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Novel fire regimes are emerging worldwide and pose substantial challenges to biodiversity conservation. Addressing these challenges and mitigating their impacts on biodiversity will require developing a wide range of fire management practices. In this paper, we leverage research across taxa, ecosystems and continents to highlight strategies for applying fire knowledge in biodiversity conservation. First, we define novel fire regimes and outline different fire management practices in contemporary landscapes from different parts of the world. Next, we synthesize recent research on fire use and biodiversity, and provide a decision-making framework for biodiversity conservation under novel fire regimes. We recommend that fire management strategies for preserving biodiversity should consider both social and ecological factors, iterative learning informed by effective monitoring, and developing and testing new management actions. An integrated approach to learning about fire and biodiversity will help to navigate the complexities of novel fire regimes and preserve biodiversity in a rapidly changing world. This article is part of the theme issue ‘Novel fire regimes under climate changes and human influences: impacts, ecosystem responses and feedbacks’.

ABSTRACTBoreal forest regions, including East Siberia, have experienced elevated fire activity in recent years, leading to record‐breaking greenhouse gas emissions and severe air pollution. However, our understanding of the factors that eventually halt fire spread and thus limit fire growth remains incomplete, hindering our ability to model their dynamics and predict their impacts. We investigated the locations and timing of 2.2 million fire stops—defined as 300 m unburned pixels along fire perimeters—across the vast East Siberian taiga. Fire stops were retrieved from remote sensing data covering over 27,000 individual fires that collectively burned 80 Mha between 2012 and 2022. Several geospatial datasets, including hourly fire weather data and landscape variables, were used to identify the factors contributing to individual fire stops. Our analysis attributed 87% of all fire stops to a statistically significant (p < 0.01) change in one or more of these drivers, with fire‐weather drivers limiting fire growth over time and landscape drivers constraining it across space. We found clear regional and temporal variations in the importance of these drivers. For instance, landscape drivers—such as less flammable land cover and the presence of roads—were key constraints on fire growth in southeastern Siberia, where the landscape is more populated and fragmented. In contrast, fire weather was the primary constraint on fire growth in the remote northern taiga. Additionally, in central Yakutia, a major fire hotspot in recent years, fuel limitations from previous fires increasingly restricted fire spread. The methodology we present is adaptable to other biomes and can be applied globally, providing a framework for future attribution studies on global fire growth limitations. In northeast Siberia, we found that with increasing droughts and heatwaves, remote northern fires could potentially grow even larger in the future, with major implications for the global carbon cycle and climate.

The ongoing transformation of district heating systems (DHSs) aims to reduce emissions and increase renewable energy sources. The objective of this work is to integrate solar thermal (ST) and seasonal aquifer thermal energy storage (ATES) in various scenarios applied to a large DHS. Mixed-integer linear programming (MILP) is used to develop a comprehensive model that minimizes operating costs, including heat pumps (HPs), combined heat and power (CHP) units, electric heat boilers (EHBs), heat-only boilers (HOBs), short-term thermal energy storage (TES), and ATES. Different ATES scenarios are compared to a reference without seasonal TES (potential of 15.3 GWh of ST). An ATES system with an injection well temperature of about 55 °C has an overall efficiency of 49.8% (58.6% with additional HPs) and increases the integrable amount of ST by 178% (42.5 GWh). For the scenario with an injection well temperature of 20 °C and HPs, the efficiency is 86.6% and ST is increased by 276% (57.5 GWh). The HOB heat supply is reduced by 8.9% up to 36.6%. However, the integration of an ATES is not always economically or environmentally beneficial. There is a high dependency on the configurations, prices, or emissions allocated to electricity procurement. Further research is of interest to investigate the sensitivity of the correlations and to apply a multi-objective MILP optimization.

This paper presents a novel physical model to analyse the energy efficiency of a thermal management system based on a phase change material (PCM) for Li-ion batteries including diffusion and irreversible phenomena such as entropy. Real-world battery performance was assessed using the New European Driving Cycle (NEDC), which includes four urban routes and one ultra-urban route. The model's accuracy was validated against experimental data, and an in-depth analysis of various parameters was conducted. The results show that the choice of PCM melting temperature range is pivotal in the battery thermal management system (BTMS) performance, with RT-28HC and RT-31 exhibiting superior thermal regulation during the three charge and discharge cycles. Although the thermal gradient within the pack is often negligible under different ambient conditions, higher ambient temperatures (40 °C) or high convective coefficients (60 W/m2K) increased thermal gradients. Simulations reveal that combining PCM and active cooling systems is required to reduce thermal gradients and maintain temperature uniformity, especially in extreme conditions and long operating times. This new model provides a cost-effective, agile alternative to computationally intensive methods for analysing dynamic thermal behaviour during long charge and discharge cycles.

