Toshiaki Owari

Effects of silviculture treatments in a hurricane-damaged forest on carbon storage and emissions in central Hokkaido, Japan

Hurricanes cause abrupt carbon reduction in forests, but silviculture treatment can be an effective means of quickly regenerating and restoring hurricane-damaged sites. This study assessed how silviculture treatments affect carbon balance after hurricane damage in central Hokkaido, Japan. We examined carbon storage in trees and underground vegetation as well as carbon emissions from silviculture operations in 25-year-old stands, where scarification and plantation occurred just after hurricane damage. The amount of carbon stored varied according to silviculture treatment. Among three scarification treatments, a scarified depth of 0 cm (understory vegetation removal) led to the largest amount of carbon stored (64.7 t·ha−1 C). Among four plantation treatments, the largest amount of carbon was stored in a Larix hybrid (L. gmelinii var. japonica × L. kaempferi) plantation (80.3 t·ha−1 C). The plantation of Abies sachalinensis was not successful at accumulating carbon (40.5·ha−1 C). The amount of carbon emitted from silviculture operations was 0.05–0.14 t·ha−1 C, and it marginally affected the net carbon balance of the silviculture project. Results indicate that silviculture treatments should be performed in an appropriate way to effectively recover the ability of carbon sequestration in hurricane-damaged forests.

Analysis of forest structural complexity using airborne LiDAR data and aerial photography in a mixed conifer–broadleaf forest in northern Japan

Determining forest structural complexity, i.e., a measure of the number of different attributes of a forest and the relative abundance of each attribute, is important for forest management and conservation. In this study, we examined the structural complexity of mixed conifer–broadleaf forests by integrating multiple forest structural attributes derived from airborne LiDAR data and aerial photography. We sampled 76 plots from an unmanaged mixed conifer–broadleaf forest reserve in northern Japan. Plot-level metrics were computed for all plots using both field and remote sensing data to assess their ability to capture the vertical and horizontal variations of forest structure. A multivariate set of forest structural attributes that included three LiDAR metrics (95th percentile canopy height, canopy density and surface area ratio) and one image metric (proportion of broadleaf cover), was used to classify forest structure into structural complexity classes. Our results revealed significant correlation between field and remote sensing metrics, indicating that these two sets of measurements captured similar patterns of structure in mixed conifer–broadleaf forests. Further, cluster analysis identified six forest structural complexity classes including two low-complexity classes and four high-complexity classes that were distributed in different elevation ranges. In this study, we could reliably analyze the structural complexity of mixed conifer–broadleaf forests using a simple and easy to calculate set of forest structural attributes derived from airborne LiDAR data and high-resolution aerial photography. This study provides a good example of the use of airborne LiDAR data sets for wider purposes in forest ecology as well as in forest management.

Height Growth of Korean Pine Seedlings Planted under Strip-Cut Larch Plantations in Northeast China

To develop two-storied forest management of larch plantations in Northeast China, this study examined the height growth of Korean pine (Pinus koraiensis Sieb. et Zucc.) seedlings planted under strip-cut larch canopies. We measured the height growth of the underplanted seedlings 4 years after planting. The larch canopies were of varying stand age (12, 17, and 37 years) and strip-cut width (4.5, 6.0, and 7.5 m). We measured the seedling height growth in an open site (i.e., a site with no canopy). Underplanted seedlings had a smaller height growth (12.1–20.1 cm year−1) than the seedlings planted in the open site (23.7 cm year−1). The seedlings underplanted in the wider strip-cuts tended to have greater height growth than the seedlings underplanted in the narrowest strip-cuts. A generalized linear mixed model analysis predicted the greatest seedling height growth in the open site. A 36–47% reduction in annual height growth was predicted for the narrowest strip-cuts (4.5 m) versus the open site, while a 13–36% reduction in annual height growth was predicted for the wider strip-cuts (6.0–7.5 m) versus the open site. To maintain adequate height growth, forest managers are recommended to create wider strip-cuts (i.e., ≥6.0 m) for the purpose of underplanting Korean pine seedlings in larch plantations.

