Planning and decision-making can be improved by access to reliable forecasts of ecosystem state, ecosystem services, and natural capital. Availability of new data sets, together with progress in computation and statistics, will increase our ability to forecast ecosystem change. An agenda that would lead toward a capacity to produce, evaluate, and communicate forecasts of critical ecosystem services requires a process that engages scientists and decision-makers. Interdisciplinary linkages are necessary because of the climate and societal controls on ecosystems, the feedbacks involving social change, and the decision-making relevance of forecasts.

Dispersal affects community dynamics and vegetation response to global change. Understanding these effects requires descriptions of dispersal at local and regional scales and statistical models that permit estimation. Classical models of dispersal describe local or long-distance dispersal, but not both. The lack of statistical methods means that models have rarely been fitted to seed dispersal in closed forests. We present a mixture model of dispersal that assumes a range of disperal patterns, both local and long distance. The bivariate Student's t or ''2Dt'' follows from an assumption that the distance parameter in a Gaussian model varies randomly, thus having a density of its own. We use an inverse approach to ''compete'' our mixture model against classical alternatives, using seed rain databases from temperate broadleaf, temperate mixed-conifer, and tropical floodplain forests. For most species, the 2Dt model fits dispersal data better than do classical models. The superior fit results from the potential for a convex shape near the source tree and a ''fat tail.'' Our parameter estimates have implications for community dynamics at local scales, for vegetation responses to global change at regional scales, and for differences in seed dispersal among biomes. The 2Dt model predicts that less seed travels beyond the immediate crown influence (Ͻ5 m) than is predicted under a Gaussian model, but that more seed travels longer distances (Ͼ30 m). Although Gaussian and exponential models predict slow population spread in the face of environmental change, our dispersal estimates suggest rapid spread. The preponderance of animal-dispersed and rare seed types in tropical forests results in noisier patterns of dispersal than occur in temperate hardwood and conifer stands.

The majority of the Earth's terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12-17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon-climate feedback that could accelerate climate change.

Advances in computational statistics provide a general framework for the highdimensional models typically needed for ecological inference and prediction. Hierarchical Bayes (HB) represents a modelling structure with capacity to exploit diverse sources of information, to accommodate influences that are unknown (or unknowable), and to draw inference on large numbers of latent variables and parameters that describe complex relationships. Here I summarize the structure of HB and provide examples for common spatiotemporal problems. The flexible framework means that parameters, variables and latent variables can represent broader classes of model elements than are treated in traditional models. Inference and prediction depend on two types of stochasticity, including (1) uncertainty, which describes our knowledge of fixed quantities, it applies to all ÔunobservablesÕ (latent variables and parameters), and it declines asymptotically with sample size, and (2) variability, which applies to fluctuations that are not explained by deterministic processes and does not decline asymptotically with sample size. Examples demonstrate how different sources of stochasticity impact inference and prediction and how allowance for stochastic influences can guide research.

Recent models and analyses of paleoecological records suggest that tree populations are capable of rapid migration when climate warms. Fossil pollen is commonly interpreted as suggesting that the range of many temperate tree species expanded at rates of 100–1000 m/yr during the early Holocene. We used chloroplast DNA surveys to show that the geography of postglacial range expansion in two eastern North American tree species differs from that expected from pollen‐based reconstructions and from patterns emerging from European molecular studies. Molecular evidence suggests that American beech (Fagus grandifolia) and red maple (Acer rubrum) persisted during the late glaciation as low‐density populations, perhaps within 500 km of the Laurentide Ice Sheet. Because populations were closer to modern range limits than previously thought, postglacial migration rates may have been slower than those inferred from fossil pollen. Our estimated rates of <100 m/yr are consistent with model predictions based on life history and dispersal data, and suggest that past migration rates were substantially slower than the rates that will be needed to track 21st‐century warming.

Tree species are expected to track warming climate by shifting their ranges to higher latitudes or elevations, but current evidence of latitudinal range shifts for suites of species is largely indirect. In response to global warming, offspring of trees are predicted to have ranges extend beyond adults at leading edges and the opposite relationship at trailing edges. Large-scale forest inventory data provide an opportunity to compare present latitudes of seedlings and adult trees at their range limits. Using the USDA Forest Service's Forest Inventory and Analysis data, we directly compared seedling and tree 5th and 95th percentile latitudes for 92 species in 30 longitudinal bands for 43 334 plots across the eastern United States. We further compared these latitudes with 20th century temperature and precipitation change and functional traits, including seed size and seed spread rate. Results suggest that 58.7% of the tree species examined show the pattern expected for a population undergoing range contraction, rather than expansion, at both northern and southern boundaries. Fewer species show a pattern consistent with a northward shift (20.7%) and fewer still with a southward shift (16.3%). Only 4.3% are consistent with expansion at both range limits. When compared with the 20th century climate changes that have occurred at the range boundaries themselves, there is no consistent evidence that population spread is greatest in areas where climate has changed most; nor are patterns related to seed size or dispersal characteristics. The fact that the majority of seedling extreme latitudes are less than those for adult trees may emphasize the lack of evidence for climate-mediated migration, and should increase concerns for the risks posed by climate change.

