Legacy effects of temporary grassland in annual crop rotation on soil ecosystem services

Distinct prokaryotic and eukaryotic communities and networks in two agricultural fields of central Japan with different histories of maize-cabbage rotation

Crop rotation is an important agricultural practice for homeostatic crop cultivation. Here, we applied high-throughput sequencing of ribosomal RNA gene amplicons to investigate soil biota in two fields of central Japan with different histories of maize-cabbage rotation. We identified 3086 eukaryotic and 17,069 prokaryotic sequence variants (SVs) from soil samples from two fields rotating two crops at three different growth stages. The eukaryotic and prokaryotic communities in the four sample groups of two crops and two fields were clearly distinguished using β-diversity analysis. Redundancy analysis showed the relationships of the communities in the fields to pH and nutrient, humus, and/or water content. The complexity of eukaryotic and prokaryotic networks was apparently higher in the cabbage-cultivated soils than those in the maize-cultivated soils. The node SVs (nSVs) of the networks were mainly derived from two eukaryotic phyla: Ascomycota and Cercozoa, and four prokaryotic phyla: Pseudomonadota, Acidobacteriota, Actinomycetota, and Gemmatimonadota. The networks were complexed by cropping from maize to cabbage, suggesting the formation of a flexible network under crop rotation. Ten out of the 16 eukaryotic nSVs were specifically found in the cabbage-cultivated soils were derived from protists, indicating the potential contribution of protists to the formation of complex eukaryotic networks.

Dynamic of the Soil Microbiota in Short-Term Crop Rotation

Crop rotation is one of the oldest and most effective methods of restoring soil fertility, which declines when the same plant is grown repeatedly. One of the reasons for a reduction in fertility is the accumulation of pathogenic and unfavorable microbiota. The modern crop rotation schemes (a set of plant species and their order in the crop rotation) are highly effective but are designed without considering soil microbiota dynamics. The main goal of this study was to perform a short-term experiment with multiple plant combinations to access the microbiological effects of crop rotation. It could be useful for the design of long-term crop rotation schemes that take the microbiological effects of the crop rotation into account. For the analysis, five plants (legumes: vetch, clover, and cereals: oats, wheat, and barley) were used. These five plants were separately grown in pots with soil. After the first phase of vegetation, the plants were removed from the soil and a new crop was planted. Soil samples from all 25 possible combinations of primary and secondary crops were investigated using v4-16S rDNA gene sequencing. It was shown that the short-term experiments (up to 40 days of growing) are effective enough to find microbial shifts in bulk soil from different plants. Both primary and secondary cultures are significant factors for the microbial composition of microbial soil communities. Changes are the most significant in the microbial communities of vetch soils, especially in the case of vetch monoculture. Growing clover also leads to changes in microbiota, especially according to beta-diversity. Data obtained can be used to develop new crop rotation schemes that take into account the microbiological effects of various crops.

Mapping vegetation species succession in a mountainous grassland ecosystem using Landsat, ASTER MI, and Sentinel-2 data

Vegetation species succession and composition are significant factors determining the rate of ecosystem biodiversity recovery after being disturbed and subsequently vital for sustainable and effective natural resource management and biodiversity. The succession and composition of grasslands ecosystems worldwide have significantly been affected by accelerated environmental changes due to natural and anthropogenic activities. Therefore, understanding spatial data on the succession of grassland vegetation species and communities through mapping and monitoring is essential to gain knowledge on the ecosystem and other ecosystem services. This study used a random forest machine learning classifier on the Google Earth Engine platform to classify grass vegetation species with Landsat 7 ETM+ and ASTER multispectral imager (MI) data resampled with the current Sentinel-2 MSI data to map and estimate the changes in vegetation species succession. The results indicate that ASTER MI has the least accuracy of 72%, Landsat 7 ETM+ 84%, and Sentinel-2 had the highest of 87%. The result also shows that other species had replaced four dominant grass species totaling about 49 km2 throughout the study.

Ecosystem service multifunctionality assessment and coupling coordination analysis with land use and land cover change in China's coastal zones

Ecosystem services (ESs) have received widespread attention worldwide for their potential to solve sustainability issues. However, extensive land use and land cover change (LUCC) driven by human activities has raised concerns regarding its impacts on ESs, especially in coastal zones. More importantly, spatial-temporal changes, their coupling relationships with LUCC, and their underlying drivers have not been thoroughly analyzed. This study focuses on China's coastal zones to investigate the spatial-temporal changes of ecosystem service multifunctionality (ESM) from 2000 to 2018. Coupling coordination degree (CCD) analysis of the relationship between ESM and comprehensive intensity of land use was applied to identify coastal cities with low-level coordination and their main drivers in 2018. The results show that: (1) the proportion with high levels of ESM decreased by 1.01% from 2000 to 2010 and then increased by 3.29% from 2010 to 2018; (2) the ESM of China's coastal zones present significant spatial heterogeneity, and the low levels of ESM are mainly distributed in the north and urban areas, while most areas in the southern coastal zones have high levels of ESM; (3) forest land is the leading land cover type for ESM, and China's forest conservation policies significantly contribute to the increase in ESM; (4) the CCD of most cities in the southern coastal zones, apart from Shanghai and the Pearl River Delta, is at a relatively high level and experiences no significant changes, while most cities in the northern coastal zones display an improving trend; (5) the land use type, landform type, and leaf area index are the determinants of ESM, and the annual average temperature, population density, and surface elevation are the greatest influences on the CCD. The findings of this study can inform ecological conservation and landscape planning and are beneficial to the sustainable development of coastal zones in China.