Mizue Ohashi

Vegetation and subsequent ecosystem services can recover over time in forest headwaters devastated by massive disasters. However, in cold regions, their recovery rates are typically slow and often imperceptible, which makes it difficult to evaluate how much ecosystem services have recovered. This study targeted dissolved organic matter (DOM), which plays a central role in biogeochemical processes in forest ecosystems, and aimed to examine whether vegetation conditions affect the quality of stream DOM from cool-temperate forest headwaters in northern Japan. To achieve this, hydrological observations and stream water sampling were conducted monthly from May to December 2021 in three small forest catchments with different landslide coverage. Dissolved organic carbon (DOC) concentration in stream water was measured, and the molecular composition of DOM was analyzed using ultrahigh-resolution mass spectrometry and compared among the three catchments. The peak-intensity-weighted average aromaticity index (AIwa) increased with DOC concentration. We found that AIwa was the highest in the undisturbed catchment, followed by the catchments with landslide coverages of 16% and 52% at a given DOC level. These results indicate that the quality of DOM could dramatically change depending not only on DOC concentration but also on vegetation disturbance in cool-temperate forest headwaters.

Abstract. Dissolved organic matter (DOM) degradation in freshwater rivers and streams plays a major role in the global carbon cycle. However, little is known about how the source and composition of riverine DOM contribute to the production of greenhouse gases, especially in high-latitude areas with a large proportion of carbon-rich peatlands. Here, we conducted for the first time the combination of molecular-level characterization of terrestrially derived DOM and the potential carbon dioxide (CO2) production measurements in pristine subarctic rivers of Finnish Lapland. 21-day incubation studies were conducted with water samples taken from two rivers differing in DOM content during spring and fall 2018. The changes in the DOM concentration and molecular composition, as well as the CO2 production, were measured. The DOM molecular characterization was carried out using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Our results demonstrate efficient mineralization of dissolved organic carbon (DOC) into CO2 in mineral soil associated clearwater river during the incubation, while significantly lower CO2 production per DOC was observed in the brown-water river surrounded by peatlands. The limited degradability in the brown-water river was caused by a large number of terrestrial and aromatic compounds (i.e., highly unsaturated and phenolic compounds, condensed aromatics, and polyphenolics) from surrounding peatlands. In the clearwater river, the percentage of formulas assigned to aliphatics decreased over the incubation, indicating microbial utilization of biolabile DOM. This study highlights the importance of energy-rich, biolabile molecular compounds and the contribution of clearwater systems in the DOM degradation dynamics of subarctic catchments.

Tree resistance to uprooting can be estimated as the critical turning moment in tree-pulling experiments. The depth at the center point of rotation (Dcp) in tree-pulling experiments is measured as an indicator of below-ground traits and is related to this critical turning moment. However, few researchers have investigated the relationship between the Dcp and maximum root depth. Our objective in this study was to clarify whether the Dcp in tree-pulling experiments can be estimated as the maximum root depth of Pinus thunbergii Parl. in sandy soils. We also estimated which position of displacement of the center of rotation (Cp) can be applied as the Dcp. We conducted tree-pulling experiments, and compared the Dcp obtained from images with the measured maximum root depth. We found significant positive correlations between the Dcp and maximum root depth. The Cp displacement concentrated immediately below the stem when the maximum critical turning moment was reached. This position should be measured as the Dcp, which is related to the maximum root depth. We found that the Dcp can serve as a parameter, preventing the need for uprooting, when tree-pulling experiments are performed to obtain an important below-ground trait for understanding the critical turning moment.

Three-dimensional (3D) root system architecture (RSA) is a predominant factor in anchorage failure in trees. Only a few studies have used 3D laser scanners to evaluate RSA, but they do not check the accuracy of measurements. 3D laser scanners can quickly obtain RSA data, but the data are collected as a point cloud with a large number of points representing surfaces. The point cloud data must be converted into a set of interconnected axes and segments to compute the root system traits. The purposes of this study were: (i) to propose a new method for easily obtaining root point data as 3D coordinates and root diameters from point cloud data acquired by 3D laser scanner measurement; and (ii) to compare the accuracy of the data from main roots with intensive manual measurement. We scanned the excavated root systems of two Pinus thunbergii Parl. trees using a 3D laser scanner and neuTube software, which was developed for reconstructing the neuronal structure, to convert the point cloud data into root point data for reconstructing RSA. The reconstruction and traits of the RSA calculated from point cloud data were similar in accuracy to intensive manual measurements. Roots larger than 7 mm in diameter were accurately measured by the 3D laser scanner measurement. In the proposed method, the root point data were connected as a frustum of cones, so the reconstructed RSAs were simpler than the 3D root surfaces. However, the frustum of cones still showed the main coarse root segments correctly. We concluded that the proposed method could be applied to reconstruct the RSA and calculate traits using point cloud data of the root system, on the condition that it was possible to model both the stump and ovality of root sections.

<p>In recent ethological studies, the behaviors and interactions of animals have been recorded by digital video cameras and webcams, which provide high functionality at reasonable cost. However, extracting the behavioral data from these videos is a laborious and time-consuming manual task. We recently proposed a novel method for tracking unmarked multiple honeybees in a flat arena, and developed a prototype software named "K-Track". The K-Track algorithm successfully resolved nearly 90% of cases involving overlapped or interacted insects, but failed when such events happened near an edge of a circular arena, which is commonly employed in experiments. In the present study, we improved our K-Track algorithm by comparing the interaction trajectories obtained from forward and backward playing of video episodes. If the tracking results differed between the forward and backward episodes, the trajectory with lower maximum moving distance per frame is chosen. Based on this concept, we developed a new software, "K-Track-kai", and compared the performances of K-Track and K-Track-kai in honeybee tracking experiments. In the cases of 6 and 16 honeybees, K-Track-kai improved the tracking accuracy from 91.7% to 96.4% and from 94.4% to 96.7%, respectively.</p>