Local neighborhood effects on long‐term survival of individual trees in a neotropical forest

Abstract

The survival of approximately 235 000 individual tropical trees and saplings in the 50 ha permanent plot on Barro Colorado Island (BCI), Panama was analyzed over a 13‐year interval (1982–1995) as a function of four biotic neighborhood variables: (i) total stem density; (ii) conspecific density; (iii) relative plant size; and (iv) relative species richness. These neighborhood variables were measured in annular rings of width 2.5 m, extending 30 m from a given focal plant, and in one more distant annulus at 47.5–50 m. Because survival was spatially autocorrelated, a Gibbs sampler and a Monte Carlo Markov chain method were used for fitting an autologistic regression model to obtain unbiased estimates of parameter variances for hypothesis testing. After pooling all species at the community level, results showed that all four variables had significant and often strong effects on focal plant survival. Three of the four variables had negative effects on focal plant survival; relative plant size was the only variable with a positive effect (18% increase in the survival odds ratio). The variables with a negative effect on the survival odds ratio, in order of their effect strength in the nearest annulus, were: stem density (a 70% reduction in the survival odds ratio), conspecific density (50% reduction) and species richness (13% reduction). A guild‐level analysis revealed considerable heterogeneity among guilds in their responses to these variables. For example, survival of gap species showed a much larger positive response to relative plant size than did survival of shade‐tolerant species. Survival of shrub species was positively affected by conspecific density, but canopy tree survival was negatively affected. Conspecific density negatively affected survival of rare species much more strongly than survival of common species. The neighborhood effects of conspecific density disappear within approximately 12–15 m of the focal plant. Although locally strong, the rapid spatial decay of these effects raises unanswered questions about their quantitative contribution to the maintenance of tree diversity on landscape scales in the BCI forest.

Forest tree neighborhoods are structured more by negative conspecific density dependence than by interactions among closely related species

“…However, most other studies of seedling and sapling growth and survival in forests have similarly detected density-dependent effects at scales < 30 m (Curran and Webb 2000, Hubbell et al 2001, Peters 2003, Uriarte et al 2004b, Comita and Hubbell 2009). …”

Pourquoi et où les arbres adultes meurent dans une jeune forêt tempérée? Le rôle du voisinage

“…Characteristics of tree neighbourhood are closely related to competition intensity and mortality risk (Hubbell et al, 2001;Uriarte et al, 2004). However, most of the research has been carried out on monospecific stands (Dobbertin et al, 2001;Drobyshev et al, 2007;Monserud and Sterba 1999), with relative less attention being focused on mixed forests where the effect of neighbour identity creates a much more complex picture (Hubbell et al, 2001;Yao et al, 2001;Zhao et al, 2004).…”

Quantification of neighbourhood‐dependent plant growth by Bayesian hierarchical modelling

“…Such a relationship between plant performance and neighbourhood weight is not surprising, although success in demonstrating the phenomenon has been rather variable in the past. Early work by Kira et al (1953) found the weight of regularly spaced plants to be correlated with the mean weight of the plant's six nearest neighbours, and several subsequent studies also found a relationship between plant growth and neighbourhood properties (Mithen et al 1984;Weiner 1984;Silander & Pacala 1985;Stoll et al 1994;Hubbell et al 2001;Stoll & Bergius 2005). However, such relationships have sometimes proved harder to demonstrate in the field (Martin & Ek 1984;Coomes et al 2002), especially when plants are regularly spaced (Lorimer 1983;Wimberly & Bare 1996; but see also Larocque 2002).…”

“…Although Bayesian data analysis is not yet widely used in ecology (Ellison 2004), recent applications of Bayesian techniques to spatial problems in plant ecology, including neighbourhood-dependent survival of trees in a tropical rain forest (Hubbell et al . 2001), tree fecundity (Clark et al .…”