The Sandynallah valley (Western Ghats, India) features one of the oldest peat accumulations in the world at >50 kyr and has been central to the reconstruction of late Quaternary paleoclimate using paleovegetation changes in the forest-grassland vegetation mosaic that coexist here. It is well-known that short-term disturbances (fire, frost, intense drought) can also cause vegetation switches when multiple stable states exist, but this framework has seldom been considered in paleoecology investigations. Using stable carbon isotope signatures (relative C3-C4 vegetation abundance) on the cellulose fraction from two well-dated peat cores ~170 m apart - Core 1 closer to the hillslope (32000 years old) and Core 2 from the centre of the valley floor (45,000 years old) - we looked at paleovegetation changes and the implications for paleoclimate reconstruction within the alternative stable states framework. Charcoal data from another sediment profile from the same valley was used to correlate with paleofires. We propose that the valley floor is bistable, switching between peat-forming vegetation ‘sedgeland’ and montane stunted evergreen forest ‘shola’, maintained by level of waterlogging. Core 1 shows shola-sedgeland dynamics with vegetation switching at c.22ka from shola (possibly due to fires) to a prolonged unstable state until 13 ka sustained by low waterlogging. Following a hiatus c.13-7 ka, sedgeland dominates, with a shift into shola at 3.75 ka driven by increasing aridity. Core 2 shows a relatively stable signature, enriched in C3-vegetation in the last glacial (45-20 ka) compared to the Holocene. Given temperature is the primary driver of abundance in C3-C4 mixed-grasslands, C4 dominance beginning c.18.5 ka followed by C4 enrichment is indicative of deglacial warming that continues into the Holocene except for a departure at ~10 ka. The record at Core 2 is indicative of changing climate while Core 1 shows disturbance-based vegetation dynamics. The simultaneously distinctive vegetation states in Cores 1 and 2 within the same valley is the first record of alternative stable states in the past in the montane tropics. Our results point to the need to account for short-term disturbances and site attributes before ascribing vegetation changes to changing climate in alternative stable states landscapes.
Transportation fuels flow through a complex supply chain from the point of crude oil extraction to the point of combustion. We present a model that tracks the movement of gasoline and diesel across the petroleum infrastructure network consisting of pipeline, tankers, trucks, trains, refineries, and blenders. While direct CO2 emissions, from combustion, outweigh all supply chain emissions from processing and fuel movement, the indirect CO2 emissions also contribute a not insignificant amount of emissions driven by demand of transportation fuels. We resolve county-scale supply chain (Scope 3) CO2 emissions using publicly accessible data to quantify fuel movement between different linkages and transportation modes across the country. For most of the US, the exact volume of fuel moved between counties, from different refineries, along different modes of transportation, is not explicitly known. Linear optimization is used to model these flows with supply and demand related constraints. This work presents the most complete view of spatially-resolved scope-3 style CO2 emissions from United States’ road transportation fuels. It offers a chance to investigate spatial patterns of scope-3 emissions across the country, as well as spatial differences between scope-1 and scope-3. Understanding embodied CO2 emissions of commodity flows across the US has implications for national and local policy.
Many states in US follow strict regulations on water discharge into the streams to enforce water quality standards, however water withdrawal restrictions from the streams are limited and inadequate in water management at the time of low flows. In states such as Virginia (VA), Virginia Department of Environmental Quality (VDEQ) requires a Virginia Water Protection (VWP) permit for all water withdrawals made from Virginia’s surface waters. However, under certain provisions of VWP regulations, users are exempted from having a permit (e.g., water withdrawal in existence before 1989) allowing unrestricted access for water withdrawals. Such permit exemptions are in existence in many states and present a severe challenge to the management of water supplies. Still, little research exists that quantifies the impact they could have on water availability. This study was conducted to compare the impact of permit exemptions on surface water availability and drought flows and compares these impacts to the relatively well-studied risks presented by climate change and demand growth in Virginia (VA). This study makes use of VaHydro, a comprehensive, modular flow model to examine the impacts of exempt users’ withdrawals, demand growth, climate change and compare with the base scenario representing current precipitation and temperature conditions and current withdrawals. While the reduction in flows was widespread in climate change scenario, the impacts were more localized in exempt users and demand growth scenarios. It was observed that permit exemptions existed in 90% of the counties in VA and impacts on flows exceeded than climate change scenario in certain regions and at the low flows. Higher reduction in flows was observed during winter months in climate change scenarios while reductions were observed higher in summer months in demand and exempt user scenarios.
