1 Anthropogenic changes in the global climate are shifting the potential ranges of many plant species.2 Changing climates will allow some species the opportunity to expand their range, others may experience a contraction in their potential range, while the current and future ranges of some species may not overlap. Our capacity to generalize about the threat these range shifts pose to plant diversity is limited by many sources of uncertainty.3 In this paper we summarize sources of uncertainty for migration forecasts and suggest a research protocol for making forecasts in the context of uncertainty.

We analyzed the spatial patterns among seeds, seedlings, saplings, and conspecific adult trees of the cool-temperate tree species Acer palmatum var. Matsumurae in a conifer-hardwood mixed forest in northern Japan, using two models that consider the influence of each adult within the neighborhood of the offspring. The results showed that recruitment patterns of each stage could be characterized and that significant shifts occur between successive stages. Sound seeds were more widely dispersed than unsound seeds; the mean dispersal distance (MDD) was 41.5 m for sound seeds, but only 12.6 m for unsound seeds. Most seedlings were located near conspecific adult trees, with a MDD of 14.3 m. Saplings, however, were more dispersed away from conspecific adult trees, with an MDD of more than 35 m. Light and gap distributions did not strongly affect the spatial distribution of the offspring; most saplings were located under nonconspecific canopies. These results suggest that the recruitment pattern of Japanese maple offspring is strongly affected by conspecific adult neighbors, rather than by light and gap distributions, with close proximity to conspecific adult trees reducing the growth and survival of seedlings during the transition to saplings.

A spatial and mechanistic model is developed for the dynamics of transition oak—northern hardwoods forests in northeastern North America. The purpose of the model is to extrapolate from measurable fine—scale and short—term interactions among individual trees to large—scale and long—term dynamics of forest communities. Field methods, statistical estimators, and model structure were designed simultaneously to ensure that parameters could be estimated from data collected in the field. This paper documents eight aspects of a three—year study to calibrate, test, and analyze the model for the nine dominant and subdominant tree species in transition oak—northern hardwoods forests: 1) Design and structure of the model. The model makes population dynamic forecasts by predicting the fate of every individual tree throughout its life. Species—specific functions predict each tree's dispersal, establishment, growth, mortality, and fecundity. Trees occupy unique spatial positions, and individual performance is affected by the local availability of resources. Competition is mechanistic; resources available to each tree are reduced by neighbors. Although the model was developed to include light, water, and nitrogen, the version described here includes only competition for light (shading and light—dependent performance) because the field data provide little evidence of competition for nitrogen and water over the range of sites examined. 2) Estimates of the model's parameters for each species. The estimates reveal a variety of "strategic trade—offs" among the species. For example, species that grow quickly under high light tend to cast relatively little shade, have low survivorship under low light, and have high dispersal. In contrast, species that grow slowly under high light tend to cast relatively dark shade, and to have high survivorship under low light and low dispersal. These trade—offs define one of two dominant "axes" of strategic variation. 3) Community level predictions of the model. The model predicts succession from early dominance by species such as Quercus rubra and Prunus serotina, to late dominance by Fagus grandifolia and Tsuga canadensis, with Betula alleganiensis present as a gap phase species in old—growth stands. The model also predicts that old—growth communities will have intraspecifically clumped and interspecifically segregated spatial distributions. 4) An error analysis that identifies community level predictions that are robust given the level of sampling uncertainty in the study. This analysis translates the statistical uncertainty associated with each parameter estimate into statistical uncertainty in the model's predictions. The robust predictions include those mentioned in aspect (3) above. 5) Sensitivity of the model to changes in initial conditions and to changes in the three parameters not included in the error analysis. For example, the model predicts that initial abundances continue to affect community composition well into succession (> 300 yr for some species). 6) Tests of the system— and community—level predictions of the model against independent data gleaned from other studies. These tests support the predictions found to be robust in the error analysis, including those predictions mentioned in aspect (3) above. 7) Modeling experiments that determine which aspects of individual performance and inter—neighbor competition are responsible for each of the robust predictions identified in aspect (4) above and tested in aspect (6) above. This analysis reveals a wide variety of causal relationships, with most parameters contributing to at least one community level phenomenon. 8) An explanation of the diversity of individual level causes identified in aspect (7). The two "axes" describing most of the strategic variation among the species (see [2]), provide a simple explanation of community level pattern in terms of individual level processes.

Patterns of seed rain were observed at five forest locations in recent treefall gaps and paired understory sites in a tropical wet forest in northeast Costa Rica. Seed rain was dominated by animal-dispersed species. Overall, significantly more wind-dispersed seeds arrived into treefall gaps than into forest understory. Contrary to expectations, understory sites received a greater seed rain than did gap sites during three of four sample periods over the course of one year. Considerable spatial heterogeneity, however, existed among forest locations, with some forest sites receiving up to three times more seed rain input than others. Results from this seed rain study generally matched those from an earlier study at this site in terms of seed rain volume and dominant plant families. Composition of seed rain was more similar among habitat types (i.e., gap, understory) than among forest locations (i.e., paired sites) suggesting that spatial foraging activity and habitat preference of seed dispersers result in non-random patterns of seed rain. If true, then such patterns have implications for evolution of fruit and seed characters that promote survival and establishment of seeds under certain environmental conditions.

Recruitment, the addition of new individuals into a community, is an important factor that can substantially affect community composition and dynamics. We present a method for calibrating spatial models of plant recruitment that does not require identifying the specific parent of each recruit. This method calibrates seedling recruitment functions by comparing tree seedling distributions with adult distributions via a maximum likelihood analysis. The models obtained from this method can then be used to predict the spatial distributions of seedlings from adult distributions.We calibrated recruitment functions for 10 tree species characteristic of transition oak-northern hardwood forests. Significant differences were found in recruit abundances and spatial distributions. Predicted seedling recruitment limitation for test stands varied substantially between species, with little recruitment limitation for some species and strong recruitment limitation for others. Recruitment was limited due to low overall recruit production or to restricted recruit dispersion. When these seedling recruitment parameters were incorporated into a spatial, individual-based model of forest dynamics, called SORTIE, alterations of recruitment parameters produced substantial changes in species abundance, providing additional support for the potential importance of seedling recruitment processes in community structure and dynamics.