As an important soil carbon pool in Qinghai-Tibet Plateau (QTP), alpine peatland are extremely sensitive to global change. Duration of drainage and water table drawdown accelerate peatland degradation due to the soil changed from anaerobic condition to aerobic condition, which may even worsen under climate warming. Hence, the objective of our research was to evaluate the effect of drainage on microbial characteristics, greenhouse gas (GHG) emissions and their influencing factors, and further analyze whether the the variability of GHG emissions increases with warming. The results showed that the influence of water table drawdown on microbial communities were greater than that of duration of drainage. Both the fungal and prokaryotic community compositions varied with water table gradient, and soil microbiota may served as a biomarker to analyze the differences in GHG emissions among three different water table treatments. Intriguingly, the GHG emission decreased with the increase of drainage age, while water table drawdown decreased the emissions of CO2 and CH4, and increased the emission of N2O. In addition, high temperature increased CO2 by 75% and N2O by 42%, but not significantly decreased the CH4 emission rates. Structural equation modeling showed that microbe was the primary factor affecting GHG emissions from drained peatlands, especially prokaryotes. In all, this study indicate water table has a greater effect on GHG emissions than duration of drainage, and the variability of GHG emissions increases with warming.

This study’s objective was to develop a method by which smallholder forest plantations can be mapped accurately in Andhra Pradesh, India, using multitemporal visible and near-infrared (VNIR) bands from the Sentinel-2 MultiSpectral Instruments (MSIs). Conversion to agriculture, coupled with secondary dependencies on and scarcity of wood products, has driven the deforestation and degradation of natural forests in Southeast Asia. Concomitantly, forest plantations have been established both within and outside of forests, with the latter (as contiguous blocks) being the focus of this study. Accurately mapping smallholder forest plantations in South and Southeast Asia is difficult using remotely sensed data due to the plantations’ small size (average of 2 hectares), short rotation ages (4-7 years for timber species), and spectral similarities to croplands and natural forests. Cloud-free Harmonized Landsat Sentinel-2 (HLS) S10 data was acquired over six dates, from different seasons, over four years (2015-2018). Available in situ data on forest plantations was supplemented with additional training data resulting in 2,230 high-quality samples aggregated into three land use classes: non-forest, natural forest, and forest plantations. Image classification used random forests on a thirty-band stack consisting of the VNIR bands and NDVI images for all six dates. The median classification accuracy from the 5-fold cross-validation was 94.3%. Our results, predicated on high-quality training data, demonstrate that (mostly smallholder) forest plantations can be separated from natural forests even using only the Sentinel-2 VNIR bands when multitemporal data (across both years and seasons) are used.

Violence in Rakhine, Myanmar forcibly displaced nearly one million Rohingya who took refuge in Cox’s Bazar–Teknaf peninsula of Bangladesh. Initially, nearly 2,000 ha of forested lands had to be cleared to accommodate them in an area, that is ecologically very sensitive. Fuelwood collection and illegal logging have become widespread since their arrival, causing severe environmental degradation, including loss of a vast amount of forest cover. To devise conservation strategies of a highly sensitive ecosystem, it is imperative to understand the degree of forest cover deterioration and associated impacts related to Rohingya emigration. This study employed satellite images to monitor and model spatiotemporal pattern of forest cover degradation, and loss of ecosystem function in the peninsula. Supervised classification method was used to derive multidate land use/cover data which was then utilized to monitor spatiotemporal pattern of forest cover change from 2017–2019. Dynamic modelling was performed to predict changes in the forest covers using markov cellular automata. Analysis revealed that 3,130 ha of different forested covers were transformed into either refugee camps or degraded forest cover between 2017 and 2019. Prediction showed that around 5,115 ha of forest may experience loss from 2019–2027. Furthermore, above ground biomass and carbon stock estimation indicated a consistent loss, which is likely to swell if present rate of deforestation continues. The findings of this work have considerable implications in developing conservation decisions, priority interventions and public policies to save an ecologically sensitive area.

This paper examines land use patterns of rural households and the association with food production and income across three different zones of various forest proximity across a landscape gradient (remote, intermediate and on-road) in the Chittagong Hill Tracts region of Bangladesh. We conducted in-depth semi-structured surveys of households (175-300) and farm owners (30) to collect information on people’s perceptions of land use change, present land use patterns and contributions to food production and income. Our research found that more than half of the surveyed households experienced a decline in the land available for food production over the past 30 years. The land use patterns revealed decreasing crop lands (mainly swidden farms) and an increase in areas of planted trees. However, household use of the reduced crop land has not affected food production in the on-road zone, whereas the diversity of food sources has declined. People living in more remote areas used larger areas of crop (swidden farms) and fallow lands, fruit orchard and accessed natural forest lands that provide a diverse reservoir of food sources. The current land uses contribute to variations in annual household income, with remote dwelling people earning less to those living in the intermediate and on-road zones. In summary, this transition of land uses over three decades and changes in income and food availability cannot be generalised across the region because of zone specific differences. We recommend a broader and context-reliant landscape management approach in consideration of the diversity of forest and tree benefits.