Natural-like technosignatures candidates may represent a detection problem for both artificial systems and humans. We tested traditional computer vision models with natural formations with special characteristics, Ahuna Mons region in Ceres in this particular case. We looked if these artificial models may represent a trustful aid to human detection and identification of potential technosignatures in planetary surfaces. Ahuna Mons is a 4km particular geologic feature on the surface of Ceres of possibly cryovolcanic origin. The special characteristics of Ahuna Mons are also interesting in regard of its surrounding area, especially for the big crater besides. This crater possesses similarities with Ahuna Mons including diameter, age, morphology, etc. Under the cognitive psychology perspective and using current computer vision models we analyzed these two features on Ceres for comparison and pattern recognition similarities. Several algorithms were employed avoiding human cognitive bias. 3D analysis from images of both features characteristics are discussed. Results showed positive results for these algorithms about similarities of both features. Discussion is provided about implications of this pilot computer vision techniques experiment for Ahuna Mons and the potential cognitive bias problem of both human and Artificial Intelligence models and the risks for the search of technosignatures.
Over the last two decades, several datasets have been developed to assess flood risk at the global scale. In recent years, some of these datasets have become detailed enough to be informative at national scales. The use of these datasets nationally could have enormous benefits in areas lacking existing flood risk information and allow better flood management decisions and disaster response. In this study, we evaluate the usefulness of global data for assessing flood risk in five countries: Colombia, England, Ethiopia, India, and Malaysia. National flood risk assessments are carried out for each of the five countries using global datasets and methodologies. We also conduct interviews with key water experts in each country to explore what capacity there is to use these global datasets nationally. To assess national flood risk, we use 6 datasets of global flood hazard, 7 datasets of global population, and 3 different methods for calculating vulnerability that have been used in previous global studies of flood risk. We find that the datasets differ substantially at the national level, and this is reflected in the national flood risk estimates. While some global datasets could be of significant value for national flood risk management, others are either not detailed enough, or too outdated to be relevant at this scale. For the relevant global datasets to be used most effectively for national flood risk management, a country needs a functioning, institutional framework with capability to support their use and implementation.
Actions addressing anthropogenic climate change are paramount to survival; however, there are limitations to the current binary approach which considers adaptation and mitigation as separate actions. Insights from Indigenous pluralistic ontology reveals anticipatory capacity to include components of adaptation as well as mitigation. Drawing from our research in the Pamir Mountains of Tajikistan, ecological calendars build anticipatory capacity for climate change. Anticipatory capacity, having the ability to envision possible and sustainable futures, occurs in response to the changes in the environment. It includes elements of foresight as these actions are simultaneously in preparation for upcoming uncertainty. These two aspects are elements of the adaptation-mitigation binary respectively. As illustrated by the ecological calendars in the Bartang Valley of Tajikistan, this approach has been carried out for many generations and is founded upon context specificity, intellectual pluralism, and relations between the agropastoralists and transformations in their habitat. Reconceptualizing the adaptation-mitigation binary is not bound to the boarders of the Pamir Mountains, rather it is a practice that is relevant globally.
The field of MultiSector Dynamics (MSD) explores the dynamics and co-evolutionary pathways of human and Earth systems with a focus on critical goods, services, and amenities delivered to people through interdependent sectors. This commentary lays out core definitions and concepts, identifies MSD science questions in the context of the current state of knowledge, and describes ongoing activities to expand capacities for open science, leverage revolutions in data and computing, and grow and diversify the MSD workforce. Central to our vision is the ambition of advancing the next generation of complex adaptive human-Earth systems science to better address interconnected risks, increase resilience, and improve sustainability. This will require convergent research and the integration of ideas and methods from multiple disciplines. Understanding the tradeoffs, synergies, and complexities that exist in coupled human-Earth systems is particularly important in the context of energy transitions and increased future shocks.
