Dynamic modelling shows substantial contribution of ecosystem restoration to climate change mitigation

This is the final version. Available from the Global Systems Institute, University of Exeter via the link in this recordGSI scientific working paper series number 2021/02Limiting global warming to a 1.5°C temperature rise requires drastic emissions reductions and removal of carbon dioxide from the atmosphere. Most modelled pathways for 1.5°C assume substantial removals in the form of biomass energy with carbon capture and storage, which brings with it increasing risks to biodiversity and food security via extensive land-use change. Recently, multiple efforts to describe and quantify potential removals via ecosystem-based approaches have gained traction in the climate policy discourse. However, these options have yet to be evaluated in a systematic and scientifically robust way. We provide spatially explicit estimates of ecosystem restoration potential quantified with a Dynamic Global Vegetation Model. Simulations covering forest restoration, reforestation, reduced harvest, agroforestry and silvopasture were combined and found to sequester an additional 93 Gt C by 2100, reducing mean global temperature increase by ~0.12°C (5-95% range 0.06-0.21°C) relative to a baseline mitigation pathway. Ultimately, pathways to achieving the 1.5°C goal garner broader public support when they include land management options that can bring about multiple benefits, including ecosystem restoration, biodiversity protection, and resilient agricultural practices

Decarbonising the critical sectors of aviation, shipping, road freight and industry to limit warming to 1.5–2°C

Limiting warming to well below 2°C requires rapid and complete decarbonisation of energy systems. We compare economy-wide modelling of 1.5°C and 2°C scenarios with sector-focused analyses of four critical sectors that are difficult to decarbonise: aviation, shipping, road freight transport, and industry. We develop and apply a novel framework to analyse and track mitigation progress in these sectors. We find that emission reductions in the 1.5°C and 2°C scenarios of the IMAGE model come from deep cuts in CO2 intensities and lower energy intensities, with minimal demand reductions in these sectors’ activity. We identify a range of additional measures and policy levers that are not explicitly captured in modelled scenarios but could contribute significant emission reductions. These are demand reduction options, and include less air travel (aviation), reduced transportation of fossil fuels (shipping), more locally produced goods combined with high load factors (road freight), and a shift to a circular economy (industry). We discuss the challenges of reducing demand both for economy-wide modelling and for policy. Based on our sectoral analysis framework, we suggest modelling improvements and policy recommendations, calling on the relevant UN agencies to start tracking mitigation progress through monitoring key elements of the framework (CO2 intensity, energy efficiency, and demand for sectoral activity, as well as the underlying drivers), as a matter of urgency

A Functional Misexpression Screen Uncovers a Role for Enabled in Progressive Neurodegeneration

Drosophila is a well-established model to study the molecular basis of neurodegenerative diseases. We carried out a misexpression screen to identify genes involved in neurodegeneration examining locomotor behavior in young and aged flies. We hypothesized that a progressive loss of rhythmic activity could reveal novel genes involved in neurodegenerative mechanisms. One of the interesting candidates showing progressive arrhythmicity has reduced enabled (ena) levels. ena down-regulation gave rise to progressive vacuolization in specific regions of the adult brain. Abnormal staining of pre-synaptic markers such as cystein string protein (CSP) suggest that axonal transport could underlie the neurodegeneration observed in the mutant. Reduced ena levels correlated with increased apoptosis, which could be rescued in the presence of p35, a general Caspase inhibitor. Thus, this mutant recapitulates two important features of human neurodegenerative diseases, i.e., vulnerability of certain neuronal populations and progressive degeneration, offering a unique scenario in which to unravel the specific mechanisms in an easily tractable organism

Epsin 1 Promotes Synaptic Growth by Enhancing BMP Signal Levels in Motoneuron Nuclei

