search
The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
4 Projects, page 1 of 1

  • Canada
  • UK Research and Innovation
  • UKRI|NERC
  • 2022
  • 2026

  • Funder: UKRI Project Code: NE/X005267/1
    Funder Contribution: 1,376,230 GBP
    Partners: University of Saskatchewan, CAS, Indian Inst of Technology Kharagpur, IITR, Swiss Re, National Institute of Hydrology, NERC British Antarctic Survey, Universität Innsbruck

    The world's mountains store and release frozen water when it is most valuable, as summer meltwater in the growing season. This service is an extraordinary generator of wealth and well-being, sustaining a sixth of the global population and a quarter of global GDP, but is highly vulnerable to climate change. Over the next 30 years, the Alps, Western North America, Himalayas and Andes will lose 10-40% of their snow, hundreds of cubic kilometres of summer water supply, and by end of century, mountain glaciers will lose 20-60% of their ice. To map our mountain water resources and predict their future, we must rely on models of snowfall, seasonal snowpacks, glacier gains and losses, and river runoff. The skill of these models is, however, fundamentally limited by the quality and availability of observations needed to test and develop them, and the mountain cryosphere is so large, varied and inhospitable that we lack many of these key observations. In most mountain ranges, snowfall is underestimated by 50-100%, and weather records are too short to have captured a history of their climate extremes. The thickness of only 6 of 41,000 glaciers has been surveyed in the Himalayan headwaters of the Brahmaputra, Indus and Ganges basins, so the lifespan of a water resource used by 800 million people remains unpredictable. This project aims to fill four of the key observation gaps: 1) snowfall, 2) glacier thickness, 3) runoff, and 4) weather extremes, by taking a targeted approach to provide not blanket coverage of the mountain cryosphere but carefully-selected datasets designed to test and improve model skill. Importantly, through the calibration and refinement of relevant model processes at these target sites we can eliminate gross biases and reduce uncertainties in model outputs that can then apply not just locally but across all model scales, in the past, present and future. We will make new snowfall observations with a pioneering method that, for the first time, makes unbiased measurements over areas thousands to billions of times larger than rain gauges, and use these to test and improve snowfall models that are run worldwide. To capture and understand the extremes of mountain precipitation, we will extend the decades-long instrumental record back by centuries to millennia by identifying the signals of wet and dry years preserved in high, undisturbed Himalayan-lake sediments that we will core and analyse at very high resolution. In parallel, we will use a recently acquired and uniquely extensive glacier survey from Nepal to improve glacier-thickness models on the mountain-range scale. We will use our new snowfall maps and projections to drive detailed models of snowpack and glacier evolution over the 21st century for two targeted catchments in the Alps and Himalayas. We will apply our models to our glacier thickness maps to determine how long these glaciers will survive under a changing climate, how much meltwater will flow into their catchments and how this will change. We will test the performance of our models against cutting-edge new flux and hydrochemistry observations of the contribution of different water sources to downstream river flow. Finally, we will determine which climate factors affect the frequency and severity of extreme wet and dry years for the two catchments, and how these events are likely to change through the 21st century. Together, our targeted, data-driven modelling advances will demonstrably improve our ability to quantify how much seasonal snow accumulates in the mountain cryosphere and predict how it will change in the future, what the timescales and potential trajectories for change are for glacier-ice resources, how frequently dry and wet years occur, what climate factors cause this, and how these extremes will change. By making the mountain cryosphere more predictable, we will support societies in managing change in this critical but vulnerable water resource.

  • Funder: UKRI Project Code: NE/W006448/1
    Funder Contribution: 603,466 GBP
    Partners: UBC, TOWSON UNIVERSITY, AMHERST COLLEGE, UZH, University of Montreal, NAU, NASA, Aurora Research Institute, University of Lapland, AU...

