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Despite faster-than-expected progress in clean energy technology deployment, global annual CO2 emissions have increased from 2020 to 2023. The feasibility of limiting warming to 1.5 °C is therefore questioned. Here we present a model intercomparison study that accounts for emissions trends until 2023 and compares cost-effective scenarios to alternative scenarios with institutional, geophysical and technological feasibility constraints and enablers informed by previous literature. Our results show that the most ambitious mitigation trajectories with updated climate information still manage to limit peak warming to below 1.6 °C (‘low overshoot’) with around 50% likelihood. However, feasibility constraints, especially in the institutional dimension, decrease this maximum likelihood considerably to 5–45%. Accelerated energy demand transformation can reduce costs for staying below 2 °C but have only a limited impact on further increasing the likelihood of limiting warming to 1.6 °C. Our study helps to establish a new benchmark of mitigation scenarios that goes beyond the dominant cost-effective scenario design.

How are rain forest photosynthesis and turbulent fluxes influenced by clouds? To what extent are clouds affected by local processes driven by rain forest energy, water, and carbon fluxes? These interrelated questions were the main drivers of the intensive field experiment CloudRoots-Amazon22 which took place at the Amazon Tall Tower Observatory (ATTO)/Campina supersites in the Amazon rain forest during the dry season, in August 2022. CloudRoots-Amazon22 collected observational data to derive cause–effect relationships between processes occurring at the leaf level up to canopy scales in relation to the diurnal evolution of the clear-to-cloudy transition. First, we studied the impact of cloud and canopy radiation perturbations on the subdiurnal variability of stomatal conductance. Stoma opening is larger in the morning, modulated by the cloud optical thickness. Second, we combined 1-Hz frequency measurements of the stable isotopologues of carbon dioxide and water vapor with measurements of turbulence to determine carbon dioxide and water vapor sources and sinks within the canopy. Using scintillometer observations, we inferred 1-min sensible heat flux that responded within minutes to the cloud passages. Third, collocated profiles of state variables and greenhouse gases enabled us to determine the role of clouds in vertical transport. We then inferred, using canopy and upper-atmospheric observations and a parameterization, the cloud cover and cloud mass flux to establish causality between canopy and cloud processes. This shows the need for a comprehensive observational set to improve weather and climate model representations. Our findings contribute to advance our knowledge of the coupling between cloudy boundary layers and primary carbon productivity of the Amazon rain forest.

The coastline of Sub-Saharan Africa hosts highly diverse fish communities of great conservation value, which are also key resources for local livelihoods. However, many costal ecosystems are threatened by overexploitation and their conservation state is frequently unknown due to their vast spatial extent and limited monitoring budgets. Here, we evaluated the potential of citizen science-based eDNA surveys to alleviate such chronic data deficiencies and assessed fish communities in Mozambique using two 12S metabarcoding primer sets. Samples were either collected by scientific personnel or trained community members and results from the two metabarcoding primers were combined using a new data merging approach. Irrespective of the background of sampling personnel, a high average fish species richness was recorded (38 ± 20 OTUs per sample). Individual sections of the coastline largely differed in the occurrence of threatened and commercially important species, highlighting the need for regionally differentiated management strategies. A detailed comparison of the two applied primer sets revealed an important trade-off in primer choice with MiFish primers amplifying a higher number of species but Riaz primers performing better in the detection of threatened fish species. This trade-off could be partly resolved by applying our new data-merging approach, which was especially designed to increase the robustness of multiprimer assessments in regions with poor reference libraries. Overall, our study provides encouraging results but also highlights that eDNA-based monitoring will require further improvements of, for example, reference databases and local analytical infrastructure to facilitate routine applications in Sub-Saharan Africa.

Energy models are used to study emissions mitigation pathways, such as those compatible with the Paris Agreement goals. These models vary in structure, objectives, parameterization and level of detail, yielding differences in the computed energy and climate policy scenarios. To study model differences, diagnostic indicators are common practice in many academic fields, for example, in the physical climate sciences. However, they have not yet been applied systematically in mitigation literature, beyond addressing individual model dimensions. Here we address this gap by quantifying energy model typology along five dimensions: responsiveness, mitigation strategies, energy supply, energy demand and mitigation costs and effort, each expressed through several diagnostic indicators. The framework is applied to a diagnostic experiment with eight energy models in which we explore ten scenarios focusing on Europe. Comparing indicators to the ensemble yields comprehensive ‘energy model fingerprints’, which describe systematic model behaviour and contextualize model differences for future multi-model comparison studies.

The Society for Vascular Surgery and the Enhanced Recovery After Surgery (ERAS®) Society formally collaborated and elected an international, multi-disciplinary panel of experts to review the literature and provide evidence-based suggestions for coordinated peri-operative care for patients undergoing infrainguinal bypass surgery for peripheral artery disease. Structured around the ERAS® core elements, 26 suggestions were made and organized into preadmission, preoperative, intraoperative, and postoperative sections.

The leaf photosynthesis models developed by Farquhar et al. (1980, https://doi.org/10.1007/BF00386231) (FvCB) and Goudriaan et al. (1985, https://doi.org/10.1007/978-1-4899-3665-3_10) (G85) are both used in Earth system and weather models to quantify ecosystem carbon assimilation. Despite their common role, a systematic comparison between these two photosynthesis models is currently lacking in scientific literature. In this technical report we compared the two models in a systematic way. Hereto we performed a comparative analysis of the model structures as well as the modeled responses of photosynthesis to light and CO2 at leaf level. To facilitate future model comparison, we also constructed a lookup table that presents FvCB model parameters fitted to CO2-response curves from G85 in a wide natural range in photosynthetic capacity at standardized temperature. The structure of the FvCB model differs fundamentally from the G85 model as the FvCB model considers rate-limiting processes due to Rubisco capacity, electron transport and triose phosphate utilization in parallel, whereas the G85 model considers Rubisco activity and triose phosphate utilization limitation to act in series scaled with quantum use efficiency. The models also differ fundamentally in terms of the parametrization of dark respiration. Still, both models calculate near-similar responses of photosynthesis to changes in light and CO2 across a wide range in photosynthetic capacity with only two free parameters each. Our work thereby highlights functional similarities between these model approaches despite fundamental differences in model structure. Hence, standardized parameter sets that yield similar photosynthesis responses to light and CO2 may facilitate intercomparison of Earth system and weather models.

Achieving the objectives of the Paris Climate Agreement requires a fast transition of the energy system. This leads to consequences for energy security, which a central element of the energy strategy of many countries. Important dimensions of energy security are energy diversity and energy sovereignty. The main objective of this study is to assess how different strategies and climate objectives affect these dimensions. For this, we developed a set of model-based mitigation scenarios that limit global warming to below 2 °C and 1.5 °C for 16 world regions. The scenarios differ in the energy transition strategy, focusing either more on intermittent renewables or lifestyle change. We show that energy supply diversity increases in deep mitigation scenarios in practically all regions, especially in India and China. This is due to strong growth of bioenergy and intermittent renewables, together with less fossil fuel use. There is also a substantial decrease in total energy trade in mitigation scenarios with a strong focus on intermittent renewables. Without such a strong focus on renewables, the decrease in oil and coal trade is offset by additional trade in bioenergy. However, more trade in bioenergy leads to a higher diversity in energy exporters.