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To identify the soil carbon stock changes from croplands/grasslands to forestlands in Japan, we compared the soil carbon stock of a cropland/grassland with that of an adjacent forestland at 22 different sites. With respect to a 0–30-cm depth basis, the soil carbon stock in the cropland/grassland was the same as that in the forestland; however, it was less than that in the forestland when an equivalent mass approach was used. The ratio of the soil carbon stock in the forestland to that in the cropland/grassland was 1.11 on average, which is comparable with previous mass-corrected paired sampling studies. The ratio was affected by two factors: tree age and current vegetation. Mean annual temperature, mean annual precipitation, phosphate absorption coefficient, litter quantity, and former land use did not affect the ratio. According to a comparison with the results of a paired study for deforestation, the application of the reciprocal of the soil carbon stock ratio of deforestation to the ratio of afforestation was slightly overestimated. Further studies are necessary to establish a general conclusion. Some previous studies, including those involving non-mass-corrected data, are possibly biased, and more studies using the paired sampling method with equivalent mass basis must be conducted to provide the general factor for soil carbon stock change in the future.

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-2year-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-2year-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.

High-resolution data on spatial variations in the productivity of bryophytes and the mass of the organic layer are important components in geochemical models for northern forests. We investigated spatial variations in growth rates of the feather moss Hylocomium splendens and the thickness of the organic layer in relation to environmental factors on a north-facing slope in Interior Alaska. The forest floor on the 600 m × 600 m slope was classified into four types, i.e., Classes I–IV, characterized mainly by the dominance of leaf litter, H. splendens, Pleurozium schreberi, and Sphagnum spp., respectively. Spatial autocorrelation analyses showed clustering patterns for some tree and forest floor variables, which were associated with the distribution of the four classes on the slope. Mean growth (length) rates of H. splendens were high in Class II, while growth rates by weight were high in Class I due to a high weight-to-length ratio of shoots. The thickness of the organic layer in bryophyte patches ranged from 6.0 to 40.7 cm and was also controlled by slope orientation. The presence of large trees, particularly Betula neoalaskana, mediated the relationship between topography and forest floor characteristics.

Black spruce (Picea mariana (Mill.) B.S.P.) is a dominant species on north-facing slopes located on the permafrost in the Alaskan Interior, where tree growth rates vary significantly across slope gradients. To better understand the effects of nitrogen (N) and mycorrhizal associations on plant growth, we investigated the relationships between tree growth and isotope ratios of nitrogen (δ15N) in foliage and roots, because plant δ15N values reflect tree dependencies on N uptake by mycorrhizae. We established two transects (one along a slope gradient, and a second on a north-to-east axis at a fixed elevation) and four plots on the slope gradient transect. We measured current shoot growth of saplings on transects and aboveground biomass (AGB) in the plots. We collected foliage and fine root samples and measured their δ15N signatures and N concentrations. The AGB and shoot growth varied widely across the gradient: values were higher at high elevations and at the east–northeast aspect. Foliage δ15N values and N concentrations were positively correlated with tree growth, but growth rate was negatively correlated with the dependency on mycorrhizae for N uptake. Thus, black spruce had a reduced dependency on mycorrhizae for N uptake on the upper slope, where conditions were N-rich. On the lower slope, where the soil active layer was shallow, black spruce growth was limited and had an elevated dependency on mycorrhizae for N uptake.

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.

The Atlantic Forest, Humid Chaco, and Dry Chaco are major eco-regions in Paraguay, but information on forest carbon stocks in these forest types remains limited. To establish a system to measure, report and verify forest carbon change under the REDD+ mechanism, we developed new allometric equations to estimate tree biomass in each eco-region. Three models of total and aboveground biomass were developed from destructive sampling data. The models performed well, explaining ≥96% of the variation in aboveground and total biomass, although the best model differed among the eco-regions. The inclusion of height and wood density improved fit in the Atlantic Forest model, but including wood density did not enhance the Humid and Dry Chaco models. Our models will improve the estimation of biomass in Paraguay because they provide better estimates of total and aboveground biomass in each eco-region than pan-tropical generic models. Discipline: Forestry and forest products Additional key words: allometric models, Atlantic forests, Chaco forests, living biomass including root, REDD-plus * Corresponding author: satoo@affrc.go.jp Received 24 September 2014; accepted 20 November 2014. Introduction The REDD+ mechanism (Reducing Emissions from Deforestation and forest Degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries) provides financial incentives to help developing countries establish ways to reduce emissions from deforestation and forest degradation. Because the measurement, reporting, and verification (MRV) of forest carbon change are indispensable for REDD implementation, the use of a ground-based inventory with remote sensing is recommended to monitor carbon stocks on a national scale (UNFCCC 2009). For a ground-based inventory, permanent sample plots allow the monitoring of carbon stocks by area (e.g. Fox et al. 2010, Samreth et al. 2012). Estimates of carbon stocks in living biomass can be obtained using allometric equations with measured field variables such as diameter and tree height in the plots (Metzker et al. 2012). However, the main source of uncertainty in biomass estimates lies in the choice of allometric model (Molto et al. 2013). Although the proportion of forested area has continuously declined during the last 20 years in Paraguay (Huang et al. 2007), information on forest carbon stocks and allometric models remains limited. Generic allometric equations developed by Chave et al. (2005) can be used to estimate forest biomass and carbon stocks across diverse tropical forest types (Gibbs et al. 2007, Asner et al. 2009, Mitchard et al. 2013), including Atlantic Forest (Vieira et al. 2008) and Humid and Dry Chaco (Gasparri et al.