    The TundraTime project will address climate change impacts in tundra ecosystems including how warming is shifting tundra plant phenology - the timing of life events such as bud burst or flowering - and productivity - the increase in plant growth and biomass over time. We will answer the fundamental research question of whether climate warming is leading to longer tundra growing seasons and thus increasing plant productivity in the Arctic, with important implications for carbon cycling and wildlife. Critical knowledge gaps in the field of global change ecology are what role the high latitudes will play in the global carbon cycle and how Arctic food webs will be restructured in the future with accelerated warming. A critical unknown is whether shifting plant phenology is altering tundra carbon cycling and wildlife habitats. Projections of climate feedbacks from high-latitude ecosystems remain uncertain as we do not yet know if carbon losses from warming soils will be offset by increases in tundra productivity. Tundra plant responses to warming could be key for understanding the fate of wildlife populations in a rapidly changing Arctic. Forty years of satellite and field observations have revealed widespread changes in the tundra's surface that protects large stocks of frozen carbon below. Field studies indicate that plants are coming into leaf earlier in spring, bare ground is becoming vegetated, and plants are now growing taller. While there is scientific consensus that climate change is reshaping Arctic ecosystems, great uncertainty persists about what the greening observed from space means in terms of change on-the-ground. The TundraTime project will answer the fundamental research questions of whether climate warming is leading to longer periods of plant growth and increases in plant productivity in the Arctic. We will test specific hypotheses of whether tundra ecosystems are experiencing: A) increases in productivity, B) shifts in phenology and C) asynchrony of above- and below-ground plant growth. To explore these questions, we will integrate high-resolution drone and time-lapse camera imagery with satellite and in-situ data from 12 focal Arctic research sites. Our findings will inform biome-wide projections of tundra vegetation change and global-scale predictions of climate feedbacks to unprecedented rates of warming. If tundra plant productivity is responding directly to the warmer and longer Arctic growing seasons then tundra productivity will trap more carbon in tundra ecosystems and restructure wildlife habitats. However, if instead tundra plant growing seasons are shifting earlier, then projections of increases in tundra vegetation with warming may be overestimates and earlier timing of key forage could alter migratory behaviour and ultimately wildlife populations. And, if the above- and below-ground responses of tundra plants are asynchronous, plant growth in the now extended snow-free autumns could instead be occurring below ground, which would overturn how satellite data and Earth-system models estimate plant productivity and carbon storage in warming tundra ecosystems. The TundraTime project will test the drivers of Arctic greening by resolving the uncertainty around what role shifting plant phenology plays in the increased tundra productivity with warming. This research will bridge critical scale gaps to resolve the uncertainty between satellite and in-situ observations of changes in the timing of plant growth with accelerating climate warming.

  • Funder: UKRI Project Code: NE/W003104/1
    Funder Contribution: 450,327 GBP
    Partners: UAF, Beihang University, UNIS, DLR, University of Leicester, GFZ German Research, ASTRON, FMI, Swedish Institute of Space Physics, University of Saskatchewan...

    The UK along with the rest of the world is becoming increasingly dependent on technological systems, including satellite communications, global positioning systems, and power grids, that are at risk from space weather. Many space weather hazards originate in the ionosphere, the ionised upper part of the atmosphere at altitudes of 90 km and above, where solar wind energy channelled by the Earth's magnetic field can cause a variety of unpredictable and deleterious effects. It causes electrical currents to flow, which heat the atmosphere in a process known as Joule heating, which in turn can cause the atmosphere to expand upwards, producing drag on satellites, hence making their orbits harder to predict and reducing their lifetimes. It produces horizontal motions of the ionosphere which modify the neutral winds in the thermosphere through friction. It produces the auroras, associated with particle precipitation from the magnetosphere above, which modify the ionospheric structure. Moreover, it gives rise to plasma instabilities which cause the ionosphere to become corrugated, scattering radio waves from satellites consequently disturbing communications and GPS. Although the large-scale distribution of such space weather hazards is relatively well reproduced in global circulation models, the physics occurring on spatial scales smaller than the model grid is poorly understood, which holds back improvements in forecasting. The FINESSE project will exploit a new and unique NERC-funded incoherent scatter radar system, EISCAT_3D, located in northern Scandinavia, to study these sub-grid space weather scales. EISCAT_3D will be able to determine the ionospheric structure in a box roughly 200 km to a side horizontally and 800 km vertically, at an unprecedented spatial and temporal resolution, to image the processes leading to space weather effects. FINESSE will also exploit a next-generation coherent scatter radar to measure ionospheric motions, three neutral wind imagers to measure the interaction between the thermosphere and the ionosphere, three all-sky auroral cameras to view regions of precipitation from the magnetosphere above, a fine-scale auroral imager to observe auroral structures on spatial and temporal scales even finer than EISCAT_3D can probe, and a radio telescope and network of GPS receivers to look at the scintillation of radio signals from both cosmic sources and satellites. The main aims of FINESSE are as follows. 1) To determine the small-scale sources of Joule heating, to place these within the context of the larger picture of polar auroral disturbances, to determine the link between Joule heating and satellite drag, and to incorporate these results to improve forecast models. 2) To determine the cause of small-scale ionospheric structuring, and to understand how this leads to scintillation of radio signals. 3) To probe auroral dynamics at the very smallest temporal and spatial scales to understand the physics of coupling between the magnetosphere and ionosphere, the role auroral processes play in heating and structuring the ionosphere and atmosphere, and the instability that leads to substorms (explosive releases of energy into the nightside auroral ionosphere). FINESSE will liaise with space weather forecasters and other stakeholders to disseminate this greater understanding of small-scale processes in producing space weather hazards and to translate it into significant economic benefit to the UK.

