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Adequate seed provenance is an important guarantee for the restoration of the mixed Korean pine (Pinus koraiensis) and broadleaf forest (MKPBF). However, the commercial harvest exclusion in natural forests has led to a sharp decline in economic income from timber. Given the economic value of Korean pine seeds, predatory seed harvesting (PSH) has become increasingly serious in the past 20 years and has significantly reduced the seed and seedling bank, which might seriously threaten the restoration and sustainable management of the MKPBF. How the historical PSH has affected the future of the MKPBF is unclear at the landscape scale. In this study, we quantified the effects of seed harvesting at the landscape scale by a forest landscape model LANDIS PRO, and then assessed the legacy effects of the historical PSH on the composition and structure of the MKPBF in the Xiaoxing’an Mountains, Northeast China. Our results showed that the historical PSH decreased the Korean pine basal area of all age cohorts, with an average decrease of 0.06 to 0.19 m2 ha−1 but insignificantly altered the age structure diversity of Korean pine throughout the simulation. Our results indicated that the historical PSH remarkably decreased the dominance of Korean pine by 11.1%, but significantly increased the dominance of spruce (Picea koraiensis and Picea jezoensis) and fir (Abies nephrolepis) by 3.8% and 4.5%, respectively, and had an insignificant effect on the other tree species over the simulation. We found that the historical PSH evidently changed the succession trajectories of the disturbed stands, which would result in the transition from the succession pattern dominated by Korean pine to that dominated by spruce and fir. The historical PSH decreased the importance value of Korean pine by 12.2% on average but increased it by 5.1% and 6.0% for spruce and fir, respectively, and resulted in an average 33.2% increase in the dissimilarity index compared with the initial state during the whole simulation period. Future forest management should strictly limit the intensity and rotation of seed harvesting to protect the seed provenance of Korean pine and consider how to ensure the recovery and sustainable management of the MKPBF through direct seeding or seedling planting.

Proactive managements, such as the resistant and the adaptive treatments, have been proposed to cope with the uncertainties of future climates. However, quantifying the uncertainties of forest response to proactive managements is challenging. Korean pine is an ecologically and economically important tree species in the temperate forests of Northeast China. Its dominance has evidently decreased due to excessive harvesting in the past decades. Understanding the responses of Korean pine to proactive managements under the future climates is important. In this study, we evaluated the range of responses of Korean pine to proactive managements under Representative Concentration Pathway (RCP) 8.5 scenarios from four General Circulation Models (GCMs). We coupled an ecosystem process-based model, LINKAGES, and a forest landscape model, LANDIS PRO, to simulate scenarios of management and climate change combinations. Our results showed that the resistant and the adaptive treatment scenarios increased Korean pine importance (by 14.2% and 42.9% in importance value), dominance (biomass increased by 9.2% and 25.5%), and regeneration (abundance &lt, 10 years old increased by 286.6% and 841.2%) throughout the simulation. Results indicated that proactive managements promoted the adaptability of Korean pine to climate change. Our results showed that the variations of Korean pine response to climate change increased (ranging from 0% to 5.8% for importance value, 0% to 4.3% for biomass, and 0% to 85.4% for abundance) throughout the simulation across management scenarios. Our result showed that regeneration dictated the uncertainties of Korean pine response to climate change with a lag effect. We found that the effects of proactive managements were site-specific, which was probably influenced by the competition between Korean pine and the rare and protected broadleaf tree species. We also found that the adaptive treatment was more likely to prompt Korean pine to migrate into its suitable habitats and promoted it to better cope with climate change. Thus, the adaptive treatment is proposed for Korean pine restoration under future climates.

State-of-the-art forest models are often complex, analytically intractable, and computationally expensive, due to the explicit representation of detailed biogeochemical and ecological processes. Different models often produce distinct results while predictions from the same model vary with parameter values. In this project, we developed a rigorous quantitative approach for conducting model intercomparisons and assessing model performance. We have applied our original methodology to compare two forest biogeochemistry models, the Perfect Plasticity Approximation with Simple Biogeochemistry (PPA-SiBGC) and Landscape Disturbance and Succession with Net Ecosystem Carbon and Nitrogen (LANDIS-II NECN). We simulated past-decade conditions at flux tower sites located within Harvard Forest, MA, USA (HF-EMS) and Jones Ecological Research Center, GA, USA (JERC-RD). We mined field data available from both sites to perform model parameterization, validation, and intercomparison. We assessed model performance using the following time-series metrics: Net ecosystem exchange, aboveground net primary production, aboveground biomass, C, and N, belowground biomass, C, and N, soil respiration, and species total biomass and relative abundance. We also assessed static observations of soil organic C and N, and concluded with an assessment of general model usability, performance, and transferability. Despite substantial differences in design, both models achieved good accuracy across the range of pool metrics. While LANDIS-II NECN showed better fidelity to interannual NEE fluxes, PPA-SiBGC indicated better overall performance for both sites across the 11 temporal and two static metrics tested (HF-EMS R 2 &macr, = 0.73 , + 0.07 , R M S E &macr, = 4.68 , &minus, 9.96, JERC-RD R 2 &macr, = 0.73 , + 0.01 , R M S E &macr, = 2.18 , &minus, 1.64 ). To facilitate further testing of forest models at the two sites, we provide pre-processed datasets and original software written in the R language of statistical computing. In addition to model intercomparisons, our approach may be employed to test modifications to forest models and their sensitivity to different parameterizations.