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Abstract. Regional land carbon budgets provide insights on the spatial distribution of the land uptake of atmospheric carbon dioxide, and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions, due to different definitions and component fluxes reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers, that connect CO2 uptake in one area with its release in another also requires better definition and protocols to reach harmonized regional budgets that can be summed up to the globe and compared with the atmospheric CO2 growth rate and inversion results. In this study, for the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims as an update of regional carbon budgets over the last two decades based on observations, for 10 regions covering the globe, with a better harmonization that the precursor project, we provide recommendations for using atmospheric inversions results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes and land use fluxes.

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.

# Genetic background and thermal regime influence adaptation to novel environment in the seed beetle, Callosobruchus maculatus [https://doi.org/10.5061/dryad.f1vhhmgz7](https://doi.org/10.5061/dryad.f1vhhmgz7) The data contained in these two data files (bodymass.csv and lifehistory.csv) contain data on body mass, development time, lifetime reproductive success, and age-specific reproduction of two populations of *Callosobruchus maculatus* that evolved under fluctuating or constant thermal regimes and were subsequently assayed under fluctuating or thermal regimes. ## Description of the data and file structure bodymass.csv contains information on: * Pop: Population (either USA or LEIC). * Treatment: Note that C = Constant Regime Constant Environment; I = Fluctuating Regime Fluctuating Environment; CIA = Constant Regime Fluctuating Environment; ICA = Fluctuating Regime Constant Environment. The transformation for this occurs in the code. * Rep: Replicate number. * Sex: Sex of individual (M or F). * Day: Always 22. * VCMass: Chamber mass (g). * VCBeet.Mass: Chamber w/ beetle (g). * Beet.Mass: Beetle mass (g). lifehistory.csv contains information on: * Pop: Population (either USA or LEIC). * Treat: Treatment; note that C = Constant Regime Constant Environment; I = Fluctuating Regime Fluctuating Environment; CIA = Constant Regime Fluctuating Environment; ICA = Fluctuating Regime Constant Environment. The transformation for this occurs in the code. * Rep: Replicate. * Pair.Date: Date paired. * VC: Chamber ID. * DayEgg: Egg day. * DateEgg: Date of first egg lay. * DateMeasure: Date of measurement for offspring. * DT: Development Time. * Males/Female/Total: Number of offspring that are Male/Female/Combined Total. * Comments: Comments made during data collection. ## Code/Software Code used to run the analysis and produce the graphs is located on GitHub via https://github.com/EIvimeyCook/Fluctuating\_Beetles or via Zenodo with the DOI, https://zenodo.org/doi/10.5281/zenodo.10118422. Climate change is associated with the increase in both mean and variability of thermal conditions. Therefore, the use of more realistic fluctuating thermal regimes is the most appropriate laboratory method for predicting population responses to thermal heterogeneity. However, the long- and short-term implications of evolving under such conditions are not well understood. Here, we examined differences in key life history traits among populations of seed beetles (Callosobruchus maculatus) that evolved under either constant control conditions or in an environment with fluctuating daily temperatures. Specifically, individuals from two distinct genetic backgrounds were kept for 19 generations at one of two temperatures, a constant temperature (T=29°C) or a fluctuating daily cycle (Tmean=33°C, Tmax=40°C, and Tmin=26°C), and were assayed either in their evolved environment or in the other environment. We found that beetles that evolved in fluctuating environments but were then switched to constant 29°C conditions had far greater lifetime reproductive success compared to beetles that were kept in their evolved environments. This increase in reproductive success suggests that beetles raised in fluctuating environments may have evolved greater thermal breadth than control condition beetles. In addition, the degree of sexual dimorphism in body size and development varied as a function of genetic background, evolved thermal environment, and current temperature conditions. These results highlight not only the value of incorporating diel fluctuations into climate research but also suggest that populations that experience variability in temperature may be better able to respond to both short- and long-term changes in environmental conditions.

Abstract. Model intercomparison studies in the climate and Earth sciences communities have been crucial to building 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 the 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), which is 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 any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) Coupled Model Intercomparison Project Phase 5 (CMIP5) outputs under prescribed scenarios for historic (from the 1950s) and future (to 2100) time periods; it will be adapted to CMIP phase 6 (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 an understanding of the range of plausible changes in marine ecosystems and improve our capacity to define and convey the 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.