Earths Future最新文献

Biodiversity, vital for ecosystem stability and human well-being, faces threats from land use and climate change. Accurately predicting these effects is crucial for effective conservation. High emission development scenario is commonly viewed as the most detrimental to biodiversity. However, recent researches suggest a more complex relationship between development paths and biodiversity outcomes. Our study addresses this by using an emergy-based approach to estimate current provincial-level biodiversity potential and project future species richness losses (amphibians, mammals, and birds) across climate zones and provincial divisions under various SSP-RCP scenarios for 2030, 2050, 2070, and 2090. The results revealed significant regional variations in China's biodiversity potential, with the highest in southwestern provinces. Future land use trends indicate increased construction land and barren alongside a decline in grasslands, leading to considerable habitat loss and fragmentation under various scenarios, stressing conservation needs. Future biodiversity loss follows the Hu line and climate zones, with significant decreases in the south and humid regions. Land-use changes could reduce species richness by 1–6 per 10 km grid cell. High-emission scenario SSP585 do not necessarily have the most detrimental effects on biodiversity and different scenarios require targeted focus on specific climatic zones and provinces. These findings underscore that different scenarios require targeted conservation efforts in specific regions sensitive to biodiversity loss. Our study provides a scientific foundation for these targeted efforts, ensuring that regions are prioritized under various future scenarios. This approach aids in developing effective conservation strategies amidst the complex interplay of land use dynamics and climate change.

Most of the world's population faces freshwater scarcity threats, and reservoirs, built both for ensuring water supply during prolonged droughts and reducing downstream flood risks, are critical infrastructure for water sustainability. Historical inflow data and water demand were used to estimate reservoir storage allocation and operation policies when designing and building reservoirs, 50–100 years ago. This study assesses historical reservoir operations in 16 Southeastern reservoirs and evaluates the potential for utilizing existing flood control storage for alternative purposes without increasing downstream flood risk. Using a reservoir simulation model, we evaluate the resulting storage under four initial storage conditions for observed and synthetic seasonal maximum 6-day flood pulses. For most reservoirs, we find conservation storage is depleting and did not exceed the flood storage capacity in their historical operation. The simulation model resulted in most of the reservoirs' storage levels staying within the flood control pool for all scenarios (for observed and synthetic floods). Additional flood risk was lowest for initial storage condition 1 (flood control pool empty) and highest with condition 2 (50% of the flood control pool full). Flood risk increased the most for reservoirs with small ratios of flood control to conservation pool storage. Our study shows the potential for reallocation and utilization of flood control storage to meet the increasing demand. As limited opportunities for new reservoirs exist, utilizing current reservoir storage without introducing additional downstream risk may be an effective management strategy to mitigate flood and drought risk under climate change and population growth.

Critical Zone (CZ) scientists have advanced understanding of Earth's surface through process-based research that quantifies water, energy, and mass fluxes in predominantly undisturbed systems. However, the CZ is being increasingly altered by humans through climate and land use change. Expanding the scope of CZ science to include both human- and non-human controls on the CZ is important for understanding anthropogenic impacts to Earth's surface processes and ecosystem services. Here, we share perspectives from predominantly U.S.-based, early career CZ scientists centered around broadening the scope of CZ science to focus on societally relevant science through a transdisciplinary science framework. We call for increased training on transdisciplinary methods and collaboration opportunities across disciplines and with stakeholders to foster a scientific community that values transdisciplinary science alongside physical science. Here, we build on existing transdisciplinary research frameworks by highlighting the need for institutional support to include and educate graduate students throughout the research processes. We also call for graduate-student-led initiatives to increase their own exposure to transdisciplinary science through activities such as transdisciplinary-focused seminars and symposiums, volunteering with local conservation groups, and participating in internships outside academia.

