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Intensive management is known to markedly alter soil carbon (C) storage and turnover in Moso bamboo forests compared with extensive management. However, the effects of intensive management on soil respiration (RS) components remain unclear. This study aimed to evaluate the changes in different RScomponents (root, mycorrhizal, and free-living microorganism respiration) in Moso bamboo forests under extensive and intensive management practices. A 1-year in-situmicrocosm experiment was conducted to quantify the RScomponents in Moso bamboo forests under the two management practices using mesh screens of varying sizes. The results showed that the total RSand its components exhibited similar seasonal variability between the two management practices. Compared with extensive management, intensive management significantly increased cumulative respiration from mycorrhizal fungi by 36.73%, while decreased cumulative respiration from free-living soil microorganisms by 8.97%. Moreover, the abundance of arbuscular mycorrhizal fungi (AMF) increased by 43.38%, but bacterial and fungal abundances decreased by 21.65% and 33.30%, respectively, under intensive management. Both management practices significantly changed the bacterial community composition, which could be mainly explained by soil pH and available potassium. Mycorrhizal fungi and intensive management affected the interrelationships between bacterial members. Structural equation modeling indicated that intensive management changed the cumulative RSby elevating AMF abundance and lowering bacterial abundance. We concluded that intensive management reduced the microbial respiration-derived C loss, but increased mycorrhizal respiration-derived C loss.

ABSTRACTHosts can initiate macroautophagy/autophagy as an antiviral defense response, while viruses have developed multiple ways to evade the host autophagic degradation. However, little is known as to whether viruses can target lipids to subvert autophagic degradation. Here, we show that a low abundant signaling lipid, phosphatidylinositol 3,5-bisphosphate (PtdIns(3,5)P2), is required for rice black-streaked dwarf virus (RBSDV) to evade the autophagic degradation in the insect vector Laodelphax striatellus. RBSDV binds to PtdIns(3,5)P2and elevates its level through its main capsid protein P10, leading to inhibited autophagy and promoted virus propagation. Furthermore, we show that PtdIns(3,5)P2inhibits the autophagy pathway by preventing the fusion of autophagosomes and lysosomes through activation of Trpml (transient receptor potential cation channel, mucolipin), an effector of PtdIns(3,5)P2. These findings uncover a strategy whereby a plant virus hijacks PtdIns(3,5)P2via its viral capsid protein to evade autophagic degradation and promote its survival in insects.

Integrating land use type and other geographic information within spatial interpolation has been proposed as a solution to improve the performance and accuracy of soil nutrient mapping at the regional scale. This study developed a non–algorithm approach, i.e.,applying inverse distance weighting (IDW) and ordinary kriging (OK), to individual land use types rather than to the whole watershed, to determine if this improved the performance in mapping soil total C (TC), total N (TN), and total P (TP) in a 200–km2urbanizing watershed in Southeast China. Four land use types were identified by visual interpretation as forest land, agricultural land, green land, and urban land. One hundred and fifty soil samples (0–10 cm) were taken according to land use type and patch size. Results showed that the non–algorithm approach, interpolation based on individual land use types, substantially improved the performance of IDW and OK for mapping TC, TN, and TP in the watershed. Root mean square errors were reduced by 3.9% for TC, 10.7% for TN, and 25.9% for TP by the application of IDW, while the improvements by OK were slightly lower as 0.9% for TC, 7.7% for TN, and 18.1% for TP. Interpolations based on individual land use types visually improved depiction of spatial patterns for TC, TN, and TP in the watershed relative to interpolations by the whole watershed. Substantial improvements might be expected with denser sampling points. We suggest that this non–algorithm approach might provide an alternative to algorithm–based approaches to depict watershed–scale nutrient patterns.