  • Funder: UKRI Project Code: NE/W006650/1
    Funder Contribution: 652,019 GBP
    Partners: Natural England, JNCC, SNH, Swansea University, McGill University, University of Gothenburg

    Human activities have already raised global species extinction rates a thousand-fold and have pushed an additional million species towards extinction. Biodiversity is also rapidly changing on more local scales as climate change drives the redistribution of species, and pressures such as overharvesting and habitat fragmentation intensify in many areas. Understanding how biodiversity influences ecosystem functions, such as carbon capture and fisheries productivity, is a crucial challenge directly relevant to meeting the UN sustainable development goals, and UK policy imperatives of harnessing biodiversity to achieve sustainable economic growth and using nature-based solutions to help meet 'net-zero' emissions by 2050. Since the mid- 1990s, several hundred experiments have tested how changes in biodiversity influence ecosystem functions and services, with many studies indicating that biodiversity loss does not reduce functioning as long as the single best-performing species is retained. However, these studies have focused on local-scale interactions between species in small habitat units such as grassland plots, field enclosures, or aquarium tanks; we therefore lack studies that consider BEF relationships on the larger landscape-, regional- or even national- scales most relevant to the public, ecosystem managers, and policy makers. Ecological theory suggests that biodiversity is more important for ecosystem services as scale increases due to greater environmental variation, but it cannot currently be evaluated in real ecosystems because we lack BEF studies across scales and environmental gradients. In this project we aim to bridge the gap between experiments and relevant larger scales by using Great Britain's intertidal forests as a model system. These highly productive and valuable ecosystems occur extensively around the GB's varied and complex coastlines and are formed by a manageable suite of seaweed species which can be easily manipulated across multiple distinct environmental gradients. To meet our overall aim, we will incorporate multiple environmental factors into experiments, observations and models delivered across three inter-linked work packages which together provide a generalised approach and scaling relationships for BEF. Our first work package uses a 100km stretch of the south Wales coastline - which incorporates gradients in wave exposure and turbidity - as an accessible template to experimentally test the causal effect of intertidal forest biodiversity on ecosystem functioning from small patches to the whole coastline. Our second package combines a network of standardised observations in intertidal forests around GB, with satellite remote sensing and statistical modelling, to test how BEF relationships scale-up -- from 1 m to 1000km scales -- in naturally assembled communities. The third and final work package uses the new experimental and observational data to inform dynamic models, allowing us to test how species traits such as dispersal and environmental tolerances interacts with environmental variability to determine BEF relationships across scales. A key innovation here is the explicit - and empirically informed - integration of spatial environmental variability in multiple environmental factors. These will be generalised to represent how the environment varies in a range of different ecosystems from forests, to agricultural landscapes, and to coral reefs. The advancement of our project aim will deliver a revised appreciation of the role of diversity in ecosystems and demonstrate a generalizable approach for upscaling biodiversity - ecosystem functioning relationships. We anticipate that this will feed into predictions for how biodiversity changes will influence ecosystem functioning and services on large, relevant- scales, in intertidal forests and beyond, with a range of applications from natural capital models, to the design of large-scale ecosystem restoration projects.

