Soil Microbial Community Composition During Natural Recovery in the Loess Plateau, China

This study aimed to determine the characteristics of soil microbial community composition and its relationship with soil chemical properties during natural recovery in the Loess Plateau.The soil microbial community composition was analyzed by comparing the soil microbial phospholipid fatty acids（PLFAs） of eight croplands abandoned for 1,3,5,10,13,15,20,and 30 yr in the Dunshan watershed,northern Loess Plateau,China.The results showed that soil organic carbon,total nitrogen,soil microbial biomass carbon,and soil microbial biomass nitrogen significantly increased with the abandonment duration,whereas the metabolic quotient significantly decreased.The Shannon richness and Shannon evenness of PLFAs significantly increased after 10 yr of abandonment.Gram-negative,Gram-positive,bacterial,fungal,and total PLFAs linearly increased with increased abandonment duration.Redundancy analysis showed that the abandonment duration was the most important environmental factor in determining the PLFA microbial community composition.The soil microbial PLFAs changed from anteiso-to iso-,unsaturated to saturated,and short-to long-chain during natural recovery.Therefore,in the Loess Plateau,cropland abandonment for natural recovery resulted in the increase of the soil microbial PLFA biomass and microbial PLFA species and changed the microbial from chemolithotrophic to a more heterotrophic community.

Soil aggregation and aggregate associated organic carbon and total nitrogen under long-term contrasting soil management regimes in loess soil

This study investigated the effects of three contrasting soil management regimes and different nutrient treatments on the distribution of water-stable aggregates（〉2, 1–2, 0.5–1, 0.25–0.5, and 〈0.25 mm） and associated soil organic carbon（SOC） and total nitrogen（TN） content in loess soil. A 21-yr long-term experiment was performed, in which soil management regimes include cropland abandonment（Abandonment）, bare fallow（Fallow） and wheat-fallow cropping（Cropping）. Under Cropping, the following nutrient treatments were employed： control（CK, no nutrient input）, nitrogen only（N）, nitrogen and potassium（NK）, phosphorus and potassium（PK）, NP, NPK, and manure（M） plus NPK（MNPK）. Results demonstrated that Abandonment significantly increased the content of soil macro-aggregates（〉0.25 mm） and mean weight diameter（MWD） at 0–10 and 10–20 cm soil horizons compared with Cropping, whereas Fallow yielded lower values of above two parameters. Abandonment increased SOC and TN contents in all aggregate sizes by 17–62% and 6–60%, respectively, at 0–10 cm soil layer compared with Cropping. Conversely, Fallow decreased SOC and TN contents in all aggregates by 7–27% and 7–25%, respectively. Nevertheless, the three soil management regimes presented similar SOC contents in all aggregates at 10–20 cm soil horizon. Only Cropping showed higher TN content in 〉0.5 mm aggregates than the two other regimes. Consequently, Abandonment enhanced the partitioning proportions of SOC and TN in 〉1 mm macro-aggregates, and Fallow promoted these proportions in micro-aggregates compared with Cropping. Under Cropping, long-term fertilization did not affect the distribution of aggregates and MWD values compared with those under CK, except for NPK treatment. Fertilizer treatments enhanced SOC and TN contents in aggregates at all tested soil depths. However, fertilization did not affect the partitioning proportions of SOC and TN contents in all aggregates compared with CK. Comprehensive results showed that different soil management regimes generated varied patterns of SOC and TN sequestration in loess soil. Abandonment enhanced soil aggregation and sequestered high amounts of SOC and TN in macro-aggregates. Long-term amendment of organic manure integrated with NPK maintained soil aggregate stability and improved SOC and TN sequestration in all aggregates in loess soil subjected to dryland farming.

GEE-Based monitoring method of key management nodes in cotton production

The high-temporal-resolution monitoring of key management nodes in cotton management via agricultural remote sensing is vital forfield cotton macro-statistics,particularly for predicting cotton production and obtaining comprehensive data.This study examines Shihezi,Xinjiang as a case study,utilizing Sentinel-1 and Sentinel-2 data from 2019 to 2021.Three machine learning models(RF,SVM,and CART)were employed to extract annual crop classification area rasters,monitor weekly cultivation progress,and monitor abandoned cropland during the cultivation period.The results demonstrate that the random forest model has produced satisfactory results in gridded extraction for cotton classification areas,achieving the producer’s accuracy of the cotton category reached 98.5%,and the kappa coefficient is 0.947.Cotton cultivated in 2021 began is a week later than in 2020,yet exhibited a faster cultivate speed.The proportion of abandoned cottonfields in the study area rose in 2020 compared to 2019.The methodology presented in this study has a certain reference value for exploring the monitoring of continuous changes in crops over the years and macro-monitoring of important activities in the entire growth cycle.

Carbon dioxide exchange and biomass productivity of the herbaceous layer of a managed tropical humid savanna ecosystem in western Kenya

Aims Humid savannas,as a result of high precipitation amounts,are highly productive.they are also hotspots for land use change and potential sources of carbon dioxide(CO_(2))due to the large soil carbon(C)stocks.understanding how ecosystem CO_(2) exchange is influenced by changes arising from agricultural land use is vital in future management of these ecosystems and in responding to the ongoing shifts in manage-ment and climate.the aim of this study was to identify how ecosystem CO_(2) exchange and biomass productivity of the herbaceous layer of a humid savanna in Kenya respond to current management practices.Methods We used flux chambers to quantify CO_(2) fluxes,while monthly harvests were undertaken to determine biomass development of the herba-ceous layer of three sites that were(i)fenced to exclude livestock graz-ing,(ii)subjected to grazing by livestock and(iii)abandoned after being cultivated for maize production and also open to grazing by livestock.Important findingsthe peak aboveground biomass ranged between 380 and 1449 g m−2 and biomass production was significantly(P<0.05)lower in the grazed and abandoned plots.the maximum gross primary production(gPP)and net ecosystem CO_(2) exchange(NEE)ranged between 21.8±1.3 to 32.5±2.7 and−9.6±0.7 to−17.9±4.8μmol m−2 s−1,respectively.seasonal NEE fluctuations ranged between 10 and 21μmol m−2s−1,while spatial(among sites)differences ranged between 2 and 10μmol m−2 s−1.Ecosystem respiration(Reco)fluc-tuated between 5 and 10μmol m−2 s−1 during the growing sea-son.Reco was,however,not significantly different among the sites.unlike in other similar ecosystems where ecosystem respiration is determined by the ambient temperature,we did not find any rela-tionship between Reco and temperature in this savanna.Instead,soil moisture accounted for 38-88%of the spatial and seasonal fluc-tuations in ecosystem CO_(2) fluxes and aboveground biomass pro-duction.management influenced the maximum gPP and NEE rates through modification of soil moisture,plant species composition and aboveground biomass.We concluded that soil moisture is the key determinant of ecosystem CO_(2) exchange and productivity in this tropical savanna.management,however,significantly modifies C fluxes and productivity through its influence on soil moisture,plant species composition and aboveground green biomass and should be taken into consideration in future similar studies.