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. Ecological Society of America is collaborating with JSTOR to digitize, preserve and extend access to Ecological Monographs.Abstract. Recruitment limitation of tree population dynamics is poorly understood, because fecundity and dispersal are difficult to characterize in closed stands. We present an approach that estimates seed production and dispersal under closed canopies and four limitations on recruitment: tree density and location, fecundity, seed dispersal, and establishment. Consistent estimates are obtained for 14 canopy species using 5 yr of census data from 100 seed traps and several thousand mapped trees and seedlings from five southern Appalachian forest stands that span gradients in elevation and moisture. Fecundity (seed production per square centimeter of basal area) ranged over four orders of magnitude, from 100 cm2 basal area/yr (Carya, Cornus, Nyssa, Quercus) to >103 cm2/yr (Betula). Mean dispersal distance ranged from <5 m (Cornus, Nyssa) to >20 m (Acer, Betula, Liriodendron, Tsuga) and was positively correlated with fecundity. Species also differ in the degree of seed clumping at fine (1 M2) spatial scales. Dispersal patterns can be classed in two groups based on dispersal vector: wind-dispersed taxa with high fecundities, long-distance dispersal, and low clumping vs. animal-dispersal taxa with low fecundities, short-distance dispersal, and a high degree of clumping. "Colonization" limitations caused by sizes and locations of parent trees, fecundity, and dispersal were quantified as the fraction of sites receiving seed relative to that expected under null models that assume dispersal is nonlocal (i.e., long-distance) and not clumped (i.e., Poisson). Difference among species in colonization levels ranged from those capable of saturating the forest floor with seed in most stands (Acer, Betula, Liriodendron) to ones that leave much of the forest floor without seed, despite presence of adults (Carya, Cornus, Nyssa, Oxydendrum). Seedling establishment is one of the strongest filters on recruitment in our study area. Taken together, our results indicate (1) that fecundity and dispersal can be resolved, even under a closed canopy, and (2) that recruitment of many species is limited by the density and location of source, dispersal patterns, or both.

Principles from particle-motion physics were applied to recurring problems of the interpretation of stratigraphic charcoal data: (1) fires within catchments of lakes often produce no record in fossil-charcoal curves and (2) periods characterized by no local fire (e.g., 20th-century fire suppression) often display as much charcoal as times when local fire was frequent. Quantitative theory on source area, transport, deposition, and sampling of charcoal shows the relationship between particle sizes counted by alternative methods of charcoal analysis (pollen slides for particles 5–80 μm in diameter, petrographic thin sections for particles 50–10,000 μm diameter) and charcoal diagrams. The relationship between diameter and critical and deposition velocities results in fundamental aerodynamic differences between the sizes of particles quantified by the two methods. Charcoal recorded on pollen slides is of a size that is difficult to lift, but once entrained it remains in suspension. Thin-section charcoal is lifted at relatively low wind velocities, but it is not suspended at normal surface wind speeds. Thermal buoyancy during fire lofts charcoal above the forest canopy, depending on particle size and wind speed. Pollen-slide charcoal sizes are underrepresented near the fire, because they remain in suspension and are preferentially exported from the burn area. Thin-section charcoal is convected to lower heights on average and is deposited nearby. Following fire, thin-section charcoal is redistributed locally by wind and thus may enter lakes. Because of cohesive forces and aerodynamics, more pollen-slide charcoal remains on the ground, and less enters lakes. Source areas for pollen-slide charcoal are subcontinental to global, and diagrams of pollen-slide charcoal are biased toward nonlocal charcoal. They can be used to interpret importance of fire for broad spatial and temporal scales. Thin-section charcoal represents, the catchment fire regime. Simulation models that generate charcoal during fire, mix sediments, and then sample at specified intervals indicate that (1) in the absence of sediment mixing the pollen-slide method should consistently resolve individual fires that occur with an expectation of >30–50 yr, (2) unless samples are continuous, neither method will produce useful estimates of fire frequency, and (3) even a modest amount of sediment mixing will obscure the signal.