Evaluating the Performance of Photogrammetric Products Using Fixed-Wing UAV Imagery over a Mixed Conifer–Broadleaf Forest: Comparison with Airborne Laser Scanning

Unmanned aerial vehicles (UAVs) and digital photogrammetric techniques are two recent advances in remote sensing (RS) technology that are emerging as alternatives to high-cost airborne laser scanning (ALS) data sources. Despite the potential of UAVs in forestry applications, very few studies have included detailed analyses of UAV photogrammetric products at larger scales or over a range of forest types, including mixed conifer–broadleaf forests. In this study, we assessed the performance of fixed-wing UAV photogrammetric products of a mixed conifer–broadleaf forest with varying levels of canopy structural complexity. We demonstrate that fixed-wing UAVs are capable of efficiently collecting image data at local scales and that UAV imagery can be effectively utilized with digital photogrammetric techniques to provide detailed automated reconstruction of the three-dimensional (3D) canopy surface of mixed conifer–broadleaf forests. When combined with an accurate digital terrain model (DTM), UAV photogrammetric products are promising for producing reliable structural measurements of the forest canopy. However, the performance of UAV photogrammetric products is likely to be influenced by the structural complexity of the forest canopy. Furthermore, we highlight the potential of fixed-wing UAVs in operational forest management at the forest management compartment level, for acquiring high-resolution imagery at low cost. A future direction of this research would be to address the issue of how well the photogrammetric products can predict the actual structure of mixed conifer–broadleaf forests.

Single-tree management for high-value timber species in a cool-temperate mixed forest in northern Japan

ABSTRACT High-value hardwood species such as monarch birch (Betula maximowicziana) and castor aralia (Kalopanax septemlobus) are important economic and ecological elements of cool-temperate mixed forests in northern Japan. This article presents the single-tree management system for high-value timber species as practised for 50 years at the University of Tokyo Hokkaido Forest. Nearly 2000 valuable broad-leaved trees meeting the size and quality criteria have been registered as ‘superior trees’, and their status is periodically monitored for timing of harvest. A case study was conducted using 2105 inventory plots to characterize the stand types in which superior trees occur. A total of 57 superior trees of 11 broad-leaved species was found in 2.2% of the inventory plots. The results indicated that superior trees generally grew in mature species-rich stands. Superior trees of some species may have promoted their abundance by dispersing relatively more seeds to the surroundings. Single-tree management facilitates the sustainable use of high-value timber species by explicitly monitoring the numbers, attributes and locations of superior trees, and contributes to conserving stand structural diversity through protection of these large-sized canopy trees, which promotes ecological values such as biomass and carbon storage, species diversity, seed abundance and bird habitat. The production of fancy wood from superior trees earns significant income through extremely high log prices (maximum > 20,000 USD m–3). EDITED BY Nicholas Brokaw

The use of fixed–wing UAV photogrammetry with LiDAR DTM to estimate merchantable volume and carbon stock in living biomass over a mixed conifer–broadleaf forest

Abstract Remote sensing (RS) data are often used as a complementary data source to acquire accurate quantitative estimations of merchantable volume (V) and carbon stock in living biomass (CST), which are critical for the sustainable use of forest resources. In this study, we investigated the utility of unmanned aerial vehicles (UAVs) and the structure from motion (SfM) technique for estimating and mapping the spatial distributions of V and CST of an uneven–aged mixed conifer–broadleaf forest that had experienced major disturbances (e.g., wind damage and selection harvesting) over time. In addition to the commonly used RS structural metrics, we also calculated an image metric (broadleaf vegetation cover percentage) using a UAV–SfM orthomosaic to use as an explanatory variable. Plot level validation of UAV–SfM–estimated V revealed a root mean square error (RMSE) of 39.8 m3 ha–1 and a relative RMSE of 16.7%, whereas the RMSE and relative RMSE vales for UAV–SfM–estimated CST were 14.3 Mg C ha–1 and 17.4% respectively. Our image metric had a statistically significant association with V and CST, providing additional explanatory power in the regression analysis. Nevertheless, RMSE values did not significantly change after adding the image metric into the regression analysis, e.g., %RMSE was reduced by 1.9% for V estimation, and 1.5% for CST estimation. Furthermore, the UAV–SfM estimates we obtained were comparable to light detection and ranging (LiDAR) estimates (relative RMSE of 16.4% and 16.7% for V and CST, respectively). We also successfully mapped the spatial distributions of V and CST and identified their stand– and landscape–level variations. Therefore, we confirmed the potential of UAV imagery when combined with LiDAR digital terrain model to capture the fine scale spatial variation of V and CST in uneven–aged forests subjected to silvicultural practices and natural disturbances over time.