of interspecific variation in the magnitude of both the competitive effects of different species of neighbors and the competitive responses of different species of target trees to neighbors. The matrix of competition coefficients suggests that there may be clear benefits in managing for specific mixtures of species within local neighborhoods within stands.     

Frequency, not relative abundance, of temperate tree species varies along climate gradients in eastern North America

There have been many attempts to model the impacts of climate change on the distributions of temperate tree species, but empirical analyses of the effects of climate on the distribution and abundance of tree species have lagged far behind the models. Here, we used forest inventory data to characterize variation in adult tree abundance along climate gradients for the 24 most common tree species in the northeastern United States. The two components of our measure of species abundance--local frequency vs. relative abundance--showed dramatically different patterns of variation along gradients of mean annual temperature and precipitation. Local frequency (i.e., the percentage of plots in a given climate in which a species occurred) varied strongly for all 24 species, particularly as a function of temperature. Relative abundance when present in a plot, on the other hand, was effectively constant for most species right up to their estimated climatic range limits. Although the range limits for both temperature and precipitation were quite broad for all of the species, the range of climates within which a species was common (i.e., high frequency) was much narrower. Because frequency in sites within a given climate shows a strong sensitivity to temperature, at least, this suggests that the processes determining canopy tree recruitment on new sites also vary strongly with climate.     

Analysis of neighborhood dynamics of forest ecosystems using likelihood methods and modeling.

Advances in computing power in the past 20 years have led to a proliferation of spatially explicit, individual-based models of population and ecosystem dynamics. In forest ecosystems, the individual-based models encapsulate an emerging theory of "neighborhood" dynamics, in which fine-scale spatial interactions regulate the demography of component tree species. The spatial distribution of component species, in turn, regulates spatial variation in a whole host of community and ecosystem properties, with subsequent feedbacks on component species. The development of these models has been facilitated by development of new methods of analysis of field data, in which critical demographic rates and ecosystem processes are analyzed in terms of the spatial distributions of neighboring trees and physical environmental factors. The analyses are based on likelihood methods and information theory, and they allow a tight linkage between the models and explicit parameterization of the models from field data. Maximum likelihood methods have a long history of use for point and interval estimation in statistics. In contrast, likelihood principles have only more gradually emerged in ecology as the foundation for an alternative to traditional hypothesis testing. The alternative framework stresses the process of identifying and selecting among competing models, or in the simplest case, among competing point estimates of a parameter of a model. There are four general steps involved in a likelihood analysis: (1) model specification, (2) parameter estimation using maximum likelihood methods, (3) model comparison, and (4) model evaluation. Our goal in this paper is to review recent developments in the use of likelihood methods and modeling for the analysis of neighborhood processes in forest ecosystems. We will focus on a single class of processes, seed dispersal and seedling dispersion, because recent papers provide compelling evidence of the potential power of the approach, and illustrate some of the statistical challenges in applying the methods.