Climate change is modifying the conditions of agricultural production. In particular, precipitations are redistributed in time and space. In the Rhine Valley, this results in prolonged and intensified dry and warm periods in summer on the one side, and wetter winters and heavy rain events on the other side (Riach et al., 2019). In agriculture, dry and warm periods can lead to severe loss in yields and revenue (Fuhrer & Jasper, 2009), while heavy rains can cause erosion and mudslides (Heitz, 2009) and excessive humidity can damage soils (Falloon & Betts, 2010) and favors fungal diseases (Rosenzweig et al., 2001). These evolutions of the water cycle will probably get worse as climate change go forth, and cannot anymore be totally prevented (Averbeck et al., 2019). Adaptation is therefore becoming a vital necessity (Darnhofer et al., 2010). Nevertheless, adoption or not of adaptation measures is a choice which depends on several factors: geographical (accessibility of a water resource; spatial, pedological and topographic situation of the farm); technical (equipment, workforce, know-how); economical (financial capacities, possible subsidies); geolegal (according to the rules in place in different territories). But, it can also depend on the perceptions a farmer has of climate change and of the benefits of adaptation, which are partially constructed through networks (interactions with colleagues, customers or agricultural organizations), leading to various trajectories of adaptation. Moreover, the adaptation measures shall not only be considered through their determinants, but also through their consequences, especially in terms of maladaptation, spatial inequalities but also synergies with mitigation and other issues. We base on semi-structured interviews conducted with crops and wine growing actors in the Rhine Valley (shared between France, Germany and Switzerland). Consequently, we can operate an innovative double comparison, between sectors and between countries, which sheds light on the most influential factors. We also observe that some measures are controversial, and promoted or rejected according to the actors, their perceptions and interests, resulting in a heterogeneous landscape where the role of consumers and borders remains significant. And, sometimes, hinders adaptation.
Sexual harassment in STEM continues to be a pervasive barrier to women’s full participation in the sciences. Many studies conclude that workplace culture and lack of clear policies and practices exacerbate the risks of sexual harassment. Remote research environments, such as field stations and ocean platforms, bring additional risk to researchers. Participants already face acute safety concerns related to the remoteness of the field station or oceanographic vessels, fewer and less clear policies and enforcement regulations are in place, and multiple institutions bear responsibility, leading to a challenging environment for preventing and handling incidents. This workshop explored the factors that permit sexual harassment in remote research, and aimed to develop practices to prevent and respond to harassment in the field. The California State University Desert Studies Center and the Center for Ocean Leadership convened workshop in March, 2021 to address sexual harassment in field science. Over three days, field and ocean science leadership and practitioners came together with leadership from professional societies and academia, and experts in sociology, policy, and social justice. The goals were to: 1) open a dialogue between sexual harassment experts and the field research community to develop best practices and recommendations; 2) build coordination and consistency in policy setting and enforcement across field stations and oceanographic platforms; 3) develop processes to monitor the reporting of sexual harassment instances occurring at remote field locations; and 4) promote a safe culture for scientists conducting research at remote field stations and on oceanographic vessels. The workshop compiled and developed best practices and recommendations in four key areas: 1) culture change, 2) policy, 3) accountability, and 4) reporting. These recommendations were targeted at all facets of field and ocean sciences, from academic and research institutions, professional societies, and funding agencies, to departments and field research crews. Here we will give an overview of the workshop findings, with particular focus on the recommendations for research leadership.