The food and energy systems face mounting challenges due to increasing demands and sustainability constraints, which impact their ability to efficiently utilize natural resources, such as land and freshwater. Among these challenges, competition for land between large-scale renewable energy production plants and agriculture poses a risk, especially for photovoltaics. Agrivoltaics offers an opportunity to synergistically use land for simultaneous production of energy and food. Recent studies have investigated the upscaling potential of agrivoltaics, moving from field scale analyses to larger-scale suitability assessments. Yet, studies addressing the interaction between crop dynamics and local climatic factors, as well as explicitly investigating hydrological dynamics of agrivoltaics across crops and climates, are still limited. Here, we first superpose a spatial data set of existing photovoltaic farms with different land use/land cover maps to assess the magnitude of land use competition associated with photovoltaics. Then, we use a spatialized agro-hydrological model to simulate the response to different levels of radiation attenuation of 22 non-irrigated crops in their harvested areas across the globe. We find that 22%–35% of rainfed harvested areas globally would maintain their yields if converted to agrivoltaics, while 13%–16% of ground-mounted photovoltaic plants globally are associated with a cropland to non-cropland transition. While carrying the typical limitations and uncertainties of global studies, our results may offer novel possibilities for cross-crop and cross-location comparisons of agrivoltaic experiences, as well as a basis to have a deeper and cross-scale understanding of the feasibility of photovoltaics.

As the urgency to evaluate the impacts of climate change on marine ecosystems increases, there is a need to develop robust projections and improve the uptake of ecosystem model outputs in policy and planning. Standardizing input and output data is a crucial step in evaluating and communicating results, but can be challenging when using models with diverse structures, assumptions, and outputs that address region-specific issues. We developed an implementation framework and workflow to standardize the climate and fishing forcings used by regional models contributing to the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) and to facilitate comparative analyses across models and a wide range of regions, in line with the FishMIP 3a protocol. We applied our workflow to three case study areas-models: the Baltic Sea Mizer, Hawai'i-based Longline fisheries therMizer, and the southern Benguela ecosystem Atlantis marine ecosystem models. We then selected the most challenging steps of the workflow and illustrated their implementation in different model types and regions. Our workflow is adaptable across a wide range of regional models, from non-spatially explicit to spatially explicit and fully-depth resolved models and models that include one or several fishing fleets. This workflow will facilitate the development of regional marine ecosystem model ensembles and enhance future research on marine ecosystem model development and applications, model evaluation and benchmarking, and global-to-regional model comparisons.

Selenium is an essential micronutrient, yet its deficiency poses severe health risks, including Kashin-Beck disease, a debilitating disorder endemic to selenium-deficient regions like Tibet. Despite the known risks, the extent and drivers of selenium deficiency in Tibetan populations remain poorly characterized. Here, we present the first large-scale assessment of urinary selenium levels across Tibet, based on 637 systematically collected samples, revealing an average concentration of 7.71 μg/L, far below adequate thresholds. Dietary patterns, particularly reliance on the red meat and vegetable diet, emerged as the dominant factor influencing selenium levels, while aging was associated with a marked decline in selenium status. Geographical factors were found to exert indirect but significant effects. These findings highlight critical selenium deficiencies among Tibetan residents and emphasize the urgent need for targeted interventions, including the introduction of selenium-enriched foods, to mitigate health risks—especially for older populations most at risk.

Climate change is anticipated to considerably reduce global marine fish biomass, driving marine ecosystems into unprecedented states with no historical analogs. The Time of Emergence (ToE) marks the pivotal moment when climate conditions (i.e., signal) deviate from pre-industrial norms (i.e., noise). Leveraging ensemble climate-to-fish simulations from one Earth System Model (IPSL-CM6A-LR) and one Marine Ecosystem Model (APECOSM), this study examines the ToE of epipelagic, migratory and mesopelagic fish biomass alongside their main environmental drivers for two contrasted climate-change scenarios. Globally averaged biomass signals emerge over the historical period. Epipelagic biomass decline emerged earlier (1950) than mesozooplankton decline (2017) due to a stronger signal in the early 20th century, possibly related to trophic amplification induced by an early emerging surface warming (1915). Trophic amplification is delayed for mesopelagic biomass due to postponed warming in the mesopelagic zone, resulting in a later emergence (2017). ToE also displays strong size class dependence, with epipelagic medium sizes (20 cm) experiencing delayed emergence compared to the largest (1 m) and smallest (1 cm) categories. For the epipelagic and mesopelagic communities, the regional signal emergence lags behind the global average, with median ToE estimates of 2030 and 2034, respectively. This is due to stronger noise in regional time-series than in global averages. The regional ToEs are also spatially heterogeneous, driven predominantly by the signal pattern akin to mesozooplankton. Additionally, our findings underscore that mitigation efforts (i.e., transitioning from SSP5-8.5 to SSP1-2.6 scenario) can potentially curtail emerging ocean surface signals by 30%.