search
The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
4 Projects, page 1 of 1
  • Funder: UKRI Project Code: NE/X005267/1
    Funder Contribution: 1,376,230 GBP
    Partners: University of Saskatchewan, CAS, Indian Inst of Technology Kharagpur, IITR, Swiss Re, National Institute of Hydrology, NERC British Antarctic Survey, Universität Innsbruck

    The world's mountains store and release frozen water when it is most valuable, as summer meltwater in the growing season. This service is an extraordinary generator of wealth and well-being, sustaining a sixth of the global population and a quarter of global GDP, but is highly vulnerable to climate change. Over the next 30 years, the Alps, Western North America, Himalayas and Andes will lose 10-40% of their snow, hundreds of cubic kilometres of summer water supply, and by end of century, mountain glaciers will lose 20-60% of their ice. To map our mountain water resources and predict their future, we must rely on models of snowfall, seasonal snowpacks, glacier gains and losses, and river runoff. The skill of these models is, however, fundamentally limited by the quality and availability of observations needed to test and develop them, and the mountain cryosphere is so large, varied and inhospitable that we lack many of these key observations. In most mountain ranges, snowfall is underestimated by 50-100%, and weather records are too short to have captured a history of their climate extremes. The thickness of only 6 of 41,000 glaciers has been surveyed in the Himalayan headwaters of the Brahmaputra, Indus and Ganges basins, so the lifespan of a water resource used by 800 million people remains unpredictable. This project aims to fill four of the key observation gaps: 1) snowfall, 2) glacier thickness, 3) runoff, and 4) weather extremes, by taking a targeted approach to provide not blanket coverage of the mountain cryosphere but carefully-selected datasets designed to test and improve model skill. Importantly, through the calibration and refinement of relevant model processes at these target sites we can eliminate gross biases and reduce uncertainties in model outputs that can then apply not just locally but across all model scales, in the past, present and future. We will make new snowfall observations with a pioneering method that, for the first time, makes unbiased measurements over areas thousands to billions of times larger than rain gauges, and use these to test and improve snowfall models that are run worldwide. To capture and understand the extremes of mountain precipitation, we will extend the decades-long instrumental record back by centuries to millennia by identifying the signals of wet and dry years preserved in high, undisturbed Himalayan-lake sediments that we will core and analyse at very high resolution. In parallel, we will use a recently acquired and uniquely extensive glacier survey from Nepal to improve glacier-thickness models on the mountain-range scale. We will use our new snowfall maps and projections to drive detailed models of snowpack and glacier evolution over the 21st century for two targeted catchments in the Alps and Himalayas. We will apply our models to our glacier thickness maps to determine how long these glaciers will survive under a changing climate, how much meltwater will flow into their catchments and how this will change. We will test the performance of our models against cutting-edge new flux and hydrochemistry observations of the contribution of different water sources to downstream river flow. Finally, we will determine which climate factors affect the frequency and severity of extreme wet and dry years for the two catchments, and how these events are likely to change through the 21st century. Together, our targeted, data-driven modelling advances will demonstrably improve our ability to quantify how much seasonal snow accumulates in the mountain cryosphere and predict how it will change in the future, what the timescales and potential trajectories for change are for glacier-ice resources, how frequently dry and wet years occur, what climate factors cause this, and how these extremes will change. By making the mountain cryosphere more predictable, we will support societies in managing change in this critical but vulnerable water resource.

  • Funder: UKRI Project Code: NE/W006448/1
    Funder Contribution: 603,466 GBP
    Partners: UBC, TOWSON UNIVERSITY, AMHERST COLLEGE, UZH, University of Montreal, NAU, NASA, Aurora Research Institute, University of Lapland, AU...