Litter plays key roles in forest ecosystems, and forest degradation is likely to spur a further decline in leaf litterfall inputs to forest soils. However, the effects on physicochemical surface-soil properties remain largely unknown, especially in seasonal tropical forest ecosystems. We initiated a litterremoval manipulation experiment in a Cambodian lowland evergreen forest undergoing intensive selective logging. Litter removal performed for 2 and 4.4 years respectively triggered an increase in bulk density and decrease in surface-soil carbon (C) and nitrogen (N) contents to 67 and 73% of the original levels, respectively. After only 2 years of treatment, bulk density rose to very high value (>1.40 Mg m) likely preventing further soil compaction, while the C and N reduction effects lasted over 2 years. Greater soil compaction occurs in stands with a smaller initial bulk density. However, C (N)-rich soils did not necessarily lose a greater relative proportion of C (N) than C (N)-poor soils. Although N remained above C following the litter removal, conservative trends in the C:N ratio suggested a limited capacity for N retention. Together, our data suggest that shifts in leaf litter inputs in response to localized human disturbances may have rapid and lasting consequences on physicochemical surface-soil properties; possibly accelerated by a tropical climate. Moreover, a speedy recovery to an adequate litter supply, at least before reaching the upper soil compaction limit, is essential to conserve forest ecosystems. Discipline: Soils, fertilizers and plant nutrition Additional key words: bulk density, carbon, forest degradation, nitrogen, soil compaction

As a feasibility study for applying a simplified method to estimate CO2 emissions from deforestation and forest degradation in tropical forests, we estimated the nationwide forest tree biomass carbon stock using data from 100 permanent sampling plots (PSPs) set by the Forestry Administration, Cambodia in seasonal forests in Cambodia. Averaged tree carbon stocks and SE-Standard error were at 158.8 ± 7.3 Mg C ha-1 for evergreen and semi-evergreen forests and 55.2 ± 6.9 Mg C ha-1 for deciduous forests in 1998 (the first census) and for the second census in 2000-2001, 163.8 ± 7.8 Mg C ha-1 and 56.2 ± 6.7 Mg C ha-1, respectively. The averaged tree biomass carbon stock differed significantly between the two forest types. Using the forest cover for 2006 and the averaged carbon stock for 2000-2001, the national-level forest tree carbon stock in the early to mid-2000s was estimated at 824.2 ± 39.2 Tg C for evergreen forests and 263.9 ± 31.3 Tg C for deciduous forests, and 1,088.1 ± 50.2 Tg C in total. By repeating this calculation for all forest areas by remote sensing and averaged tree carbon stock via ground-based measurement with PSPs, we could monitor the total tree carbon stock in nationwide forests in Cambodia. We also presented the possible reasons for uncertainty related to the present tree biomass carbon stock of forests and recommendations in order to improve the accuracy of the carbon stock using PSP systems in Cambodia.

Forest soils in the basalt region of Southeast Asia are important natural resources, due to their high agricultural potential and high capacity for carbon sequestration. To characterize the physicochemical properties and the components of the soil organic carbon of forest soils in the basalt region, five evergreen sites (E1–5) and one deciduous forest site (D1) were selected in Cambodia at elevations ranging from 132 to 908 m. The components of the soil organic carbon of each site were separated using a density fractionation approach, i.e. high(≥ 1.6 g cm−3) and low( 600 m), were strongly weathered and characterized by a lower pH, a lower level of exchangeable bases, and a more reddish color than the other evergreen forest soils. The soils of sites E3 and E4, located on a hillside and at the base of a hill, respectively, had a high soil effective cation exchange capacity in the B horizons compared to those at sites E1–2 and E5. The soil of site E5 in the isolated basalt region had characteristics resembling those in sites E1–2 except for its high exchangeable aluminum content. The site D1 soil on a hillside was relatively young and shallow, and black in color. The carbon stock in the six forest sites (0–30 cm in depth) was 40.8– 113.7 Mg C ha−1 for high-density fractions and 3.3–7.6 Mg C ha−1 for low-density fractions, respectively. The differences in vegetation types (deciduous vs. evergreen forests), mean annual temperature and free aluminum contents among forest sites were considered factors affecting the carbon content and carbon to nitrogen (C/N) ratio of high-density fractions. It was considered that the variously weathered parent materials, regulated by the relative position in the basalt plateau, were responsible for the gradient of soil morphology and soil nutrient conditions and characterized the soil carbon stock in the study area. Discipline: Forestry and forest products Additional key words: tropical monsoon forest * Corresponding author: e-mail jtori@affrc.go.jp Received 29 May 2012; accepted 19 September 2012.

