• Energy Research
• 13. Climate action close
• 3. Good health close
• GB close
• AU close
• FI close

Abstract Tropical mountain cloud forests (TMCF) harbour a high bryophyte (mosses and liverworts) biomass and diversity. Furthermore, the high air humidity makes these forests well suited for bryophyte‐associated nitrogen (N2) fixation by cyanobacteria, providing a potentially important source of N input to the ecosystem. However, few studies have assessed bryophyte‐associated N input in these ecosystems, and these have focused on epiphytic bryophytes, whereas abundant ground‐covering bryophytes have not been included. In this study, we quantified N2 fixation rates associated with bryophytes, focusing on ground‐covering mosses in a neotropical mountain cloud forest. Furthermore, we identified the effects of climate change (higher temperature 10 vs. 20° and lower bryophyte moisture level 50% vs. 100%) on N2 fixation across bryophyte species and groups (mosses and liverworts). Nitrogen fixation rates associated with ground‐covering moss species were up to 2 kg N ha−1 year−1, which is comparable to other N inputs (e.g. N deposition) in tropical cloud forests. Furthermore, changes in temperature showed little effect on N2 fixation, but low moisture levels significantly suppressed N2 fixation activity. We found low N2 fixation activity associated with the investigated liverworts. Our results demonstrate the importance of ground‐covering, moss‐associated N2 fixation as a N source in tropical cloud forests and suggest that predicted future declines in precipitation in these systems will reduce N inputs from bryophyte‐associated cyanobacteria. Read the free Plain Language Summary for this article on the Journal blog.

AbstractForecasting the variability of dwellings and residential land is important for estimating the future potential of environmental technologies. This paper presents an innovative method of converting average residential density into a set of one-hectare 3D tiles to represent the dwelling stock. These generic tiles include residential land as well as the dwelling characteristics. The method was based on a detailed analysis of the English House Condition Survey data and density was calculated as the inverse of the plot area per dwelling. This found that when disaggregated by age band, urban morphology and area type, the frequency distribution of plot density per dwelling type can be represented by the gamma distribution. The shape parameter revealed interesting characteristics about the dwelling stock and how this has changed over time. It showed a consistent trend that older dwellings have greater variability in plot density than newer dwellings, and also that apartments and detached dwellings have greater variability in plot density than terraced and semi-detached dwellings. Once calibrated, the shape parameter of the gamma distribution was used to convert the average density per housing type into a frequency distribution of plot density. These were then approximated by systematically selecting a set of generic tiles. These tiles are particularly useful as a medium for multidisciplinary research on decentralized environmental technologies or climate adaptation, which requires this understanding of the variability of dwellings, occupancies and urban space. It thereby links the socioeconomic modeling of city regions with the physical modeling of dwellings and associated infrastructure across the spatial scales. The tiles method has been validated by comparing results against English regional housing survey data and dwelling footprint area data. The next step would be to explore the possibility of generating generic residential area types and adapt the method to other countries that have similar housing survey data.

River deltas and estuaries are disproportionally-significant coastal landforms that are inhabited by nearly 600 M people globally. In recent history, rapid socio-economic development has dramatically changed many of the World's mega deltas, which have typically undergone agricultural intensification and expansion, land-use change, urbanization, water resources engineering and exploitation of natural resources. As a result, mega deltas have evolved into complex and potentially vulnerable socio-ecological systems with unique threats and coping capabilities. The goal of this research was to establish a holistic understanding of threats, resilience, and adaptation for four mega deltas of variable geography and levels of socio-economic development, namely the Mekong, Yellow River, Yangtze, and Rhine deltas. Compiling this kind of information is critical for managing and developing these complex coastal areas sustainably but is typically hindered by a lack of consistent quantitative data across the ecological, social and economic sectors. To overcome this limitation, we adopted a qualitative approach, where delta characteristics across all sectors were assessed through systematic expert surveys. This approach enabled us to generate a comparative assessment of threats, resilience, and resilience-strengthening adaptation across the four deltas. Our assessment provides novel insights into the various components that dominate the overall risk situation in each delta and, for the first time, illustrates how each of these components differ across the four mega deltas. As such, our findings can guide a more detailed, sector specific, risk assessment or assist in better targeting the implementation of risk mitigation and adaptation strategies.