    The TundraTime project will address climate change impacts in tundra ecosystems including how warming is shifting tundra plant phenology - the timing of life events such as bud burst or flowering - and productivity - the increase in plant growth and biomass over time. We will answer the fundamental research question of whether climate warming is leading to longer tundra growing seasons and thus increasing plant productivity in the Arctic, with important implications for carbon cycling and wildlife. Critical knowledge gaps in the field of global change ecology are what role the high latitudes will play in the global carbon cycle and how Arctic food webs will be restructured in the future with accelerated warming. A critical unknown is whether shifting plant phenology is altering tundra carbon cycling and wildlife habitats. Projections of climate feedbacks from high-latitude ecosystems remain uncertain as we do not yet know if carbon losses from warming soils will be offset by increases in tundra productivity. Tundra plant responses to warming could be key for understanding the fate of wildlife populations in a rapidly changing Arctic. Forty years of satellite and field observations have revealed widespread changes in the tundra's surface that protects large stocks of frozen carbon below. Field studies indicate that plants are coming into leaf earlier in spring, bare ground is becoming vegetated, and plants are now growing taller. While there is scientific consensus that climate change is reshaping Arctic ecosystems, great uncertainty persists about what the greening observed from space means in terms of change on-the-ground. The TundraTime project will answer the fundamental research questions of whether climate warming is leading to longer periods of plant growth and increases in plant productivity in the Arctic. We will test specific hypotheses of whether tundra ecosystems are experiencing: A) increases in productivity, B) shifts in phenology and C) asynchrony of above- and below-ground plant growth. To explore these questions, we will integrate high-resolution drone and time-lapse camera imagery with satellite and in-situ data from 12 focal Arctic research sites. Our findings will inform biome-wide projections of tundra vegetation change and global-scale predictions of climate feedbacks to unprecedented rates of warming. If tundra plant productivity is responding directly to the warmer and longer Arctic growing seasons then tundra productivity will trap more carbon in tundra ecosystems and restructure wildlife habitats. However, if instead tundra plant growing seasons are shifting earlier, then projections of increases in tundra vegetation with warming may be overestimates and earlier timing of key forage could alter migratory behaviour and ultimately wildlife populations. And, if the above- and below-ground responses of tundra plants are asynchronous, plant growth in the now extended snow-free autumns could instead be occurring below ground, which would overturn how satellite data and Earth-system models estimate plant productivity and carbon storage in warming tundra ecosystems. The TundraTime project will test the drivers of Arctic greening by resolving the uncertainty around what role shifting plant phenology plays in the increased tundra productivity with warming. This research will bridge critical scale gaps to resolve the uncertainty between satellite and in-situ observations of changes in the timing of plant growth with accelerating climate warming.

  • Funder: UKRI Project Code: NE/W003104/1
    Funder Contribution: 450,327 GBP
    Partners: UAF, Beihang University, UNIS, DLR, University of Leicester, GFZ German Research, ASTRON, FMI, Swedish Institute of Space Physics, University of Saskatchewan...

    The UK along with the rest of the world is becoming increasingly dependent on technological systems, including satellite communications, global positioning systems, and power grids, that are at risk from space weather. Many space weather hazards originate in the ionosphere, the ionised upper part of the atmosphere at altitudes of 90 km and above, where solar wind energy channelled by the Earth's magnetic field can cause a variety of unpredictable and deleterious effects. It causes electrical currents to flow, which heat the atmosphere in a process known as Joule heating, which in turn can cause the atmosphere to expand upwards, producing drag on satellites, hence making their orbits harder to predict and reducing their lifetimes. It produces horizontal motions of the ionosphere which modify the neutral winds in the thermosphere through friction. It produces the auroras, associated with particle precipitation from the magnetosphere above, which modify the ionospheric structure. Moreover, it gives rise to plasma instabilities which cause the ionosphere to become corrugated, scattering radio waves from satellites consequently disturbing communications and GPS. Although the large-scale distribution of such space weather hazards is relatively well reproduced in global circulation models, the physics occurring on spatial scales smaller than the model grid is poorly understood, which holds back improvements in forecasting. The FINESSE project will exploit a new and unique NERC-funded incoherent scatter radar system, EISCAT_3D, located in northern Scandinavia, to study these sub-grid space weather scales. EISCAT_3D will be able to determine the ionospheric structure in a box roughly 200 km to a side horizontally and 800 km vertically, at an unprecedented spatial and temporal resolution, to image the processes leading to space weather effects. FINESSE will also exploit a next-generation coherent scatter radar to measure ionospheric motions, three neutral wind imagers to measure the interaction between the thermosphere and the ionosphere, three all-sky auroral cameras to view regions of precipitation from the magnetosphere above, a fine-scale auroral imager to observe auroral structures on spatial and temporal scales even finer than EISCAT_3D can probe, and a radio telescope and network of GPS receivers to look at the scintillation of radio signals from both cosmic sources and satellites. The main aims of FINESSE are as follows. 1) To determine the small-scale sources of Joule heating, to place these within the context of the larger picture of polar auroral disturbances, to determine the link between Joule heating and satellite drag, and to incorporate these results to improve forecast models. 2) To determine the cause of small-scale ionospheric structuring, and to understand how this leads to scintillation of radio signals. 3) To probe auroral dynamics at the very smallest temporal and spatial scales to understand the physics of coupling between the magnetosphere and ionosphere, the role auroral processes play in heating and structuring the ionosphere and atmosphere, and the instability that leads to substorms (explosive releases of energy into the nightside auroral ionosphere). FINESSE will liaise with space weather forecasters and other stakeholders to disseminate this greater understanding of small-scale processes in producing space weather hazards and to translate it into significant economic benefit to the UK.