We thank Carl-Henrik Heldin (Uppsala University, Sweden) for his generous gift of the PS1 pMad antibody, Hugo Bellen, Corey Goodman, Janis Fischer, Graeme Davis, Guillermo Marques, Michael O'Connor, Kate O'Connor-Giles, and the Bloomington Drosophila Stock Center for flies strains, the Developmental Studies Hybridoma Bank at the University of Iowa for antibodies to Wit and CSP; Marie Phillips for advice on membrane fractionation; Avital Rodal, Kate O'Connor-Giles, Ela Serpe, Kristi Wharton, Mojgan Padash-Barmchi for discussions or comments on the manuscript. We also thank Jody Summers at OUHSC for her generosity in letting us to use her confocal microscope.Conceived and designed the experiments: PAV TRF LRC BZ. Performed the experiments: PAV TRF LRC SMR HB NER BZ. Analyzed the data: PAV TRF LRC SMR HB NER BZ. Wrote the paper: PAV TRF BZ.Bone morphogenetic protein (BMP) retrograde signaling is crucial for neuronal development and synaptic plasticity. However, how the BMP effector phospho-Mother against decapentaplegic (pMad) is processed following receptor activation remains poorly understood. Here we show that Drosophila Epsin1/Liquid facets (Lqf) positively regulates synaptic growth through post-endocytotic processing of pMad signaling complex. Lqf and the BMP receptor Wishful thinking (Wit) interact genetically and biochemically. lqf loss of function (LOF) reduces bouton number whereas overexpression of lqf stimulates bouton growth. Lqf-stimulated synaptic overgrowth is suppressed by genetic reduction of wit. Further, synaptic pMad fails to accumulate inside the motoneuron nuclei in lqf mutants and lqf suppresses synaptic overgrowth in spinster (spin) mutants with enhanced BMP signaling by reducing accumulation of nuclear pMad. Interestingly, lqf mutations reduce nuclear pMad levels without causing an apparent blockage of axonal transport itself. Finally, overexpression of Lqf significantly increases the number of multivesicular bodies (MVBs) in the synapse whereas lqf LOF reduces MVB formation, indicating that Lqf may function in signaling endosome recycling or maturation. Based on these observations, we propose that Lqf plays a novel endosomal role to ensure efficient retrograde transport of BMP signaling endosomes into motoneuron nuclei.Yeshttp://www.plosone.org/static/editorial#pee

Uncertain effectiveness of Miscanthus bioenergy expansion for climate change mitigation explored using land surface, agronomic and integrated assessment models

This is the author accepted manuscript. The final version is available on open access from Wiley via the DOI in this recordLarge-scale bioenergy plays a key role in climate change mitigation scenarios, but its efficacy is uncertain. This study aims to quantify that uncertainty by contrasting the results of three different types of models under the same mitigation scenario (RCP2.6-SSP2), consistent with a 2 °C temperature target. This analysis focuses on a single bioenergy feedstock, Miscanthus x giganteus, and contrasts projections for its yields and environmental effects from: an integrated assessment model (IMAGE), a land surface and dynamic global vegetation model tailored to Miscanthus bioenergy (JULES) and a bioenergy crop model (MiscanFor). Under the present climate, JULES, IMAGE and MiscanFor capture the observed magnitude and variability in Miscanthus yields across Europe; yet in the tropics JULES and IMAGE predict high yields, whereas MiscanFor predicts widespread drought-related diebacks. 2040-49 projections show there is a rapid scale up of over 200 Mha bioenergy cropping area in the tropics. Resulting biomass yield ranges from 12 (MiscanFor) to 39 (JULES) Gt dry matter over that decade. Change in soil carbon ranges from +0.7 Pg C (MiscanFor) to -2.8 Pg C (JULES), depending on preceding land cover and soil carbon.2090-99 projections show large-scale biomass energy with carbon capture and storage (BECCS) is projected in Europe. The models agree that <2 °C global warming will increase yields in the higher latitudes, but drought stress in the Mediterranean region could produce low yields (MiscanFor), and significant losses of soil carbon (JULES, IMAGE). These results highlight the uncertainty in rapidly scaling-up biomass energy supply, especially in dry tropical climates and in regions where future climate change could result in drier conditions. This has important policy implications – because prominently-used scenarios to limit warming to “well below 2 °C” (including the one explored here) depend upon its effectiveness.Natural Environment Research Council (NERC)UKRIEuropean Union Horizon 202