AbstractWhile several recent studies have focused on global insect population trends, all are limited in either space or taxonomic scope. As global monitoring programs for insects are currently not implemented, inherent biases exist within most data. Expert opinion, which is often widely available, proves to be a valuable tool where hard data are limited. Our aim is to use global expert opinion to provide insights on the root causes of potential insect declines worldwide, as well as on effective conservation strategies that could mitigate insect biodiversity loss. We obtained 753 responses from 413 respondents with a wide variety of spatial and taxonomic expertise. The most relevant threats identified through the survey were agriculture and climate change, followed by pollution, while land management and land protection were recognized as the most significant conservation measures. Nevertheless, there were differences across regions and insect groups, reflecting the variability within the most diverse class of eukaryotic organisms on our planet. Lack of answers for certain biogeographic regions or taxa also reflects the need for research in less investigated settings. Our results provide a novel step toward understanding global threats and conservation measures for insects.

AbstractAimAgriculture is one of the greatest pressures on biodiversity. Regional studies have shown that the presence of natural habitat and landscape heterogeneity are beneficial for biodiversity in agriculture, but it remains unclear whether their importance varies geographically. Here, we use local biodiversity data to determine which local and landscape variables are most associated with biodiversity patterns and whether their association varies between tropical and non‐tropical regions.LocationGlobal terrestrial area in forest biomes.Major taxa studiedMore than 21,000 species of vertebrates, invertebrates, plants and other taxa.MethodsWe used generalized linear mixed‐effects models to analyse the relationships between either community total abundance or species richness (derived from the PREDICTS database) and a number of site‐level (predominant land use and land‐use intensity) and landscape‐level variables (distance to forest, the percentage of natural habitat in the surrounding landscape, landscape homogeneity, the number of land‐cover types in the landscape, and total fertilizer application). We compared the associations of these variables with biodiversity in tropical and non‐tropical regions.ResultsIn most cases, changes in biodiversity associated with landscape‐level variables were greater than those associated with local land use and land‐use intensity. Increased natural habitat availability was associated with the most consistent increases in biodiversity. Landscape homogeneity was also important but showed different directions of biodiversity change between regions. Associations with fertilizer application or the number of land‐cover types were generally weaker, although still of greater magnitude than for the local land‐use measures.Main conclusionsOur results highlight similarities and differences in the association of local‐ and landscape‐scale variables with local biodiversity in tropical and non‐tropical regions. Landscape natural habitat availability had a consistent positive association with biodiversity, highlighting the key role of landscape management in the maintenance of biodiversity in croplands. Landscape‐scale variables were almost always associated with greater changes in biodiversity than the local‐scale measures.

Green ammonia is gaining momentum as a globally significant technology for deep decarbonisation. In this thesis, several models are developed across chemical, techno-economic, and energy system modelling disciplines to explore the future role of green ammonia. First, standalone models of production (i.e., power-to-ammonia) and re-electrification (i.e., ammonia-to-power) are developed and compared to competing technologies. Second, these models are integrated into a planning and dispatch energy system model (ESM) of India to 2050. The ESM has several novel additions including the sector coupling of hydrogen and ammonia, multiple years of granular weather data, and learning-curve-based technology cost forecasts. India is chosen as an ideal case study given its globally unmatched demand growth in all three relevant sectors: electricity, green hydrogen, and green ammonia. The projected electricity demands for green hydrogen and ammonia production account for 25% of the total Indian electricity demand in 2050, underscoring the transformational potential that green hydrogen and ammonia sector coupling can have on the Indian energy system. The results of the state-of-the-art ESM highlight synergistic effects of hydrogen and ammonia sector coupling with the power system. The least-cost system employs seasonal green ammonia production paired with up to 40 million tonnes (i.e., 200 TWh) of ammonia storage, as well as some re-electrification via gas turbines. Sector coupling reduces system curtailment, addresses challenges of long-duration storage, and improves system resilience to interannual weather variations. While India is a crucial case study from a global decarbonisation perspective, the methodology and findings are generally applicable, and it is the aim of this work to motivate and accelerate the wider research community into considering the potential impacts of green ammonia sector coupling on electricity grid design. Finally, this work highlights strategic technology development direction for ammonia producers and gas turbine manufacturers, as well as implications for policymakers.

Glaciers are retreating globally, and the resulting ice-free areas provide an experimental system for understanding species colonization patterns, community formation, and dynamics. The last several years have seen crucial advances in our understanding of biotic colonization after glacier retreats, resulting from the integration of methodological innovations and ecological theories. Recent empirical studies have demonstrated how multiple factors can speed up or slow down the velocity of colonization and have helped scientists develop theoretical models that describe spatiotemporalchanges in community structure. There is a growing awareness of how different processes (e.g., time since glacier retreat, onset or interruption of surface processes, abiotic factors, dispersal, biotic interactions) interact to shape community formation and, ultimately, their functional structure through succession. Here, we examine how these studies address key theoretical questions about community dynamics and show how classical approaches are increasingly being combined with environmental DNA metabarcoding and functional trait analysis to document the formation of multitrophic communities, revolutionizing our understanding of the biotic processes that occur following glacier retreat.