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Successional, second-growth forests dominate much of eastern North America; thus, patterns of biomass accumulation in standing trees and downed wood are of great interest for forest management and carbon accounting. The timing and magnitude of biomass accumulation in later stages of forest development are not fully understood. We applied a “chronosequence with resampling” approach to characterize live and dead biomass accumulation in 16 northern hardwood stands in the White Mountains of New Hampshire. Live aboveground biomass increased rapidly and leveled off at about 350 Mg/ha by 145 years. Downed wood biomass fluctuated between 10 and 35 Mg/ha depending on disturbances. The species composition of downed wood varied predictably with overstory succession, and total mass of downed wood increased with stand age and the concomitant production of larger material. Fine woody debris peaked at 30–50 years during the self-thinning of early successional species, notably pin cherry. Our data support a model of northern hardwood forest development wherein live tree biomass accumulates asymptotically and begins to level off at ∼140–150 years. Still, 145-year-old second-growth stands differed from old-growth forests in their live ( p = 0.09) and downed tree diameter distributions ( p = 0.06). These patterns of forest biomass accumulation would be difficult to detect without a time series of repeated measurements of stands of different ages. 

Mounting evidence suggests that geographic ranges of tree species worldwide are shifting under global environmental changes. Little is known, however, about if and how these species’ range shifts may trigger the range shifts of various types of forests. Markowitz’s portfolio theory of investment and its broad application in ecology suggest that the range shift of a forest type could differ substantially from the range shifts of its constituent tree species. MethodsHere, we tested this hypothesis by comparing the range shifts of forest types and the mean of their constituent species between 1970–1999 and 2000–2019 across Alaska, Canada, and the contiguous United States using continent-wide forest inventory data. We first identified forest types in each period using autoencoder neural networks and K-means cluster analysis. For each of the 43 forest types that were identified in both periods, we systematically compared historical range shifts of the forest type and the mean of its constituent tree species based on the geographic centroids of interpolated distribution maps. ResultsWe found that forest types shifted at 86.5 km·decade^-1on average, more than three times as fast as the average of constituent tree species (28.8 km·decade^-1). We showed that a predominantly positive covariance of the species range and the change of species relative abundance triggers this marked difference. DiscussionOur findings provide an important scientific basis for adaptive forest management and conservation, which primarily depend on individual species assessment, in mitigating the impacts of rapid forest transformation under climate change. 

Statistical confidence in estimates of timber volume, carbon storage, and other forest attributes depends, in part, on the uncertainty in field measurements. Surprisingly, measurement uncertainty is rarely reported, even though national forest inventories routinely repeat field measurements for quality assurance. We compared measurements made by field crews and quality assurance crews in the Forest Inventory and Analysis program of the U.S. Forest Service, using data from 2790 plots and 51 740 trees and saplings across the 24 states of the Northern Region. We characterized uncertainty in 12 national core tree-level variables; seven tree crown variables used in forest health monitoring; three variables describing seedlings; and 11 variables describing the site, such as elevation, slope, and distance from a road. Discrepancies in measurement were generally small but were higher for some variables requiring judgment, such as tree class, decay class, and cause of mortality. When scaled up to states, forest types, or the region, uncertainties in basal area, timber volume, and aboveground biomass were negligible. Understanding all sources of uncertainty is important to designing forest monitoring systems, managing the conduct of the inventory, and assessing the uncertainty of forest attributes required for making regional and national forest policy decisions. 

Anticipating the next generation of forests requires understanding of recruitment responses to habitat change. Tree distribution and abundance depend not only on climate, but also on habitat variables, such as soils and drainage, and on competition beneath a shaded canopy. Recent analyses show that North American tree species are migrating in response to climate change, which is exposing each population to novel climate-habitat interactions (CHI). Because CHI have not been estimated for either adult trees or regeneration (recruits per year per adult basal area), we cannot evaluate migration potential into the future. Using the Masting Inference and Forecasting (MASTIF) network of tree fecundity and new continent-wide observations of tree recruitment, we quantify impacts for redistribution across life stages from adults to fecundity to recruitment. We jointly modeled response of adult abundance and recruitment rate to climate/habitat conditions, combined with fecundity sensitivity, to evaluate if shifting CHI explain community reorganization. To compare climate effects with tree fecundity, which is estimated from trees and thus is "conditional" on tree presence, we demonstrate how to quantify this conditional status for regeneration. We found that fecundity was regulated by temperature to a greater degree than other stages, yet exhibited limited responses to moisture deficit. Recruitment rate expressed strong sensitivities to CHI, more like adults than fecundity, but still with substantial differences. Communities reorganized from adults to fecundity, but there was a re-coalescence of groups as seedling recruitment partially reverted to community structure similar to that of adults. Results provide the first estimates of continent-wide community sensitivity and their implications for reorganization across three life-history stages under climate change.