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Forests worldwide store large quantities of carbon (C), particularly in soils as soil organic C (SOC). In northeastern China, two dominant forest types, secondary mixed forest (MF) and larch plantation forest (LF), cover extensive areas. However, we lack an understanding of the patterns and the mechanisms of SOC storage and stabilization in MF and LF, especially in deep soil layers. This research aims to illustrate the vertical distribution and mineral protection of SOC over soil depth; we also used δ13C values of soil fractions to evaluate SOC stability. Samples from the surface litter (Oi), organic layer (Oa+e), and 0–40 cm mineral soils were collected from both MF and LF plots. We used two different methods to separate bulk soils into distinguished fractions: (1) macro- and micro-aggregates and the non-aggregated fraction, and (2) particulate organic matter (POM) and mineral-associated organic matter (MAOM). The C concentrations, C stocks, and δ13C of all soil fractions were determined. Our findings were as follows: (1) SOC was mainly stored in mineral soils and was 13.6% lower in LF (8609 ± 1180 g C m−2) than MF (9969 ± 2084 g C m−2). (2) In both MF and LF, the SOC stock was mainly stored in aggregates (averaged 92.7%); macroaggregates dominated in the surface layers (Oa+e layer and 0–10 cm) but microaggregates dominated in the deep layers (10–20 cm and 20–40 cm). In mineral soils, MAOM was the dominant fraction of the C stock (averaged 81.6%). (3) The proportion of C distributed in microaggregates and MAOM increased from Oa+e to the 20–40 cm layer. (4) The C/N ratios and δ13C values of MAOM were smaller and heavier compared to those of POM. Our study demonstrated that in both forests, aggregate formation and mineral association predominantly contributed to SOC storage, and large stocks of SOC were distributed in the deep soil. The increasing proportion of SOC in microaggregates and MAOM along the soil depth, most likely derived from microbial turnover and microbial necromass, influenced SOC stability in both forest types. [ABSTRACT FROM AUTHOR]

Emissions of dinitrogen (N2) and nitrous oxide (N2O) from soil are important components of the global nitrogen cycle. Soil N2O emissions from terrestrial ecosystems have been well studied. However, patterns and mechanisms of N2 emissions remain unclear due to the technical difficulty in measuring N2 production. In this study, an in situ 15N labeling method was employed to determine soil N2 and N2O emission rates from the lower, middle, and upper slopes, which correspond to different moisture conditions, in a temperate forest in Northeast China. We found that N2 emissions varied from 85 to 3442 μg N m−2 h−1 across the slopes and were dominated by denitrification. The emissions of bulk N2O (22 to 258 μg N m−2 h−1) and denitrification-derived N2O (14 to 246 μg N m−2 h−1) were significantly lower than N2 emissions from their corresponding slope positions. Both N2 and N2O emissions significantly increased when soils become wetter. The ratios of N2O/(N2O + N2) were significantly higher at the upper and middle slopes (0.22 and 0.20, respectively) compared with those at the lower slope (0.08 ± 0.01). At the catchment scale, N2 accounted for 85% of the total gaseous N losses (N2O + N2). Our study shows that soil moisture drives the patterns of N2 and N2O emissions and field quantification of N2O/(N2O + N2) ratio should further consider the effect of slope position of forest ecosystems to estimate total soil gaseous N losses. [ABSTRACT FROM AUTHOR]

The individual identification of group-housed pigs plays an important role in breeding process management and individual behavior analysis. Recently, livestock identification methods based on the side view or face image have strict requirements on the position and posture of livestock, which poses a challenge for the application of the monitoring scene of group-housed pigs. To address the issue above, a Weber texture local descriptor (WTLD) is proposed for the identification of group-housed pigs by extracting the local features of back hair, skin texture, spots, and so on. By calculating the differential excitation and multi-directional information of pixels, the local structure features of the main direction are fused to enhance the description ability of features. The experimental results show that the proposed WTLD achieves higher recognition rates with a lower feature dimension. This method can identify pig individuals with different positions and postures in the pig house. Without limitations on pig movement, this method can facilitate the identification of individual pigs with greater convenience and universality. [ABSTRACT FROM AUTHOR]

In order to understand the impact of individual communities on global sustainability, we need a community sustainability assessment system (CSAS). While many sustainability assessment systems exist, they prove inadequate to the task. This article presents the results of a systematic review of the literature on existing sustainability assessment systems; offers a definition of a sustainable community; provides a multi-scale, systems approach to thinking about community; and makes recommendations from the field of performance measurement for the construction of a CSAS. [ABSTRACT FROM AUTHOR]