We studied the relationships among the soil C stock in tropical monsoon forests, the type of forest, and the environmental factors in the lower Mekong basin in Cambodia. We analyzed nine soil profiles in evergreen and deciduous forests growing over sedimentary rock and basalt. Evergreen forest soils tended to have a larger C stock than deciduous forest soils within geological formations. In evergreen and deciduous forest soils, carbon stocks were 56.9 ± 30.0 (mean ± SD) and 34.9 ± 23.5 Mg C ha-1, respectively, in the 0- to 30-cm depth range, and 108.7 ± 53.0 and 53.2 ± 30.4 Mg C ha-1, respectively, in the 0- to 100-cm depth range. Soil C stock was highly positively correlated with soil water content in the dry season, which is likely affected by the openness of the forest canopy and by soil clay content.

We examined non-destructive methodologies for practicalities in monitoring anthropogenic greenhouse gas (GHG) emissions from tropical dry-land forest under the influence of various forms of human intervention. Spaceborne SAR withstood comparison with Landsat ETM+ in land cover classification of degraded tropical forest. For measurement of carbon stock and GHG flux per unit land area, the gain-loss method requires both growth rate and removal rate of forest carbon stock. However, the latter has rarely been obtained in tropical forest. For the stock-difference method, permanent sampling plot data can be used to estimate mean carbon stock per unit land area of each forest type. For cyclic land use that includes a clear-cutting stage such as slash-and-burn agriculture, chronosequential changes in carbon stock can be predicted by determining the time and spatial-distribution of cleared land. Changes in forest biomass by logging, storm-damage, etc., may be identified by monitoring the presence and diameter of the crowns of overstory trees. We developed five equations containing the parameter for crown diameter for estimating tree biomass. Overstory height can be a parameter for estimating ecosystem carbon stock of various plant communities, and forest height can be measured by airborne and spaceborne sensors, etc. Generic equations containing the parameter for overstory height are available for estimating community biomass of tropical and subtropical forests. PALSAR has an advantage over other remote systems by enabling frequent sensing and semi-direct biomass estimation using backscattering coefficients. However, no reasonable remote sensing methods exist for monitoring the amount of carbon loss by forest conversion and logging in forests with high biomass. To compensate for the faults of the present PALSAR methodologies and to enable practical and frequent monitoring of all types of forests by humans, it is vital to devise a new methodology to detect changes in high-biomass forests.

The global forest carbon (C) stock is estimated at 662 Gt of which 45% is in soil organic matter. Thus, comprehensive understanding of the effects of forest management practices on forest soil C stock and greenhouse gas (GHG) fluxes is needed for the development of effective forest-based climate change mitigation strategies. To improve this understanding, we synthesized peer-reviewed literature on forest management practices that can mitigate climate change by increasing soil C stocks and reducing GHG emissions. We further identified soil processes that affect soil GHG balance and discussed how models represent forest management effects on soil in GHG inventories and scenario analyses to address forest climate change mitigation potential. Forest management effects depend strongly on the specific practice and land type. Intensive timber harvesting with removal of harvest residues/stumps results in a reduction in soil C stock, while high stocking density and enhanced productivity by fertilization or dominance of coniferous species increase soil C stock. Nitrogen fertilization increases the soil C stock and N2O emissions while decreasing the CH4 sink. Peatland hydrology management is a major driver of the GHG emissions of the peatland forests, with lower water level corresponding to higher CO2 emissions. Furthermore, the global warming potential of all GHG emissions (CO2, CH4 and N2O) together can be ten-fold higher after clear-cutting than in peatlands with standing trees. The climate change mitigation potential of forest soils, as estimated by modelling approaches, accounts for stand biomass driven effects and climate factors that affect the decomposition rate. A future challenge is to account for the effects of soil preparation and other management that affects soil processes by changing soil temperature, soil moisture, soil nutrient balance, microbial community structure and processes, hydrology and soil oxygen concentration in the models. We recommend that soil monitoring and modelling focus on linking processes of soil C stabilization with the functioning of soil microbiota. This review has been supported by the grant Holistic management practices, modelling and monitoring for European forest soils – HoliSoils (EU Horizon 2020 Grant Agreement No 101000289) and the Academy of Finland Fellow project (330136, B. Adamczyk). In addition to the HoliSoils consortium partners, Dr. Abramoff contributed on this study and her work was supported by the United States Department of Energy, Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the United States Department of Energy under contract DE-AC05- 00OR22725.