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Forest landscape models (FLM) are widely used for simulating forest ecosystems. As FLMs have become more mechanistic, more input parameters are required, which increases model parameter uncertainty. To better understand the increased mechanistic detail provided by LANDIS-II/PnET-Succession, we studied the effects of parameter uncertainty on model outputs based on three different approaches. Global sensitivity analyses summarized the influence of each parameter, a local sensitivity analysis determined the magnitude of and degree of nonlinearity of variation in model outputs alongside variation in individual parameters, and a regression tree analysis identified hierarchical relationships among and interaction effects between parameters. Foliar nitrogen, maintenance respiration, and atmospheric carbon dioxide concentration were the most influential parameters in the global analysis. Knowing where parameter influence is concentrated will help model users interpret results from LANDIS-II/PnET-Succession to address ecological questions and should guide priorities for data acquisition. • Mechanistic forest landscape models increasingly require more input parameters. • We quantified LANDIS-II/PnET-Succession global and local parameter uncertainty. • Foliar nitrogen, maintenance respiration, and carbon dioxide was highly influential. [ABSTRACT FROM AUTHOR]

The recording and simulation data of forest landscapes are massive, high-dimensional, and abstract, requiring intuitive representation. 3-D visualization is an efficient tool to comprehend possible landscape changes generated by real-world or forest landscape models. Based on current advantages of game engines (realism and convenience), we developed a platform for 3-D visualization of forest landscapes (FLV). FLV streamlines multiple software and programming languages to break barrier between geographic data and game engine and transforms outputs of forest landscape models into visualization parameters. Compared with previous 3-D visualizations, FLV has better realism, efficiency, and navigation. We used simulation data of post-volcanic eruption forest landscape recovery in Changbai Mountain as a case study and demonstrated functionalities of FLV. FLV can visualize seamlessly from individual tree to forest stand and landscape scales, and from individual year to decades and centuries temporal scales. It offers potential solutions for the digital representation of complex environmental change. • Development and application of a 3-D forest landscape visualization platform. • The platform has high realism and efficiency, friendly interaction, and versatility. • The platform has been applied to post-volcanic eruption forest landscape visualization. • Provides an intuitive and stereoscopic visualization solution for the dynamics of the forest landscape in time and space. [ABSTRACT FROM AUTHOR]

Forest landscape models (FLMs) are widely used to examine the influence of disturbances on long-term and broad-scale forest ecosystem dynamics. However, FLMs are not well-suited to simulating some types of management or disturbance regimes, including land-use change. Consequently, there are situations in which a researcher may wish to estimate the timing and location of events externally, either from a different model, empirical observations, or some other source, and then incorporate them into an FLM. We present Land Use Plus (LU+), an extension for the LANDIS-II FLM that allows users to integrate externally-developed, spatially and temporally explicit representations of land use or other disturbance into simulations. LU+ allows users to model the proximate effects of these events on forest composition and biomass, as well as subsequent dynamics, including tree establishment and the potential for future management. LU+ will significantly increase the breadth of research questions for which LANDIS-II may be appropriately used. [ABSTRACT FROM AUTHOR]

Most predictions of tree species' distributions at broad spatial scales are based only on one possible characterization of environmental heterogeneity. Evaluating the effects of multiple heterogeneities on predictions may help in quantifying prediction uncertaintie. In this study we investigated the effects of three levels of environmental heterogeneity on landscape-scale predictions. In addition, we analyzed how seed dispersal and interspecies competition contributes to prediction uncertainty. We used a coupled ecosystem and landscape modeling approach to predict tree species' abundance at the landscape scale. We designed multiple-species and single-species scenarios, each with the three levels of environmental heterogeneity. Our results showed the importance of considering environmental heterogeneity when predictioning tree species' abundance. For early-successional species landscape-scale predictions differed significantly among heterogeneity levels. For late-successional species, prediction uncertainties based on different heterogeneity levels were comparatively low. Seed dispersal may be a source of variation in predictions, whereas interspecies competition may reduce such variation. [ABSTRACT FROM AUTHOR]

Climate change could alter species composition, with feedback on fire disturbances by modifying fuel types and loads. However, the existing fire predictions were mainly based on climate-fire linkages that might overestimate the probability and size of fire disturbances due to simplifying or omitting vegetation feedback. We applied a model-coupling framework that combines forest succession, climate-fire linkages, and vegetation feedback to predict burned area, aboveground biomass, and species composition of boreal forests in Northeast China under climate change conditions. Results showed that climate change and fire would favor the recruitment of deciduous species, but these species need a long-time to replace the existing coniferous species. Burned area would increase with climate change. Climate change, historical and future fire disturbances affect aboveground biomass by altering tree mortality and regeneration. Further studies should address strategies for altering species composition through forest management practices to adaptation climate change and reduce carbon losses from fire. [Display omitted] • We applied a model-coupling framework to simulate the response of boreal forest to climate-fire-vegetation interactions. • Climate change and fire would favor the recruitment of drought-tolerant species. • Climate change would significantly increase the burned area of boreal forests. • Climate change, historical and future fire disturbance would affect aboveground biomass of boreal forests. • It is necessary to implement forest management strategies to alter species composition for reducing burned area and carbon losses from catastrophic fires. [ABSTRACT FROM AUTHOR]