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Abstract The Kerguelen Islands are part of the French Southern Territories, located at the limit of the Indian and Southern oceans. They are highly impacted by climate change, and coastal marine areas are particularly at risk. Assessing the responses of species and populations to environmental change is challenging in such areas for which ecological modelling can constitute a helpful approach. In the present work, a DEB-IBM model (Dynamic Energy Budget – Individual-Based Model) was generated to simulate and predict population dynamics in an endemic and common benthic species of shallow marine habitats of the Kerguelen Islands, the sea urchin Abatus cordatus. The model relies on a dynamic energy budget model (DEB) developed at the individual level. Upscaled to an individual-based population model (IBM), it then enables to model population dynamics through time as a result of individual physiological responses to environmental variations. The model was successfully built for a reference site to simulate the response of populations to variations in food resources and temperature. Then, it was implemented to model population dynamics at other sites and for the different IPCC climate change scenarios RCP 2.6 and 8.5. Under present-day conditions, models predict a more determinant effect of food resources on population densities, and on juvenile densities in particular, relative to temperature. In contrast, simulations predict a sharp decline in population densities under conditions of IPCC scenarios RCP 2.6 and RCP 8.5 with a determinant effect of water warming leading to the extinction of most vulnerable populations after a 30-year simulation time due to high mortality levels associated with peaks of high temperatures. Such a dynamic model is here applied for the first time to a Southern Ocean benthic and brooding species and offers interesting prospects for Antarctic and sub-Antarctic biodiversity research. It could constitute a useful tool to support conservation studies in these remote regions where access and bio-monitoring represent challenging issues.

Abstract The Kerguelen Islands are part of the French Southern Territories, located at the limit of the Indian and Southern oceans. They are highly impacted by climate change, and coastal marine areas are particularly at risk. Assessing the responses of species and populations to environmental change is challenging in such areas for which ecological modelling can constitute a helpful approach. In the present work, a DEB-IBM model (Dynamic Energy Budget – Individual-Based Model) was generated to simulate and predict population dynamics in an endemic and common benthic species of shallow marine habitats of the Kerguelen Islands, the sea urchin Abatus cordatus. The model relies on a dynamic energy budget model (DEB) developed at the individual level. Upscaled to an individual-based population model (IBM), it then enables to model population dynamics through time as a result of individual physiological responses to environmental variations. The model was successfully built for a reference site to simulate the response of populations to variations in food resources and temperature. Then, it was implemented to model population dynamics at other sites and for the different IPCC climate change scenarios RCP 2.6 and 8.5. Under present-day conditions, models predict a more determinant effect of food resources on population densities, and on juvenile densities in particular, relative to temperature. In contrast, simulations predict a sharp decline in population densities under conditions of IPCC scenarios RCP 2.6 and RCP 8.5 with a determinant effect of water warming leading to the extinction of most vulnerable populations after a 30-year simulation time due to high mortality levels associated with peaks of high temperatures. Such a dynamic model is here applied for the first time to a Southern Ocean benthic and brooding species and offers interesting prospects for Antarctic and sub-Antarctic biodiversity research. It could constitute a useful tool to support conservation studies in these remote regions where access and bio-monitoring represent challenging issues.

The integration of distributed renewable energy sources (RES) and the electrification of devices raise new challenges for the distribution system operator (DSO). This paper assesses PAR versus cost tradeoff when scheduling an electric vehicle (EV) fleet. We formulate a bilevel Mixed-Integer Linear Programming optimization problem. At the lower level, we minimize individual household electricity bills using dynamic pricings. At the upper level, we aim to smooth the power load curve of a typical Brussels MV/LV transformer. We show that a small deviation from cost-only optimization can reduce significantly the Peak-to-Average Ratio of the power load curve of a transformer. Harnessing load flexibility from EV allows the DSO to manage the transformer load to avoid grid congestion and also incentivizes load aggregators to participate in the ancillary services market.

The integration of distributed renewable energy sources (RES) and the electrification of devices raise new challenges for the distribution system operator (DSO). This paper assesses PAR versus cost tradeoff when scheduling an electric vehicle (EV) fleet. We formulate a bilevel Mixed-Integer Linear Programming optimization problem. At the lower level, we minimize individual household electricity bills using dynamic pricings. At the upper level, we aim to smooth the power load curve of a typical Brussels MV/LV transformer. We show that a small deviation from cost-only optimization can reduce significantly the Peak-to-Average Ratio of the power load curve of a transformer. Harnessing load flexibility from EV allows the DSO to manage the transformer load to avoid grid congestion and also incentivizes load aggregators to participate in the ancillary services market.

This paper revisits the concept of air/high-speed rail (HSR) integration in the specific case of congested airports, in which airport slots for (super) short-haul flights are freed by replacing them with high-speed trains. Freed slots are then likely allocated to longer flights, which leads to an increase in GHG emissions induced by flights from/to the airport into question. Such an unexpected effect is investigated through the case of Frankfurt Airport, where the HSR infrastructure was designed to connect smoothly with the airport. The ex post investigation isolates the time window during which airport capacity is stable. It confirms the increase in aviation climate impact. This illustrates that air/HSR integration is not always a relevant solution to curb the impact of aviation on climate change.

This paper revisits the concept of air/high-speed rail (HSR) integration in the specific case of congested airports, in which airport slots for (super) short-haul flights are freed by replacing them with high-speed trains. Freed slots are then likely allocated to longer flights, which leads to an increase in GHG emissions induced by flights from/to the airport into question. Such an unexpected effect is investigated through the case of Frankfurt Airport, where the HSR infrastructure was designed to connect smoothly with the airport. The ex post investigation isolates the time window during which airport capacity is stable. It confirms the increase in aviation climate impact. This illustrates that air/HSR integration is not always a relevant solution to curb the impact of aviation on climate change.

Abstract. Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and assess the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimates of the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes, forcings employed and initial states of ice sheet models. This study presents results from ice flow model simulations from 13 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015–2100 as part of the Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climate model results. Simulations of the Antarctic ice sheet contribution to sea level rise in response to increased warming during this period varies between −7.8 and 30.0 cm of sea level equivalent (SLE) under Representative Concentration Pathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment with constant climate conditions and should therefore be added to the mass loss contribution under climate conditions similar to present-day conditions over the same period. The simulated evolution of the West Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica mass change varies between −6.1 and 8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional simulated mass loss of 28 mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared to simulations done under present-day conditions for the two CMIP5 forcings used and display limited mass gain in East Antarctica.