Arbuscular mycorrhizal (AM) fungi can form symbiosis with 90% of the vascular plants and play important roles in ecosystem. To realize the AM fungal colonization at different succession stages in saline-alkali land and screen AM fungi species with great functions, roots and soil samples were collected from the three succession stages of Songnen saline-alkali grassland. The soil properties and AM fungal colonization were measured, and the fungus distributed extensively in three stages was annotated by sequencing for AML1/AML2 target, subsequently, maize was selected as the host to verify its colonization. The results showed that the soil properties improved with the succession of saline-alkali grassland. The plants’ communities of the three stages could be colonized by AM fungi, and the colonization rate of Leymus chinensis (the third stage) ranged from 66.67% to 100%, Puccinellia tenuiflora (the second stage) ranged from 50% to 80%, while the Suaeda glauca (the first stage) was only 35%–60%. Glomeraceae sp1 was identified as the dominant AM fungi species which occurred frequently in the succession of saline-alkali land with the isolation frequency, relative abundance, and importance value of 100%, 18.1%, and 59.1%, respectively. The colonization rate of Glomeraceae sp1 in maize ranged from 80% to 87% and similar mycorrhizal characteristics were detected in the roots of P. tenuiflora, S. glauca, and L. chinensis, indicating that Glomeraceae sp1 colonized the samples in the field. The correlation matrix indicated that colonization rate, colonization intensity, and vesicle abundance were closely related to soil conditions most, and they were related significantly to all the soil properties except cellulase activity. Besides, redundancy analysis (RDA) showed that soil properties drove the changes of AM fungal colonization and sporulation. These results will provide theoretical support for realizing the relationship between AM fungal colonization and soil conditions, and also for the exploration of AM fungi species with great functions.
Bioenergy could play a major role in decarbonizing energy systems in the context of the Paris Agreement. Large-scale bioenergy deployment could be related to sustainability issues and requires major infrastructure investments. It, therefore, needs to be studied carefully. The Bioenergy and Land Optimization Spatially Explicit Model (BLOEM) presented here allows for assessing different bioenergy pathways while encompassing various dimensions that influence their optimal deployment. In this study, BLOEM was applied to the Brazilian context by coupling it with the Brazilian Land Use and Energy Systems (BLUES) model. This allowed investigating the most cost-effective ways of attending future bioenergy supply projections and studying the role of recovered degraded pasture lands in improving land availability in a sustainable and competitive manner. The results show optimizing for limiting deforestation and minimizing logistics costs results in different outcomes. It also indicates that recovering degraded pasture lands is attractive from both logistics and climate perspectives. The systemic approach of BLOEM provides spatial results, highlighting the trade-offs between crop allocation, land use and the logistics dynamics between production, conversion, and demand, providing valuable insights for regional and national climate policy design. This makes it a useful tool for mapping sustainable bioenergy value chain pathways. 相似文献
Projection of land use and land-cover change is highly uncertain yet drives critical estimates of carbon emissions, climate change, and food and bioenergy production. We use new, spatially explicit land availability data in conjunction with a model sensitivity analysis to estimate the effects of additional land protection on land use and land cover. The land availability data include protected land and agricultural suitability and is incorporated into the Moirai land data system for initializing the Global Change Analysis Model. Overall, decreasing land availability is relatively inefficient at preserving undeveloped land while having considerable regional land-use impacts. Current amounts of protected area have little effect on land and crop production estimates, but including the spatial distribution of unsuitable (i.e., unavailable) land dramatically shifts bioenergy production from high northern latitudes to the rest of the world, compared with uniform availability. This highlights the importance of spatial heterogeneity in understanding and managing land change. Approximately doubling the current protected area to emulate a 30% protected area target may avoid land conversion by 2050 of less than half the newly protected extent while reducing bioenergy feedstock land by 10.4% and cropland and grazed pasture by over 3%. Regional bioenergy land may be reduced (increased) by up to 46% (36%), cropland reduced by up to 61%, pasture reduced by up to 100%, and harvested forest reduced by up to 35%. Only a few regions show notable gains in some undeveloped land types of up to 36%. Half of the regions can reach the target using only unsuitable land, which would minimize impacts on agriculture but may not meet conservation goals. Rather than focusing on an area target, a more robust approach may be to carefully select newly protected land to meet well-defined conservation goals while minimizing impacts to agriculture. 相似文献