Abstract This paper introduces and applies iGain4Gains, an Excel-based model, to reveal how changes to water conservation and allocation, and irrigation technology, can produce four nexus gains. These gains are; reduced aggregate water consumption, sustained crop production, lower carbon emissions, and enhanced water availability for nature. We developed the model with limited data and hypothetical future scenarios from the Amman–Zarqa basin in Jordan. Given its significant irrigation and urban water demands and difficult decisions regarding future water allocation and nexus choices, this basin is a highly appropriate case study. The paper’s primary aim is to demonstrate the iGains4Gains nexus model rather than to build an accurate hydrological model of the basin’s water resources. The model addresses two critical questions regarding increased irrigation efficiency. First, can irrigation efficiency and other factors, such as irrigated area, be applied to achieve real water savings while maintaining crop production, ensuring greenhouse gas emission reductions, and ‘freeing’ water for nature? Second, with the insight that water conservation is a distributive/allocative act, we ask who between four paracommoners (the proprietor irrigation system, neighbouring irrigation systems, society, and nature) benefits hydrologically from changes in irrigation efficiency? Recognising nexus gains are not always linear, positive and predictable, the model reveals that achieving all four gains simultaneously is difficult, likely leading to trade-offs such as water consumption rebounds or increased carbon emissions. Demonstrated by its use at a workshop in Jordan in February 2024, iGains4Gains can be used by students, scientists and decision-makers, to explore and understand nexus trade-offs connected to changes in irrigation management. The paper concludes with recommendations for governing water and irrigated agriculture in basins where large volumes of water are withdrawn and depleted by irrigation.

Abstract The Automated Meteorology—Ice—Geophysics Observation System 3 (AMIGOS-3) is a multi-sensor on-ice ocean mooring and weather, camera and precision GPS measurement station, controlled by a Python script. The station is designed to be deployed on floating ice in the polar regions and operate unattended for up to several years. Ocean mooring sensors (SeaBird MicroCAT and Nortek Aquadopp) record conductivity, temperature and depth (reported at 10 min intervals), and current velocity (hourly intervals). A Silixa XT fiber-optic distributed temperature sensing system provides a temperature profile time-series through the ice and ocean column with a cadence of 6 d−1 to 1 week−1 depending on available station power. A subset of the station data is telemetered by Iridium modem. Two-way communication, using both single-burst data and file transfer protocols, facilitates station data collection changes and power management. Power is supplied by solar panels and a sealed lead-acid battery system. Two AMIGOS-3 systems were installed on the Thwaites Eastern Ice Shelf in January 2020, providing data well into 2022. We discuss the components of the system and present several of the data sets, summarizing observed climate, ice and ocean conditions.

Despite the intrinsic relationships between the natural environment, poverty and human wellbeing, measures of poverty do not adequately account for environmental dimensions of wellbeing. This paper furthers theoretical debates about environment-poverty relationships by developing environmental dimensions and indicators for integration into multidimensional poverty indices. We demonstrate that this integration is practically possible using public datasets that are part of regular data collection efforts. Using Brazil as a case study, we develop an environmentally-adjusted multidimensional poverty measure that combines data on proximity to natural land, floods, droughts and landslide risks with information on health, education and living standards. Our results show that the integration of environmental dimensions into a poverty measure can provide different estimates of the incidence and distribution of poverty in a country, shifting attention to new target areas for poverty reduction strategies. Our measure provides a complementary and broader understanding of poverty than traditional poverty indices and could be used to track changes over time. Our measure therefore provides a potentially useful avenue to assess progress towards achieving multiple Sustainable Development Goals, while also accounting for environmental change.

Data and analysis scripts for Hertwig D, Grimmond S, Hendry MA, et al. (2020). Urban signals in high-resolution weather and climate simulations: role of urban land-surface characterisation. Theoretical and Applied Climatology 142, 701–728. https://doi.org/10.1007/s00704-020-03294-1 Data archive overview in Hertwig_TAAC_2020_JULESruns_overview.xlsx Decompress zipped archives with: $ tar -zxvf .tar.gzor 7-zip Format of JULES model output: netCDF (.nc)