Cover PhotoMontane ecosystems, as seen from Mount Jefferson on the White Mountain National Forest. These ecosystems are particularly vulnerable to climate change. Photo by Toni Lyn Morelli, U.S. Geological Survey.

Most temperate forests in U.S. are recovering from heavy exploitation and are in intermediate successional stages where partial tree harvest is the primary disturbance. Changes in regional forest composition in response to climate change are often predicted for plant functional types using biophysical process models. These models usually simplify the simulation of succession and harvest and may not consider important species‐specific demographic processes driving forests changes. We determined the relative importance of succession, harvest, and climate change to forest composition changes in a 125‐million ha area of the Central Hardwood Forest Region of U.S. We used a forest landscape modeling approach to project changes in density and basal area of 23 tree species due to succession, harvest, and four climate scenarios from 2000 to 2300. On average, succession, harvest, and climate change explained 78, 17, and 1% of the variation in species importance values (IV) at 2050, respectively, but their contribution changed to 46, 26, and 20% by 2300. Climate change led to substantial increases in the importance of red maple and southern species (e.g., yellow‐poplar) and decreases in northern species (e.g., sugar maple) and most of widely distributed species (e.g., white oak). Harvest interacted with climate change and accelerated changes in some species (e.g., increasing southern red oak and decreasing American beech) while ameliorated the changes for others (e.g., increasing red maple and decreasing white ash). Succession was the primary driver of forest composition change over the next 300 years. The effects of harvest on composition were more important than climate change in the short term but climate change became more important than harvest in the long term. Our results show that it is important to model species‐specific responses when predicting changes in forest composition and structure in response to succession, harvest, and climate change.

Abstract. Two challenges confronting forest landscape models (FLMs) are how to simulate fine, standscale processes while making large-scale (i.e., .10 7 ha) simulation possible, and how to take advantage of extensive forest inventory data such as U.S. Forest Inventory and Analysis (FIA) data to initialize and constrain model parameters. We present the LANDIS PRO model that addresses these needs. LANDIS PRO adds density and size mechanisms of resource competition. This is achieved through incorporating number of trees and DBH by species age cohort within each raster cell. Forest change is determined by the interactions of species-, stand-, and landscape-scale processes. Species-scale processes include tree growth, establishment, and mortality. Stand-scale processes include density and size-related resource competition that regulates self-thinning and seedling establishment. Landscape-scale processes include seed dispersal, as well as natural and anthropogenic disturbances. LANDIS PRO is designed to be straightforwardly comparable with forest inventory data, and thus the extensive FIA data can be directly utilized to initialize and constrain model parameters before predicting future forest change. We initialized a large landscape (;10 7 ha) from historical FIA data (1978) and the predicted forest structure and composition following 30 years of simulation were statistically calibrated against a prior time-series of sequential FIA data (1978 to 2008). The results showed that the initialized conditions realistically represented the historical forest composition and structure at 1978, and the constrained model parameters predicted reasonable outcomes at both landscape and land type scales. The subsequent evaluation of model predictions showed that the predicted forest composition and structure were comparable with old-growth oak forests; predicted forest successional trajectories were consistent with the expected successional patterns in oak-dominated forests in the study region; and the predicted stand development patterns were in agreement with the established theories of forest stand development. This study demonstrated a framework for forest landscape modeling including model initialization, calibration, and evaluation of predictions.

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LANDIS PRO predicts forest composition and structure changes incorporating species-, stand-, and landscape-scales processes at regional scales. Species-scale processes include tree growth, establishment, and mortality. Stand-scale processes contain density-and size-related resource competition that regulates self-thinning and seedling establishment. Landscapescale processes include seed dispersal and disturbances. LANDIS PRO is designed to be compatible with forest inventory data, thus extensive inventory data can be directly utilized to initialize and calibrate model parameters before predicting future forest changes. LANDIS PRO allows for exploring the eff ects of disturbances, management, climate change, and modeling the spread of invasive species. We demonstrate that LANDIS PRO successfully predicts forest successional trajectories and stand development patterns in the Central Hardwood Forest region in U.S.Niche-and biogeochemical/ecophysiographical process-based models are the primary tools used to predict forest change at regional scales ( Ͼ 10 8 ha) (Morin and Th uiller 2009). Both types of models have limitations in their abilities to incorporate site-and forest landscape-scale processes (but see Engler et al. 2009, Boulangeat et al. 2012. Site-scale processes include growth, mortality, competition, and other stand-scale processes, which are critical in shaping species ranges and infl uencing biomass predictions at regional scales (Ara ú jo and Luoto 2007, Tylianakis et al. 2008. Forest landscape scale processes are a set of spatial and stochastic processes that include seed dispersal and disturbances (He 2008). Th ey play an important role in shaping forest change at regional scales (Dawson et al. 2011) and may exert greater eff ects than the direct eff ects of climate warming (Gustafson et al. 2010). Most niche-based models do not include site-and forest landscape-scale processes (but see Engler et al. 2009), whereas processed-based models typically simplify the eff ects of disturbances as removal of a fi xed portion of biomass at specifi ed time (Scheiter and Higgins 2009). Without adequately accounting for the siteand forest landscape-scale processes, regional-scale forest change predictions made by niche-and process-based models may be subject to high uncertainties (Purves and Pacala 2008, McMahon et al. 2011).Forest landscape models (FLMs) are explicitly designed to incorporate site-and forest landscape-scale processes to predict forest change at landscape scales (He 2008). To date, FLMs have contributed relatively little to regional-scale forest change predictions due to the immense computational loads required (Supplementary material Appendix 1). Th e maximum simulation capacity (number of pixels) of FLMs is currently in the range of 10 6 -10 7 cells (He 2008). Even at such a simulation capacity, site-scale processes are simplifi ed omitting tree density and size metrics, which are key for determining stand-scale competition for resources (e.g. light) (Bohlman and Pacala 2012). Here we present L...

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Tree harvest and climate change can interact to have synergistic effects on tree species distribution changes. However, few studies have investigated the interactive effects of tree harvest and climate change on tree species distributions. We assessed the interactive effects of tree harvest and climate change on the distribution of 29 dominant tree species at 270 m resolution in the southern United States, while accounting for species demography, competition, urban growth and natural fire. We simulated tree species distribution changes to year 2100 using a coupled forest dynamic model (LANDIS PRO), ecosystem process model (LINKAGES) and urban growth model (SLEUTH). The distributions of 20 tree species contracted and nine species expanded within the region under climate change by end of 21st century. Distribution changes for all tree species were very slow and lagged behind the changes in potential distributions that were in equilibrium with new climatic conditions. Tree harvest and climate change interacted to affect species occurrences and colonization but not extinction. Occurrence and colonization were mainly affected by tree harvest and its interaction with climate change while extinctions were mainly affected by tree harvest and climate change. Synthesis and applications. Interactive effects of climate and tree harvest acted in the same direction as climate change effects on species occurrences, thereby accelerating climate change induced contraction or expansion of distributions. The overall interactive effects on species colonization were negative, specifically with positive interactive effects at leading edges of species ranges and negative interactive effects at trailing edges. Tree harvest generally did not interact with climate change to greatly facilitate or ameliorate species extinction. Our modelling results highlight the importance of considering disturbances and species demography (e.g. post‐harvest regeneration dynamics) when predicting changes in tree distributions.

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