Crop production is a large source of atmospheric ammonia (NH3), which poses risks to air quality, human health and ecosystems1–5. However, estimating global NH3 emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy4,5. Here we develop a machine learning model for generating crop-specific and spatially explicit NH3 emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH3 emissions from rice, wheat and maize fields in 2018 were 4.3 ± 1.0 Tg N yr−1, lower than previous estimates that did not fully consider fertilizer management practices6–9. Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH3 emissions by about 38% (1.6 ± 0.4 Tg N yr−1) without
Frontiers | Forty years of ocean acidification observations (1983–2023) in the Sargasso Sea at the Bermuda Atlantic Time-series Study site
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Accurate estimates of the land carbon sink are vital for informing climate projections and net-zero policies. Application of a strict filtering method to microwave satellite data enabled the evaluation of global vegetation biomass carbon dynamics for 2010–2019. The results highlight the role of demography in driving forest carbon gains and losses.
Insects have a pivotal role in ecosystem function, thus the decline of more than 75% in insect biomass in protected areas over recent decades in Central Europe1 and elsewhere2,3 has alarmed the public, pushed decision-makers4 and stimulated research on insect population trends. However, the drivers of this decline are still not well understood. Here, we reanalysed 27 years of insect biomass data from Hallmann et al.1, using sample-specific information on weather conditions during sampling and weather anomalies during the insect life cycle. This model explained variation in temporal decline in insect biomass, including an observed increase in biomass in recent years, solely on the basis of these weather variables. Our finding that terrestrial insect biomass is largely driven by complex weather conditions challenges previous assumptions that climate change is more critical in the tropics5,6 or that negative consequences in the temperate zone might only occur in the future7
Protected areas (PAs) are the primary strategy for slowing terrestrial biodiversity loss. Although expansion of PA coverage is prioritized under the Convention on Biological Diversity, it remains unknown whether PAs mitigate declines across the tetrapod tree of life and to what extent land cover and climate change modify PA effectiveness1,2. Here we analysed rates of change in abundance of 2,239 terrestrial vertebrate populations across the globe. On average, vertebrate populations declined five times more slowly within PAs (−0.4% per year) than at similar sites lacking protection (−1.8% per year). The mitigating effects of PAs varied both within and across vertebrate classes, with amphibians and birds experiencing the greatest benefits. The benefits of PAs were lower for amphibians in areas with converted land cover and lower for reptiles in areas with rapid climate warming. By contrast, the mitigating impacts of PAs were consistently augmented by effective national govern
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