Search

Marine animal biomass is expected to decrease in the 21st century due to climate driven changes in ocean environmental conditions. Previous studies suggest that the magnitude of the decline in primary production on apex predators could be amplified through the trophodynamics of marine food webs, leading to larger decreases in the biomass of predators relative to the decrease in primary production, a mechanism called trophic amplification. We compared relative changes in producer and consumer biomass or production in the global ocean to assess the extent of trophic amplification. We used simulations from nine marine ecosystem models (MEMs) from the Fisheries and Marine Ecosystem Models Intercomparison Project forced by two Earth System Models under the high greenhouse gas emissions Shared Socioeconomic Pathways (SSP5-8.5) and a scenario of no fishing. Globally, total consumer biomass is projected to decrease by 16.7 ± 9.5% more than net primary production (NPP) by 2090-2099 relative to 1995-2014, with substantial variations among MEMs and regions. Total consumer biomass is projected to decrease almost everywhere in the ocean (80% of the worlds oceans) in the model ensemble. In 40% of the worlds oceans, consumer biomass was projected to decrease more than NPP. Additionally, in another 36% of the worlds oceans consumer biomass is expected to decrease even as projected NPP increases. By analysing the biomass response within food webs in available MEMs, we found that model parameters and structures contributed to more complex responses than a consistent amplification of climate impacts of higher trophic levels. Our study provides additional insights into the ecological mechanisms that will impact marine ecosystems, thereby informing model and scenario development.

Projections of climate change impacts on marine ecosystems have revealed long-term declines in global marine animal biomass and unevenly distributed impacts on fisheries. Here we apply an enhanced suite of global marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project (Fish-MIP), forced by new-generation Earth system model outputs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), to provide insights into how projected climate change will affect future ocean ecosystems. Compared with the previous generation CMIP5-forced Fish-MIP ensemble, the new ensemble ecosystem simulations show a greater decline in mean global ocean animal biomass under both strong-mitigation and high-emissions scenarios due to elevated warming, despite greater uncertainty in net primary production in the high-emissions scenario. Regional shifts in the direction of biomass changes highlight the continued and urgent need to reduce uncertainty in the projected responses of marine ecosystems to climate change to help support adaptation planning.

While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.

In this note we revisit the empirical results in Bianchi, Büchner, and Tamoni (2020) after correcting for using information not available at the time the forecast was made. Although we note a decrease in out-of-sample |$R^2$|⁠ , the revised analysis confirms that bond excess return predictability from neural networks remains statistically and economically significant. [ABSTRACT FROM AUTHOR]

We show that machine learning methods, in particular, extreme trees and neural networks (NNs), provide strong statistical evidence in favor of bond return predictability. NN forecasts based on macroeconomic and yield information translate into economic gains that are larger than those obtained using yields alone. Interestingly, the nature of unspanned factors changes along the yield curve: stock- and labor-market-related variables are more relevant for short-term maturities, whereas output and income variables matter more for longer maturities. Finally, NN forecasts correlate with proxies for time-varying risk aversion and uncertainty, lending support to models featuring both channels. [ABSTRACT FROM AUTHOR]

The extent and impact of climate‐related extreme events depend on the underlying meteorological, hydrological, or climatological drivers as well as on human factors such as land use or population density. Here we quantify the pure effect of historical and future climate change on the exposure of land and population to extreme climate impact events using an unprecedentedly large ensemble of harmonized climate impact simulations from the Inter‐Sectoral Impact Model Intercomparison Project phase 2b. Our results indicate that global warming has already more than doubled both the global land area and the global population annually exposed to all six categories of extreme events considered: river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwaves. Global warming of 2°C relative to preindustrial conditions is projected to lead to a more than fivefold increase in cross‐category aggregate exposure globally. Changes in exposure are unevenly distributed, with tropical and subtropical regions facing larger increases than higher latitudes. The largest increases in overall exposure are projected for the population of South Asia. Plain Language Summary: Global warming changes the frequency, intensity, and spatial distribution of extreme events. We analyze computer simulations of river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwaves under past, present‐day, and potential future climate conditions. Our results show that global warming increases the number of people around the world that are affected by these events each year, both for all event types combined and each type individually. Changes in the chance of being affected by extreme events are unevenly distributed in space. Particularly large increases are simulated for tropical and subtropical regions. Key Points: We quantify the pure effect of climate change on the exposure to extreme climate impact events, for both historical and future time periodsGlobal warming increases the global population exposure to river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwavesThe largest increases in exposure are projected for tropical and subtropical regions [ABSTRACT FROM AUTHOR]

This paper describes time-dependent phase modulation experiments using an optical Michelson interferometer. Changes in the path length of the interferometer arms induce phase shifts in time and, thanks to a loudspeaker, make the interferometric signal audible. We produce time-fluctuating refractive indices and mechanical motions of one reflecting mirror. A sinusoidal motion is applied, thus creating a phase modulation of the wave in one of the interferometer arms. Sidebands of the laser frequency appear, which interfere with the other interferometer wave. Our hearing sense is quite developed, and we use it to analyze the non-linear character by the acoustic timbre. Finally, we transfer information by phase modulation. Our setup benefits the visually impaired community as temporal phase changes can be analyzed by the auditory sense, but this unconventional use of an optical interferometer is also attractive to a general audience. [ABSTRACT FROM AUTHOR]

Model intercomparison studies in the climate and earth sciences communities have been crucial to build credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within- and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment, and consequent effects on food security, biodiversity, marine industries and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size) and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem, and implies that the assemblage of all models is more likely to include a greater number of relevant processes than is any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) CMIP5 outputs under prescribed scenarios for historic (from 1950s) and future (to 2100) time periods; it will be adapted to CMIP6 in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between, and uncertainties within, models and projections when assessing climate and fisheries impacts on marine ecosystems and the services they provide. The systematic generation, collation and comparison of results from Fish-MIP will inform understanding of the range of plausible changes in marine ecosystems, and improve our capacity to define and convey strengths and weaknesses of model-based advice on future states of marine ecosystems and fisheries. Ultimately, Fish-MIP represents a step towards bringing together the marine ecosystem modelling community to produce consistent ensemble medium- and long-term projections of marine ecosystems. [ABSTRACT FROM AUTHOR]

Electricity generation by wind power plants is gaining importance all over the world. Climate change may increase or decrease the potential for wind power generation. An approach to assess the effects of climate change on wind power production is presented. Simulation results indicate small impacts of climate change on wind power generation in Germany. The northern areas seem to profit from climate change, while in small regions in the southern areas negative effects occur. According to the study’s analysis, climate change will not negatively affect wind power production. The overall effect will be surpassed by the expansion in wind power generation capacity. [ABSTRACT FROM PUBLISHER]

The light reflected by an uncoated Fabry-Perot etalon presents dark rings which give a very sensitive measurement of the variations of the return optical path in the etalon. By measuring the diameters of these rings as a function of the etalon temperature T, we get a sensitive measurement of the derivative dn/dT of the index of refraction n. We have made this experiment with a fused silica etalon and we have achieved a 2% relative uncertainty on dn/dT, comparable to the uncertainty of the best experiments.