Article 6 of the Paris Agreement on greenhouse gases enables countries to cooperate in implementing their nationally determined contributions (NDCs) towards emission reduction. Current national policies may fail to deliver on the “well below 2℃” climate goal & international cooperation through carbon markets under Article 6 is expected to enhance flexibility in mitigation options, make it cost-effective and enhance mitigation ambition overall. As countries prepare for the Glasgow Conference of Parties (COP26), the rules for such mechanisms are expected to be finalized. We analyze three questions: What is the aggregate & spatial distribution of economic efficiency gains & financial flows between Global North & South with Article 6? What is the impact of limits on inclusion of nature-based solutions? What are the multisectoral dynamic effects on technology deployment & capital investment in the Global South? We use the GCAM (Global Change Analysis Model) integrated assessment model & an 8-scenario matrix with two emission trajectories achieving carbon neutrality based on equity principles. In each case, we measure the geographic distribution of economic gains till 2050 between a pathway where countries move independently or participate cooperatively in a global carbon market. We analyze the spatial and multisectoral impacts on electricity asset stranding & investments in different mitigation options, including CCS (carbon capture & sequestration), electric vehicles, energy efficiency & renewable energy technologies. Employing limits on land area engaged for mitigation from fossil fuel sources, we showcase the sensitivity of these results to nature-based solutions. We find that in contrast to the popular notion that the Global South will inevitably gain through such global carbon market transfers, the story is more intricate. There is also a noticeable impact of limiting nature-based solutions for countries in Latin America & Sub-Saharan Africa. Further we show differences in deployment of low-emissions technologies in the near term. This has implications for technological growth & incentives for mitigation. This study provides insights for design of future global markets or regional carbon clubs & shows equity tradeoffs in achieving economic efficiency in climate change mitigation.
Financial institutions’ investment and lending portfolios could be affected by both physical climate risks stemming from impacts related to increasing temperatures, and from transition climate risks stemming from the economic consequences of the shift to a low-carbon economy. Here we present a consistent framework to explore near term (to 2030) transition risks and longer term (to 2050) physical risks, globally and in specific regions, for a range of plausible greenhouse gas emissions and associated temperature pathways, spanning 1.5-4oC levels of long-term warming. We draw on a technology-rich, regionally disaggregated Integrated Assessment Model representing energy system, agricultural and land-based greenhouse gas emissions, a reduced complexity climate model to simulate probabilistic global temperature changes over the 21st century, and a suite of impacts models to estimate regional climate-related physical hazards and impacts deriving from the temperature change pathways and their underlying socio-economics. We consider 11 scenarios to explore the dependence of risks on both temperature pathways, as well as socio-economic, technology and policy choices. This builds and expands on existing exercises such as the Network for Greening the Financial System (NGFS). By 2050, physical risks deriving from major heatwaves, agricultural drought, heat stress and crop duration reductions depend greatly on the temperature pathway. By 2030, transition risks most sensitive to temperature pathways stem from economy-wide mitigation costs, carbon price increases, fossil fuel demand reductions and potential stranding of carbon-intensive assets such as coal-fired power stations. The more stringent the mitigation action, the higher the abatement costs and sector-specific transition risks. However, such scenarios result in lower physical climate hazards throughout the century. Our study also explores multiple 2 deg C pathways which demonstrate that scenarios with similar longer-term physical risks could have very different near-term transition risks depending on technological, policy and socio-economic factors. As such, “a single scenario will not answer all questions”.
We believe that the future of Earth Observation (EO) is in fusion, harmonization, and interoperability of satellite imagery. Intensified monitoring leads to better understanding of land use and reduction of maintenance costs for all Land Cover products. RapidAI4EO is an initiative that aims to establish the foundations for the next generation of Copernicus Land Monitoring Service (CLMS) products. The goal is to provide intensified monitoring of Land Use (LU), Land Cover (LC) changes at a much higher spatial resolution and temporal cadence than is possible today. Key objectives are to explore, evaluate, and quantify state of the art deep learning algorithms and methodologies that leverage three meter, daily time series, in conjunction with higher spectral resolution Sentinel-2 imagery. Consortium Partners: The RapidAI4EO projects brings together Planet Labs PBC, the operator of the world’s largest fleet of Earth-imaging satellites and the recognized leader of the CubeSat revolution, VITO, the main production center of the Copernicus Global Land Service, Vision Impulse, a recent spin-off of German Research Center for Artificial Intelligence (DFKI, the largest research center for Artificial Intelligence in the world and one of the two European NVIDIA AI Labs), the International Institute for Applied Systems Analysis (IIASA) whose Center for Earth Observation and Citizen Science (EOCS) devises new approaches and technologies to collect data on land cover and land use, and Serco Italia, a worldwide service provider to governments, international agencies and industries, and operator of the ONDA DIAS platform. The objectives of RapidAI4EO are: 1) the creation and release of the most comprehensive spatiotemporal EO training sets ever produced for machine learning; 2) the development and implementation of novel AI solutions for continuous change detection that leverage these data sets; 3)the ability to drive frequent temporal updates of the Corine Land Cover (CLC) product; and 4)to demonstrate improved LULC mapping using harmonized Sentinel-2 and very high resolution, high cadence data streams.
