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- Di Baldassarre, Giuliano, et al.
(författare)
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Integrating Multiple Research Methods to Unravel the Complexity of Human-Water Systems
- 2021
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Ingår i: AGU Advances. - : American Geophysical Union (AGU). - 2576-604X. ; 2:3
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Predicting floods and droughts is essential to inform the development of policy in water management, climate change adaptation and disaster risk reduction. Yet, hydrological predictions are highly uncertain, while the frequency, severity and spatial distribution of extreme events are further complicated by the increasing impact of human activities on the water cycle. In this commentary, we argue that four main aspects characterizing the complexity of human-water systems should be explicitly addressed: feedbacks, scales, tradeoffs and inequalities. We propose the integration of multiple research methods as a way to cope with complexity and develop policy-relevant science.Plain Language SummarySeveral governments today claim to be following the science in addressing crises caused by the occurrence of extreme events, such as floods and droughts, or the emergence of global threats, such as climate change and COVID-19. In this commentary, we show that there are no universal answers to apparently simple questions such as: Do levees reduce flood risk? Do reservoirs alleviate droughts? We argue that the best science we have consists of a plurality of legitimate interpretations and a range of foresights, which can be enriched by integrating multiple disciplines and research methods.
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| 2. |
- Hauri, Claudine, et al.
(författare)
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More Than Marine Heatwaves: A New Regime of Heat, Acidity, and Low Oxygen Compound Extreme Events in the Gulf of Alaska
- 2024
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Ingår i: AGU ADVANCES. - 2576-604X. ; 5:1
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Tidskriftsartikel (refereegranskat)abstract
- Recent marine heatwaves in the Gulf of Alaska have had devastating impacts on species from various trophic levels. Due to climate change, total heat exposure in the upper ocean has become longer, more intense, more frequent, and more likely to happen at the same time as other environmental extremes. The combination of multiple environmental extremes can exacerbate the response of sensitive marine organisms. Our hindcast simulation provides the first indication that more than 20% of the bottom water of the Gulf of Alaska continental shelf was exposed to quadruple heat, positive hydrogen ion concentration [H+], negative aragonite saturation state (omega arag), and negative oxygen concentration [O2] compound extreme events during the 2018-2020 marine heat wave. Natural intrusion of deep and acidified water combined with the marine heat wave triggered the first occurrence of these events in 2019. During the 2013-2016 marine heat wave, surface waters were already exposed to widespread marine heat and positive [H+] compound extreme events due to the temperature effect on the [H+]. We introduce a new Gulf of Alaska Downwelling Index (GOADI) with short-term predictive skill, which can serve as indicator of past and near-future positive [H+], negative omega arag, and negative [O2] compound extreme events near the shelf seafloor. Our results suggest that the marine heat waves may have not been the sole environmental stressor that led to the observed ecosystem impacts and warrant a closer look at existing in situ inorganic carbon and other environmental data in combination with biological observations and model output. The Gulf of Alaska supports a rich ocean ecosystem and valuable fisheries. Climate change and ocean acidification threaten to disrupt marine life in the region from plankton to fish, marine mammals, and sea birds. The gradual build-up of these environmental pressures can be exacerbated further by short-term extreme events, such as marine heat waves, that can temporarily push ocean conditions beyond physiological and ecological thresholds for some organisms. The problem is worsened by the co-occurrence of extreme events for multiple factors, for example, heat and acidity. Our analysis using a regional ocean model indicates that such compound extreme events have become more frequent and intense with time in the Gulf of Alaska, raising concerns for vulnerable parts of the ecosystem. Improvements in model forecasts and observing systems may help by providing advanced warning of compound extreme events and be useful to fisheries and marine resource managers as they develop climate adaptation strategies. 20% of the shelf bottom water was exposed to quadruple heat, positive [H+], negative omega arag, and negative [O2] compound extreme events in 2019Interaction of marine heat waves and local natural variability of deep-water intrusion triggered quadruple compound extreme events on shelfNew Gulf of Alaska Downwelling Index presented as indicator for environmental conditions on continental shelf
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| 3. |
- Kuhn, McKenzie A., et al.
(författare)
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Opposing Effects of Climate and Permafrost Thaw on CH4 and CO2 Emissions From Northern Lakes
- 2021
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Ingår i: AGU Advances. - : American Geophysical Union (AGU). - 2576-604X. ; 2:4
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Tidskriftsartikel (refereegranskat)abstract
- Small, organic-rich lakes are important sources of methane (CH4) and carbon dioxide (CO2) to the atmosphere, yet the sensitivity of emissions to climate warming is poorly constrained and potentially influenced by permafrost thaw. Here, we monitored emissions from 20 peatland lakes across a 1,600 km permafrost transect in boreal western Canada. Contrary to expectations, we observed a shift from source to sink of CO2 for lakes warmer regions, driven by greater primary productivity associated with greater hydrological connectivity to lakes and nutrient availability in the absence of permafrost. Conversely, an 8-fold increase in CH4 emissions in warmer regions was associated with water temperature and shifts in microbial communities and dominant anaerobic processes. Our results suggest that the net radiative forcing from altered greenhouse gas emissions of northern peatland lakes this century will be dominated by increasing CH4 emissions and only partially offset by reduced CO2 emissions.
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| 4. |
- Nilsson, Mats, et al.
(författare)
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Upscaling Wetland Methane Emissions From the FLUXNET-CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison
- 2023
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Ingår i: AGU Advances. - 2576-604X. ; 4
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Tidskriftsartikel (refereegranskat)abstract
- Wetlands are responsible for 20%-31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency similar to 0.52-0.63 and 0.53). UpCH(4) estimated annual global wetland CH4 emissions of 146 +/- 43 TgCH4 y(-1) for 2001-2018 which agrees closely with current bottom-up land surface models (102-181 TgCH4 y(-1)) and overlaps with top-down atmospheric inversion models (155-200 TgCH4 y -1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra-tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25 degrees from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ ORNLDAAC/2253).Plain Language Summary Wetlands account for a large share of global methane emissions to the atmosphere, but current estimates vary widely in magnitude (similar to 30% uncertainty on annual global emissions) and spatial distribution, with diverging predictions for tropical rice growing (e.g., Bengal basin), rainforest (e.g., Amazon basin), and floodplain savannah (e.g., Sudd) regions. Wetland methane model estimates could be improved by increased use of land surface methane flux data. Upscaling approaches use flux data collected across globally distributed measurement networks in a machine learning framework to extrapolate fluxes in space and time. Here, we train and evaluate a methane upscaling model (UpCH4) and use it to generate monthly, globally gridded wetland methane emissions estimates for 2001-2018. The UpCH4 model uses only six predictor variables among which temperature is dominant. Global annual methane emissions estimates and associated uncertainty ranges from upscaling fall within state-of-the-art model ensemble estimates from the Global Carbon Project (GCP) methane budget. In some tropical regions, the spatial pattern of UpCH4 emissions diverged from GCP predictions, however, inclusion of flux measurements from additional ground-based sites, together with refined maps of tropical wetlands extent, could reduce these prediction uncertainties.
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