The low-lying, arid coastal regions of the Southern Mediterranean Basin, extending over 4,600 km, face daunting sea level rise and hydroclimatic changes due to shifting weather patterns. The impact of these factors on coastal urban buildings and infrastructure must be better understood. Alexandria, a historic and densely populated port city in Egypt representative of several coastal towns in the Southern Mediterranean, has experienced over 280 building collapses along its shorelines over the past two decades, and the root causes are still under investigation. We examine the decadal changes in coastal and hydroclimatic drivers along the city's coastline using photogrammetric satellite images from 1974 to 2021. We explore the interconnectivity between shoreline retreat, ground subsidence, and building collapses. Our results suggest that collapses are correlated with severe coastal erosion driven by sediment imbalances resulting from decades of inefficient landscape management and urban expansion along the city's waterfront. This severe erosion, combined with sea level rise, increases seawater intrusion, raising groundwater levels in coastal aquifers. Degrading ground stability and accelerating corrosion in building foundations ultimately culminating in collapses. We identified a coastal area of high vulnerability with over 7,000 buildings at risk, surpassing any other vulnerable zone in the Mediterranean Basin. We propose cost-effective and nature-based techniques for coastal landscape adaptation to alleviate these dangers in Alexandria and other Southern Mediterranean cities facing similar climatic challenges.

Compound dry and hot extreme (CDHE) summers in Europe, like 2015, 2018 and 2022, have wide ranging impacts: heat exacerbates moisture shortages during dry periods whereas water demand rises. Current studies of CDHE are mostly conducted in observations or coarse-resolution global climate model large ensembles. While the latter allow for the assessment of rare CDHE against the backdrop of internal variability, global ensembles fail in providing robust climate change signals at impact-relevant scales. To overcome this issue, we exploit a regional 50-member single-model initial condition large ensemble (SMILE). The SMILE provides an extensive database of CDHE in a current climate and at two global warming levels (+2°C, +3°C) across Europe in high geographical detail. We identify Northern France, Southern Germany, Switzerland, Southern Ireland, and the western coasts of the Black Sea with currently low CDHE frequency as emerging hotspots. These regions experience a tenfold increase of CDHE under global warming conditions, in parts resulting in yet unseen heat and dryness. Temperature is the dominant driver of frequency increases, except for western Europe. Additionally, tail dependence strengthens in regions with large increases in CDHE frequency. In European agricultural areas, soil moisture shows stronger negative correlations with CDHE intensity than with precipitation or temperature. Finally, our results indicate $��50��\%�$ fewer CDHE summers in a +2°C world compared to a +3°C world, highlighting the importance of climate mitigation to reduce the frequency of these multi-hazard events.

Compound inland flooding (CIF) arises from the concurrent interaction of multiple hydrometeorological drivers. In this study, we characterize key CIF events across North America, including two preconditioned events, rain-on-snow (ROS) and saturation excess flooding (SEF) for historical baseline conditions and global warming levels of 1.5, 2, and 4°C relative to the preindustrial level. Utilizing the high emission climate scenario (RCP8.5) from CanRCM4-LE with 50 members, the frequency and seasonality of compound events, along with the probability of these events leading to heavy runoff, and the relative role of external forcing and internal climate variability are assessed. We convert the identified hazards into risk levels by integrating them with exposure and vulnerability components. The results suggest that as global temperatures increase, the overall role of ROS events in causing significant runoff is projected to decrease compared to individual heavy rainfall. Concurrently, the impact of SEF occurrences is projected to become more pronounced. The signal-to-noise ratio highlights a high-confidence change signal for CIF events; however, uncertainty related to internal climate variability in future projections of joint probability with heavy runoff is more pronounced. These results underscore the need to consider compound mechanisms, dynamics, and risks associated with CIFs within systematic approaches to flood risk management.