Selection cutting has been carried out widely in natural forests in Hokkaido. However, the expected natural regeneration was not generally obtained, resulting in a degradation of natural forest resources. As one of the solutions, soil scarification with heavy machinery has been carried out to remove dwarf-bamboo that inhibit tree regeneration. However, its implementation is limited in practice because the timing of cutting (winter) and regeneration assistance (summer) is different. It is technically and costly difficult to re-approach the target points (i.e., cut stumps) scattered in the forest in summer, and the operation may disturb advance regeneration. Therefore, in this study, we attempted to conduct scarification during the snow season (winter scarification) by extending an operation to dig up snow around trees with heavy machinery in advance for cutting in winter (preparatory snow removal). The operation cost and the effects on natural regeneration were compared with control (no-scarified area) and standard scarification area (summer scarification). If we compare only the operation for regeneration assistance, the costs could be reduced to one-third of the summer scarification. In about 90％ of the winter scarification areas, the regenerated saplings (mainly Betula ermanii) overtopped the surrounding dwarf bamboos (average height 145 cm), and in about 70％ of the areas, the sapling density exceeded 1,000 trees/ha. We conclude that the winter scarification could be an option associated with selection cutting as one of the key operations to re-establish natural forest management in Hokkaido.

Although the necessity for hamlet-scale demographic analysis has been repeatedly pointed out, there has been little research due to scarcity of data. The purpose of this paper is twofold: (1) to explore the feasibility of hamlet-scale demographic analysis using the population census and (2) to examine the merger of hamlets from a demographic perspective using a cohort analysis. Thus, we chose the merger of three hamlets in the Fudo district of Joetsu City, Niigata Prefecture, in 2020. The results follow. (1) The population of hamlets after 1965 could be ascertained from censuses by interpreting census enumeration districts as hamlets, but it was not possible to similarly use censuses after 2000. (2) Fudo Elementary School became independent and expanded in the 1950s because of the large population of the cohort born during 1946-1955, i.e. the “independent-school generation.” In the post-2000 era, as a response to the declining birth rates and subsequent closure of elementary schools, there has been a call for this generation to forge a new bond. (3) The population of people aged in their 60s and 70s who serve as district officers peaked in 2015 and has been declining since. In summary, this hamlet merger was conducted by the “independent-school generation” who were old enough to be designated as district officers and had prepared for a future population decline. Future tasks are to examine the life of each of the “independent-school generation” and to improve hamlet-scale demographic analysis considering gender and social mobility trends.

Determining the flowering stage accurately is crucial for successful artificial fertilization. However, visually identifying the stage requires skill and is subjective. To address this, we developed a simple method for determining the developmental stage of female strobili of Pinus thunbergii using deep learning. A classification model was created, and an associated web application was developed, eliminating the dependency on human observation. The process involved several skilled investigators classifying various images of P. thunbergii female strobili into stages I, II, and III. From a total of 3,074 images with unanimous evaluations, we used MobileNetV2's transition learning to construct and evaluate the model. Although the model had a high accuracy rate of 0.974 and an F-score of 0.949, i.e., a balanced evaluation of precision and recall, it failed to predict some images correctly. Specifically, it struggled with images containing small female strobili in relation to the entire screen, as well as images that included unrelated objects. Additionally, it had difficulty with female strobili that were yellowish-green in color. However, despite these limitations, we propose that this tool can be useful for evaluating traits in the field.

Thematic maps, such as forest change and land cover change maps, are generally inaccurate. The assessment of accuracy, defined as the correctness of a map, is critical for understanding the quality and utility of thematic maps. This review shows the fundamental principles in area estimation and accuracy assessment for forest change maps based on three components: sampling design, response design, and analysis, and then reveals the criterion and recommended practices. Several special cases of accuracy assessment are also discussed. A probability sampling design is implemented in the statistically rigorous accuracy assessment to estimate accuracy based on the comparison of a map and reference data. Population error matrix is crucial in assessing the accuracy and estimating area. Further, the use of unbiased or consistent estimators that correspond to the sampling design is critical for deriving accuracy metrics and area estimates with associated uncertainty. Although the fundamental principles of accuracy assessment are well established, methods for addressing issues have also recently been developed. Practitioners are required to choose the optimal protocols to achieve their objectives of the accuracy assessment because no single protocol or approach can completely address all situations.