Decarbonising the critical sectors of aviation, shipping, road freight and industry to limit warming to 1.5-2 degrees C

Limiting warming to well below 2&#xB0;C requires rapid and complete decarbonisation of energy systems. We compare economy-wide modelling of 1.5&#xB0;C and 2&#xB0;C scenarios with sector-focused analyses of four critical sectors that are difficult to decarbonise: aviation, shipping, road freight transport, and industry. We develop and apply a novel framework to analyse and track mitigation progress in these sectors. We find that emission reductions in the 1.5&#xB0;C and 2&#xB0;C scenarios of the IMAGE model come from deep cuts in CO2 intensities and lower energy intensities, with minimal demand reductions in these sectors&#x2019; activity. We identify a range of additional measures and policy levers that are not explicitly captured in modelled scenarios but could contribute significant emission reductions. These are demand reduction options, and include less air travel (aviation), reduced transportation of fossil fuels (shipping), more locally produced goods combined with high load factors (road freight), and a shift to a circular economy (industry). We discuss the challenges of reducing demand both for economy-wide modelling and for policy. Based on our sectoral analysis framework, we suggest modelling improvements and policy recommendations, calling on the relevant UN agencies to start tracking mitigation progress through monitoring key elements of the framework (CO2 intensity, energy efficiency, and demand for sectoral activity, as well as the underlying drivers), as a matter of urgency. Key policy insights Four critical sectors (aviation, shipping, road freight, and industry) cannot cut their CO2 emissions to zero rapidly with technological supply-side options alone. Without large-scale negative emissions, significant demand reductions for those sectors&#x2019; activities are needed to meet the 1.5&#x2013;2&#xB0;C goal. Policy priorities include affordable alternatives to frequent air travel; smooth connectivity between low-carbon travel modes; speed reductions in shipping and reduced demand for transporting fossil fuels; distributed manufacturing and local storage; and tightening standards for material use and product longevity. The COVID-19 crisis presents a unique opportunity to enact lasting CO2 emissions reductions, through switching from frequent air travel to other transport modes and online interactions. Policies driving significant demand reductions for the critical sectors&#x2019; activities would reduce reliance on carbon removal technologies that are unavailable at scale

Improving the representation of sugarcane crop in the JULES model for climate impact assessment

Bioenergy from sugarcane production is considered a key mitigation strategy for global warming. Improving its representation in land surface models is important to further understand the interactions between climate and bioenergy production, supporting accurate climate projections and decision-making. This study aimed to calibrate and evaluate the Joint UK Land Environment Simulator (JULES) for climate impact assessments in sugarcane. A dataset composed of soil moisture, water and carbon fluxes and biomass measurements from field experiments across Brazil was used to calibrate and evaluate JULES-crop and JULES-BE parametrisations. The ability to predict the spatiotemporal variability of sugarcane yields and the impact of climate change was also tested at five Brazilian microregions. Parameters related to sugarcane allometry, crop growth and development were derived and tested for JULES-crop and JULES-BE, together with the response to atmospheric carbon dioxide, temperature and drought (CTW-response). Both parametrisations showed comparable performance to other sugarcane dynamic models, with an RMSE of 6.75 and 6.05 t ha-1 for stalk dry matter for JULES-crop and JULES-BE, respectively. The parametrisations were also able to replicate the average yield patterns observed in the five microregions over 30 years when the yield gap factors were taken into account, with the correlation (r) between simulated and observed interannual variability of yields ranging from 0.33 to 0.56. An overall small positive trend was found in future yield projections of sugarcane using the new calibrations, with exception of the Jataí mesoregion which showed a clear negative trend for the SSP5 scenario from the year 2070 to 2100. Our simulations showed that an abrupt negative impact on sugarcane yields is expected if daytime temperatures above 35 oC become more frequent. The newly calibrated version of JULES can be applied regionally and globally to help understand the interactions between climate and bioenergy production