River systems originating from the Upper Indus Basin (UIB) are dominated by runoff from snow and glacier melt and summer monsoonal rainfall. These water resources are highly stressed as huge populations of people living in this region depend on them, including for agriculture, domestic use, and energy production. Projections suggest that the UIB region will be affected by considerable (yet poorly quantified) changes to the seasonality and composition of runoff in the future, which are likely to have considerable impacts on these supplies. Given how directly and indirectly communities and ecosystems are dependent on these resources and the growing pressure on them due to ever-increasing demands, the impacts of climate change pose considerable adaptation challenges. The strong linkages between hydroclimate, cryosphere, water resources, and human activities within the UIB suggest that a multi- and inter-disciplinary research approach integrating the social and natural/environmental sciences is critical for successful adaptation to ongoing and future hydrological and climate change. Here we use a horizon scanning technique to identify the Top 100 questions related to the most pressing knowledge gaps and research priorities in social and natural sciences on climate change and water in the UIB. These questions are on the margins of current thinking and investigation and are clustered into 14 themes, covering three overarching topics of ‘governance, policy, and sustainable solutions’, ‘socioeconomic processes and livelihoods’, and ‘integrated Earth System processes’. Raising awareness of these cutting-edge knowledge gaps and opportunities will hopefully encourage researchers, funding bodies, practitioners, and policy makers to address them.
Hydrologic sciences depend on data monitoring, analyses, and simulations of hydrologic processes to ensure safe, sufficient, and equal water distribution. These hydrologic data come from but are not limited to primary (lab, plot, and field experiments) and secondary sources (remote sensing, UAVs, hydrologic models) that typically follow FAIR Principles (FAIR Principles - GO FAIR (go-fair.org)). Easy availability of FAIR data has become possible because the hydrology-oriented organizations have pushed the community to increase coordination of the protocols for generating data and sharing model platforms. In addition, networking at all levels has emerged with an invigorated effort to activate community science efforts that complement conventional data collection methods. However, it has become difficult to decipher various complex hydrologic processes with increasing data. Machine learning, a branch of artificial intelligence, provides more accurate and faster alternatives to better understand different hydrological processes. The Integrated, Coordinated, Open, Networked (ICONs) framework provides a pathway for water users to include and respect diversity, equity, and inclusivity. In addition, ICONs support the integration of peoples with historically marginalized identities into this professional discipline of water sciences. This article comprises three independent commentaries about the state of ICON principles in hydrology and discusses the opportunities and challenges of adopting them.
Sociopolitical values are an important driver of climate change beliefs, attitudes, and policy preferences. People with ‘individualist-hierarchical’ values favor individual freedom, competition, and clearly defined social hierarchies, while communitarian-egalitarians value interdependence and equality across gender, age, heritage, and ethnicity. In the US, individualist-hierarchs generally perceive less risk from climate change and express lower support for actions to mitigate it than communitarian-egalitarians. Exposure to scientific information does little to change these views. Here, we ask if a widely-used experiential simulation, World Climate, can help overcome these barriers. World Climate combines an engaging role-play with an interactive computer model of the climate system. We examine pre- and post-World Climate survey responses from 2,080 participants in the US and use a general linear mixed model approach to analyze interactions among participants’ sociopolitical values and gains in climate change knowledge, affect, and intent to take action. As expected, prior to the simulation, participants holding individualist-hierarchical values had lower levels of climate change knowledge, felt less urgency, and expressed lower intent to act than those holding communitarian-egalitarian values. However, individualist-hierarchs made significantly larger gains across all constructs, particularly urgency, than communitarian-egalitarians. Participants’ sociopolitical values also shifted: those with individualistic-hierarchical values before the simulation showed a substantial, statistically significant shift toward a communitarian-egalitarian worldview. Simulation-based experiences like World Climate may help reduce polarization and build consensus towards science-based climate action.
