Drainage is an essential prerequisite in peatland forest management, which generally, but not always, increases stand growth. Growth response depends on weather conditions, stand and site characteristics, management and biogeochemical processes. We constructed a SUSI-simulator (SUoSImulaattori, in Finnish), which describes hydrology, stand growth and nutrient availability under different management, site types and weather conditions. In the model development and sensitivity analysis, we used water table ($WT$) and stand growth data from 11 Scots pine stands. The simulator was validated against a larger dataset collected from boreal drained peatlands in Finland. In validation, SUSI was shown to predict $WT$ and stand growth well. Stand growth was mainly limited by inadequate potassium supply, and in Sphagnum peats by low oxygen availability. Model application was demonstrated for ditch network maintenance (DNM) by comparing stand growth with shallow (−0.3 m) and deep ditches (−0.9 m): The growth responses varied between 0.5 and 3.5 m³ ha⁻¹ in five years, which is comparable to experimental results. SUSI can promote sustainable peatland management and help in avoiding unnecessary drainage operations and associated environmental effects, such as increased carbon emissions, peat subsidence, and nutrient leaching. The source code is publicly available, and the modular structure allows model extension to cost–benefit analyses and nutrient export to water courses.

Different abiotic and biotic disturbances are expected to become more common in the future due to a warming climate. Globally, post-disturbance salvage logging is becoming more predominant to recover economic value from timber in disturbed forests. This study collected comparative time-study data and analyzed the productivity of cutting for windfalls in clear cuttings and determined the cutting costs of windfalls. Furthermore, the logging (i.e., cutting and forwarding) costs of wind-damaged trees and those of undamaged standing Norway spruce (Picea abies (L.) Karst.) trees in clear cuts were calculated in Finland. The results revealed that the cutting productivity of windfalls was 19–33% lower than that of undamaged stems. The cutting costs of windthrown stems with a volume of 0.3–1.5 m³ were 35–64% higher and the logging costs of windfalls were 10–30% higher than those of undamaged standing stems. The study provided new understanding regarding the productivity and costs of salvage logging operations under Finnish conditions. Even if the logging of windfalls is expensive and laborious, salvage logging operations are important for forest stands and their health to minimize post-disaster damage outbreaks in coniferous forests, such as the damage caused by bark beetles—mainly Ips typographus L.

Continuous-cover forestry (CCF) is expected to reduce the negative environmental impacts of peatland forestry in comparison with rotation forestry (RF), but the unknown profitability of CCF on peatlands limits its application in practice. The profitability of CCF was analyzed by simulating management scenarios with a process-based ecosystem model, EFIMOD, which was complemented to describe the interplay between tree growth and water table depth, which is typical of peatland forests. A variety of harvest intervals and post-harvest basal areas for a mature Norway spruce (Picea abies (L.) Karst.) dominated stand was simulated on a nutrient-rich peatland site. Conventional RF was simulated for comparison. CCF provided a higher profit than RF. The best financial performance was obtained with a 15-year harvest interval regardless of interest rate, although the overall profitability of CCF depended on the interest rate used. Ditch network maintenance was needed to maintain the stand growth only when the post-harvest basal area was smaller than 10 m²·ha⁻¹. There were many CCF scenarios in which the difference in the net present value of harvest revenues was within 10% compared with the best CCF scenario. Hence, there are many relatively profitable CCF harvesting alternatives for forest management in boreal spruce-dominated peatland forests.

Drained peatlands are one of the main sources of carbon dioxide (CO₂) emissions globally. Emission reduction and, more generally, ecosystem restoration can be enhanced by raising the water table using canal or drain blocks. When restoring large areas, the number of blocks becomes limited by the available resources, which raises the following question: in which exact positions should a given number of blocks be placed in order to maximize the water table rise throughout the area? There is neither a simple nor an analytic answer. The water table response is a complex phenomenon that depends on several factors, such as the topology of the canal network, site topography, peat hydraulic properties, vegetation characteristics and meteorological conditions. We developed a new method to position the canal blocks based on the combination of a hydrological model and heuristic optimization algorithms. We simulated 3 d dry downs from a water saturated initial state for different block positions using the Boussinesq equation, and the block configurations maximizing water table rise were searched for by means of genetic algorithm and simulated annealing. We applied this approach to a large drained peatland area (931 km²) in Sumatra, Indonesia. Our solution consistently outperformed traditional block locating methods, indicating that drained peatland restoration can be made more effective at the same cost by selecting the positions of the blocks using the presented scheme.

We used a process-based hydrological model SUSI to improve guidelines for ditch network maintenance (DNM) operations on drained peatland forests. SUSI takes daily weather data, ditch depth, strip width, peat properties, and forest stand characteristics as input and calculates daily water table depth (WTD) at different distances from ditch. The study focuses on Scots pine ( L.) dominated stands which are the most common subjects of DNM. Based on a literature survey, and consideration of the tradeoffs between forest growth and detrimental environmental impacts, long term median July–August WTD of 0.35 m was chosen as a target WTD. The results showed that ditch depths required to reach such WTD depends strongly on climatic locations, stand volume, ditch spacing, and peat thickness and type. In typical ditch cleaning areas in Finland with parallel ditches placed about 40 m apart and tree stand volumes exceeding 45 m ha, 0.3–0.8 m deep ditches were generally sufficient to lower WTD to the targeted depth of 0.35 m. These are significantly shallower ditch depths than generally recommended in operational forestry. The main collector ditch should be naturally somewhat deeper to permit water outflow. Our study brings a firmer basis on environmentally sound forestry on drained peatlands.Pinus sylvestris 3 –1

Peatlands are globally significant carbon stocks and may become major sources of the greenhouse gases (GHGs) carbon dioxide and methane in a changing climate and under anthropogenic management pressure. Diffusion is the dominant gas transport mechanism in peat; therefore, a proper knowledge of the soil gas diffusion coefficient is important for the estimation of GHG emissions from peatlands. Pore network modeling (PNM) is a potential tool for the determination of gas diffusivity in peat, as it explicitly connects the peat microstructure and the characteristics of the peat pore network to macroscopic gas transport properties. In the present work, we extracted macropore networks from three-dimensional X-ray micro-computed tomography (µCT) images of peat samples and simulated gas diffusion in these networks using PNM. These results were compared to the soil gas diffusion coefficients determined from the same samples in the laboratory using the diffusion chamber method. The measurements and simulations were conducted for peat samples from three depths. The soil gas diffusion coefficients were determined under varying water contents adjusted in a pressure plate apparatus. We also assessed the applicability of commonly used gas diffusivity models to peat. The laboratory measurements showed a decrease in gas diffusivity with depth due to a decrease in air-filled porosity and pore space connectivity. However, gas diffusivity was not extremely low close to saturation, which may indicate that the structure of the macropore network is such that it enables the presence of connected diffusion pathways through the peat matrix, even in wet conditions. The traditional gas diffusivity models were not very successful in predicting the soil gas diffusion coefficient. This may indicate that the microstructure of peat differs considerably from the structure of mineral soils and other kinds of porous materials for which these models have been constructed and calibrated. By contrast, the pore network simulations reproduced the laboratory-determined soil gas diffusion coefficients rather well. Thus, the combination of the µCT and PNM methods may offer a promising alternative to the traditional estimation of soil gas diffusivity through laboratory measurements.