Over the past 90 years, anthropogenic degradation of soil caused by alkaline, magnesium-rich dust deposit has presented a serious problem near magnesite processing factories in Jelšava and in Lubeník (Slovakia). The objective of this study was to investigate the chemical and biological soil properties in 14 sampling sites at different distances from factories, and based on the results, to propose further use of affected land. Results revealed that the available Mg 3–68 fold exceeded very high content for texturally medium soils at all grassland sampling sites, and areas close factory contained up to 14.4–17.4 g kg-1. Higher excess of available Mg caused significant increase of soil pH (up to 9.39) and worsened the conditions for the growth of vegetation. As a result, lower stock of newly formed organic matter (0.50–0.96 g kg-1 of labile carbon) with consequently weaker enzymatic activity occurred. Therefore, enrichment by organic matter provides a measure to support the biological activity of soil. The content of monitored heavy metals (Zn, Cu, Pb and Ni) was not related to Mg and did not influence the enzymatic activity of soil. Because alkaline emissions have decreased by 99.8% since 1970, the application of classical measures (mechanical removal of the Mg-rich crust, incorporation of gypsum and manure to the soil), or newer methods (growing of Mg hyper-accumulating plants) can offer more lasting positive effects than those of 50 years ago. This study concluded that Mg-rich, alkaline dust deposition causes long-lasting anthropogenic soil degradation.

Grazing exclusion (GE) has been applied as a suitable strategy to soil conservation worldwide, mainly in semiarid soils. However, it is unclear how GE management reduces the negative effects of overgrazing on the microbial community. In this study, we assessed the bacterial community in three different soil management belonged to a semiarid region from the Brazilian Caatinga biome, as follows: Native Caatinga (NC), Grazing exclusion (GE), and a highly degraded area by Overgrazing (OG). The bacterial community was assessed through the sequencing of the V4 region of the 16S rRNA gene. We also analyzed soil chemical and physical properties and correlated with bacterial community composition, and α- and β- diversities. Our results demonstrated that GE increases the content of soil C, N, and bacterial diversity. However, the changes in bacterial diversity were significant in a specific site (nº 1), suggesting that GE strategy could be a context-dependent and a complex approach to Caatinga soils. Moreover, overgrazing might restrain the potential of bacterial diversity to sustain ecosystem functions, since non-beneficial elements (e.g., Na+ and Al3+) increased in OG, which presented a negative correlation with the bacterial community. Our study provides novel evidence that high-intensity disturbance by overgrazing could not only reduce soil fertility, but it may also restrain bacterial composition, with implications on environmental functioning. Thus, the Caatinga soil microbiome may be unable to maintain ecosystem services such as plant and animals’ development under overgrazing management.

Tidal marsh wetlands in the Yellow River Delta provide valuable eco-services to the local population and global ecology. However, this area is suffering from serious degradation under the stresses of social development and climate change. Hydrological connectivity, a new framework in hydrology and ecology, has been proposed as the main factor affecting the ecological processes in coastal wetlands; however, its role in hydrology–soil–vegetation interactions remains unclear. In this study, the researchers parametrically quantified the hydrological connectivity in the tidal marsh wetlands and analyzed its relationship with Phragmites australis, one of the dominant species in this area. Our results showed threshold-like effects on the interaction between hydrological connectivity and P. australis on the plot scale. When biomass is lower than 2.2 kg/m2, the population density and structure size were found to increase with hydrological connectivity. When the biomass is higher than the threshold, the plots disconnected hydrologically because of high water consumption. Compared with soil chemistry, salinity, and water soil content, hydrological connectivity in the surface soil layer is more strongly linked to the plant traits and spatial structure in the tidal marsh wetlands due to the narrow ranges of other variables. Based on the authors’ analysis, the researchers do not recommend dense plantation of P. australis, especially near the freshwater sources in the tidal marsh, because of its high reproduction ability and competitive nature, which may cut the freshwater connectivity off, lowering the richness of plant species and habitat diversity.

The black soil region of northeast China is one of the most productive regions of the world. The depth of A horizon is rapidly decreasing due to excessive erosion. A strategy for erosion hazard evaluation and soil conservation planning has been proposed and tested on the region. Climate, geomorphology, DEM, soil, landuse, runoff plot and corn yield data were compiled. Soil erosion rate, A horizon thickness and corn yield under six conservation scenarios during 2020~2200 was predicted. The six scenarios include Present (continue present practices), Contour (contour tillage), Straw (straw incorporated in tillage layer), Combo 1 (contour tillage and terracing etc.), No-till (no-till farming) and Combo 2 (partially Combo 1 and partially No-till). Current soil life expectancy of A horizon (SLEA), which is the time until a critical horizon thickness needed for sustaining crop production is reached, was calculated for each scenario. Erosion hazard degrees were determined with SLEA. Croplands with SLEA of <0 a, 0 a~20 a, 20 a~100 a, 100 a~1000 a and ≥1000 a, were classified as “Damaged”, “High hazard”, “Moderate hazard”, “Low hazard” and “No hazard”, respectively. Current area ratio of “Damaged” and “High hazard” and “Moderate hazard” was found to be 8%, 5%, and 22%, respectively. The optimum conservation practice was found to be No-till for “Damaged”, “Combo 2” for “High hazard”, “Moderate hazard” and “Low hazard” and Present for “No hazard”. An optimum conservation schedule was also suggested for each township to maintain all soils to have an A horizon above 20 cm.