At least 37 studies demonstrate some degree of short-term influence of CO2 on human cognition, broadly considered, at CO2 concentrations frequently observed in buildings (>1000ppm). Ambient concentrations of CO2 in some cities can exceed global average values by several hundred ppm due to multiple large sources and idiosyncrasies of atmospheric transport, diffusion, and dispersion. In those few cities with extensive CO2 monitoring systems, local variations exceed 50ppm along transport corridors or close to point sources such as power plants. Scenarios of future CO2 concentrations project global average values up to 950ppm by 2100. Combining these various influences suggests that some locations in cities may regularly experience CO2 concentrations of 1300ppm by 2100. In occupied enclosed spaces such as schoolrooms, CO2 concentrations can rise several thousand ppm above ambient values. ASHRAE sets indoor air standards relative to ambient levels, not as absolute levels. Highly energy efficient buildings reduce air leakage and may have lower ventilation air exchange rates to reduce energy loss. LEED standards do not address effects of certification standards on CO2 concentrations. Cabs of vehicles and other enclosed spaces in the transport sector also can be several thousand ppm above ambient levels. Long-term exposure to elevated CO2 at these levels has not been studied in humans but limited studies of mouse models demonstrate respiratory impairments after three-month exposure to 890ppm CO2 for newborn mice. We are unaware of any studies of health impacts of CO2 on mice or humans that use pre-industrial concentrations of CO2 as baseline values. Thus, experimental methodologies must be reformed and standardized before we can fully appreciate how living in an elevated CO2 world is already affecting human health. Connecting the dots between these various influences suggests that exposure (particularly long-term exposure) to CO2 concentrations that affect cognition may vary significantly depending upon distance from active sources (power plants, roadways) and occupation (e.g. truck driver), such effects will grow to serious levels, may already exert a toll on human cognitive outcomes, and could implicate environmental justice concerns.
Production of food in space via photosynthetic crops similar to the ones we use on Earth requires profligate use of resources that will be in short supply in early long duration space missions. We demonstrate that production of bulk calories via chemotrophic single cell organisms is 2 to 3 orders of magnitude less expensive in terms of energy, volume, and water usage than via photosynthetic crops. In addition we survey the history and current state of the art in production of food from non-photosynthetic single cell organisms.
Vivo 1606 model is used for the study of standalone use of smartphone as a positioning device with FM supported location (Assisted- GNSS) for GPS, GLONASS, BeiDou. The observations were collected at every 5-minute interval for the analysis. The sessions were divided into three shifts morning, afternoon, and evening to check the accuracy in real time static mode. Mobile topographer app was used for capturing WGS-84 geographic coordinates having horizontal and vertical position with time in an urban environment to analyze which time of a day is good and till what time one can take GPS reading to get the minimum errors using smartphone. It is found that the positional dilution of precision (PDOP) stabilizes in about 35 minutes and minimizes at a value 0.2. The observations beyond have minor changes, so the position at 35 minutes has been used as reference for evaluation of statistical parameters. The real time observations of horizontal, vertical, and positional accuracy seem to increase with time as the PDOP, HDOP, VDOP values decrease i.e. improves with time. It has been observed that, RMSE of PDOP is 0.0485 and HDOP is 0.029 during afternoon is higher as compared to morning and evening values. The study suggest that the preference of survey shall be in the order: morning, evening and afternoon, which may further depend on the season at time. The survey during noon in summers can give much higher values of PDOP and thus the survey can be carried out during morning and evening times preferably.