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Permafrost forests play an important role in the global carbon budget due to the huge amounts of carbon stored below ground in these ecosystems. Although fine roots are considered to be a major pathway of belowground carbon flux, separate contributions of overstory trees and understory shrubs to fine root dynamics in these forests have not been specifically characterized in relation to permafrost conditions, such as active layer thickness. In this study, we investigated fine root growth and morphology of trees and understory shrubs using ingrowth cores with two types of moss substrates (feather- and Sphagnum mosses) in permafrost black spruce (Picea mariana) stands along a north-facing slope in Interior Alaska, where active layer thickness varied substantially. Aboveground biomass, litterfall production rate, and fine root mass were also examined. Results showed that aboveground biomass, fine root mass, and fine root growth of black spruce trees tended to decrease downslope, whereas those of understory Ericaceae shrubs increased. Belowground allocation (e.g., ratio of fine root growth/leaf litter production) increased downslope in both of black spruce and understory plants. These results suggested that, at a lower slope, belowground resource availability was lower than at upper slope, but higher light availability under open canopy seemed to benefit the growth of the understory shrubs. On the other hand, understory shrubs were more responsive to the moss substrates than black spruce, in which Sphagnum moss substrates increased fine root growth of the shrubs as compared with feather moss substrates, whereas the effect was unclear for black spruce. This is probably due to higher moisture contents in Sphagnum moss substrates, which benefited the growth of small diameter (high specific root length) fine roots of understory shrubs. Hence, the contribution of understory shrubs to fine root growth was greater at lower slope than at upper slope, or in Sphagnum than in feather-moss substrates in our study site. Taken together, our data show that fine roots of Ericaceae shrubs are a key component in belowground carbon flux at permafrost black spruce forests with shallow active layer and/or with Sphagnum dominated forest floor.

Spatiotemporal prediction of the response of planted forests to a changing climate is increasingly important for the sustainable management of forest ecosystems. In this study, we present a methodology for estimating spatially varying productivity in a planted forest and changes in productivity with a changing climate in Japan, with a focus on Japanese cedar (Cryptomeria japonica D. Don) as a representative tree species of this region. The process-based model Biome-BGC was parameterized using a plant trait database for Japanese cedar and a Bayesian optimization scheme. To compare productivity under historical (1996-2000) and future (2096-2100) climatic conditions, the climate scenarios of two representative concentration pathways (i.e., RCP2.6 and RCP8.5) were used in five global climate models (GCMs) with approximately 1-km resolution. The seasonality of modeled fluxes, namely gross primary production, ecosystem respiration, net ecosystem exchange, and soil respiration, improved after two steps of parameterization. The estimated net primary production (NPP) of stands aged 36-40 years under the historical climatic conditions of the five GCMs was 0.77 ± 0.10 kgC m-2 year-1 (mean ± standard deviation), in accordance with the geographical distribution of forest NPP estimated in previous studies. Under the RCP2.6 and RCP8.5 scenarios, the mean NPP of the five GCMs increased by 0.04 ± 0.07 and 0.14 ± 0.11 kgC m-2 year-1, respectively. The increases in annual NPP were small in the southwestern region because of the decreases in summer NPP and the small increases in winter NPP under the RCP2.6 and RCP8.5 scenarios, respectively. Under the RCP2.6 scenario, Japanese cedar was at risk in the southwestern region, in accordance with previous studies, and monitoring and silvicultural practices should be modified accordingly.

We investigated the capabilities of a canopy height model (CHM) derived from aerial photographs using the Structure from Motion (SfM) approach to estimate aboveground biomass (AGB) in a tropical forest. Aerial photographs and airborne Light Detection and Ranging (LiDAR) data were simultaneously acquired under leaf-on canopy conditions. A 3D point cloud was generated from aerial photographs using the SfM approach and converted to a digital surface model (DSMP). We also created a DSM from airborne LiDAR data (DSML). From each of DSMP and DSML, we constructed digital terrain models (DTM), which are DTMP and DTML, respectively. We created four CHMs, which were calculated from (1) DSMP and DTMP (CHMPP); (2) DSMP and DTML (CHMPL); (3) DSML and DTMP (CHMLP); and (4) DSML and DTML (CHMLL). Then, we estimated AGB using these CHMs. The model using CHMLL yielded the highest accuracy in four CHMs (R2 = 0.94) and was comparable to the model using CHMPL (R2 = 0.93). The model using CHMPP yielded the lowest accuracy (R2 = 0.79). In conclusion, AGB can be estimated from CHM derived from aerial photographs using the SfM approach in the tropics. However, to accurately estimate AGB, we need a more accurate DTM than the DTM derived from aerial photographs using the SfM approach. [ABSTRACT FROM AUTHOR]