  • Funder: UKRI Project Code: NE/W006650/1
    Funder Contribution: 652,019 GBP
    Partners: Natural England, JNCC, SNH, Swansea University, McGill University, University of Gothenburg

    Human activities have already raised global species extinction rates a thousand-fold and have pushed an additional million species towards extinction. Biodiversity is also rapidly changing on more local scales as climate change drives the redistribution of species, and pressures such as overharvesting and habitat fragmentation intensify in many areas. Understanding how biodiversity influences ecosystem functions, such as carbon capture and fisheries productivity, is a crucial challenge directly relevant to meeting the UN sustainable development goals, and UK policy imperatives of harnessing biodiversity to achieve sustainable economic growth and using nature-based solutions to help meet 'net-zero' emissions by 2050. Since the mid- 1990s, several hundred experiments have tested how changes in biodiversity influence ecosystem functions and services, with many studies indicating that biodiversity loss does not reduce functioning as long as the single best-performing species is retained. However, these studies have focused on local-scale interactions between species in small habitat units such as grassland plots, field enclosures, or aquarium tanks; we therefore lack studies that consider BEF relationships on the larger landscape-, regional- or even national- scales most relevant to the public, ecosystem managers, and policy makers. Ecological theory suggests that biodiversity is more important for ecosystem services as scale increases due to greater environmental variation, but it cannot currently be evaluated in real ecosystems because we lack BEF studies across scales and environmental gradients. In this project we aim to bridge the gap between experiments and relevant larger scales by using Great Britain's intertidal forests as a model system. These highly productive and valuable ecosystems occur extensively around the GB's varied and complex coastlines and are formed by a manageable suite of seaweed species which can be easily manipulated across multiple distinct environmental gradients. To meet our overall aim, we will incorporate multiple environmental factors into experiments, observations and models delivered across three inter-linked work packages which together provide a generalised approach and scaling relationships for BEF. Our first work package uses a 100km stretch of the south Wales coastline - which incorporates gradients in wave exposure and turbidity - as an accessible template to experimentally test the causal effect of intertidal forest biodiversity on ecosystem functioning from small patches to the whole coastline. Our second package combines a network of standardised observations in intertidal forests around GB, with satellite remote sensing and statistical modelling, to test how BEF relationships scale-up -- from 1 m to 1000km scales -- in naturally assembled communities. The third and final work package uses the new experimental and observational data to inform dynamic models, allowing us to test how species traits such as dispersal and environmental tolerances interacts with environmental variability to determine BEF relationships across scales. A key innovation here is the explicit - and empirically informed - integration of spatial environmental variability in multiple environmental factors. These will be generalised to represent how the environment varies in a range of different ecosystems from forests, to agricultural landscapes, and to coral reefs. The advancement of our project aim will deliver a revised appreciation of the role of diversity in ecosystems and demonstrate a generalizable approach for upscaling biodiversity - ecosystem functioning relationships. We anticipate that this will feed into predictions for how biodiversity changes will influence ecosystem functioning and services on large, relevant- scales, in intertidal forests and beyond, with a range of applications from natural capital models, to the design of large-scale ecosystem restoration projects.