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Land use conversion increases network complexity and stability of soil microbial communities in a temperate grassland
Soils harbor highly diverse microbial communities that are critical to soil health, but agriculture has caused extensive land use conversion resulting in negative effects on critical ecosystem processes. However, the responses and adaptations of microbial communities to land use conversion have not yet been understood. Here, we examined the effects of land conversion for long-term crop use on the network complexity and stability of soil microbial communities over 19 months. Despite reduced microbial biodiversity in comparison with native tallgrass prairie, conventionally tilled (CT) cropland significantly increased network complexity such as connectivity, connectance, average clustering coefficient, relative modularity, and the number of species acting at network hubs and connectors as well as resulted in greater temporal variation of complexity indices. Molecular ecological networks under CT cropland became significantly more robust and less vulnerable, overall increasing network stability. The relationship between network complexity and stability was also substantially strengthened due to land use conversion. Lastly, CT cropland decreased the number of relationships between network structure and environmental properties instead being strongly correlated to management disturbances. These results indicate that agricultural disturbance generally increases the complexity and stability of species “interactions”, possibly as a trade-off for biodiversity loss to support ecosystem function when faced with frequent agricultural disturbance.
Co-benefit of forestation on ozone air quality and carbon storage in South China
Substantial forestation-induced greening has occurred over South China, affecting the terrestrial carbon storage and atmospheric chemistry. However, these effects have not been systematically quantified due to complex biosphere-atmosphere interactions. Here we integrate satellite observations, forestry statistics, and an improved atmospheric chemistry model to investigate the impacts of forestation on both carbon storage and ozone air quality. We find that forestation alleviates surface ozone via enhanced dry deposition and suppressed turbulence mixing, outweighing the effect of enhanced biogenic emissions. The 2005-2019 greening mitigated the growing season mean surface ozone by 1.4 ± 2.3 ppbv, alleviated vegetation exposure by 15%-41% (depending on ozone metrics) in forests over South China, and increased Chinese forest carbon storage by 1.8 (1.6-2.1) Pg C. Future forestation may enhance carbon storage by 4.3 (3.8-4.8) Pg C and mitigate surface ozone over South China by 1.4 ± 1.2 ppbv in 2050. Air quality management should consider such co-benefits as forestation becomes necessary for carbon neutrality.
Diversity of biomass usage pathways to achieve emissions targets in the European energy system
Biomass is a versatile renewable energy source with applications across the energy system, but it is a limited resource and its usage needs prioritization. We use a sector-coupled European energy system model to explore near-optimal solutions for achieving emissions targets. We find that provision of biogenic carbon has higher value than bioenergy provision. Energy system costs increase by 20% if biomass is excluded at a net-negative (−110%) emissions target and by 14% at a net-zero target. Dispatchable bioelectricity covering ~1% of total electricity generation strengthens supply reliability. Otherwise, it is not crucial in which sector biomass is used, if combined with carbon capture to enable negative emissions and feedstock for e-fuel production. A shortage of renewable electricity or hydrogen supply primarily increases the value of using biomass for fuel production. Results are sensitive to upstream emissions of biomass, carbon sequestration capacity and costs of direct air capture.
Rising greenhouse gas emissions embodied in the global bioeconomy supply chain
The bioeconomy is key to meeting climate targets. Here, we examine greenhouse gas emissions in the global bioeconomy supply chain (1995–2022) using advanced multi-regional input-output analysis and a global land-use change model. Considering agriculture, forestry, land use, and energy, we assess the carbon footprint of biomass production and examine its end-use by provisioning systems. The footprint increased by 3.3 Gt CO2-eq, with 80% driven by international trade, mainly beef and biochemicals (biofuels, bioplastics, rubber). Biochemicals showed the largest relative increase, doubling due to tropical land-use change (feedstock cultivation) and China’s energy-intensive processing. Food from retail contributes most to the total biomass carbon footprint, while food from restaurants and canteens account for >50% of carbon-footprint growth, with three times higher carbon intensity than retail. Our findings emphasize the need for sustainable sourcing strategies and that adopting renewables and halting land-use change could reduce the bioeconomy carbon footprint by almost 60%.
Uneven diffusion: a multi-scale analysis of rural settlement evolution and its driving forces in China from 2000–2020
In recent years, the spatial and temporal patterns of rural settlement expansion in China have shifted significantly due to rapid urbanization and industrialization. This study examines rural settlement expansion in China from 2000 to 2020, using the Landscape Expansion Index (LEI) and GIS spatial analysis to assess changes in land use scale and related factors. The findings reveal that: (1) From 2000 to 2020, China saw a rapid and large-scale expansion of rural settlements, with the total area increasing by 40,322.74 km², 87.42% of which resulted from outlying expansion, indicating a clear diffusion trend. (2) The movement of rural settlements has predominantly followed a southeast–northwest axis, focusing on the middle reaches of the Yangtze River, with a clockwise rotation shift. (3) Settlement expansion has been primarily concentrated in low-elevation, waterfront, and road-adjacent areas, where GDP per capita and population density significantly influence settlement patterns. These results offer valuable insights for optimizing the spatial distribution and industrial restructuring of rural settlements, as well as for guiding rural spatial planning and industrial policy development.
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