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Abstract. In this study, we present the first combined open- and coastal-ocean pCO2 mapped monthly climatology (Landschützer et al., 2020b, https://doi.org/10.25921/qb25-f418, https://www.nodc.noaa.gov/ocads/oceans/MPI-ULB-SOM_FFN_clim.html, last access: 8 April 2020) constructed from observations collected between 1998 and 2015 extracted from the Surface Ocean CO2 Atlas (SOCAT) database. We combine two neural network-based pCO2 products, one from the open ocean and the other from the coastal ocean, and investigate their consistency along their common overlap areas. While the difference between open- and coastal-ocean estimates along the overlap area increases with latitude, it remains close to 0 µatm globally. Stronger discrepancies, however, exist on the regional level resulting in differences that exceed 10 % of the climatological mean pCO2, or an order of magnitude larger than the uncertainty from state-of-the-art measurements. This also illustrates the potential of such an analysis to highlight where we lack a good representation of the aquatic continuum and future research should be dedicated. A regional analysis further shows that the seasonal carbon dynamics at the coast–open interface are well represented in our climatology. While our combined product is only a first step towards a true representation of both the open-ocean and the coastal-ocean air–sea CO2 flux in marine carbon budgets, we show it is a feasible task and the present data product already constitutes a valuable tool to investigate and quantify the dynamics of the air–sea CO2 exchange consistently for oceanic regions regardless of its distance to the coast. 

Benthic animals profoundly influence the cycling and storage of carbon and other elements in marine systems, particularly in coastal sediments. Recent climate change has altered the distribution and abundance of many seafloor taxa and modified the vertical exchange of materials between ocean and sediment layers. Here, we examine how climate change could alter animal-mediated biogeochemical cycling in ocean sediments. The fossil record shows repeated major responses from the benthos during mass extinctions and global carbon perturbations, including reduced diversity, dominance of simple trace fossils, decreased burrow size and bioturbation intensity, and nonrandom extinction of trophic groups. The broad dispersal capacity of many extant benthic species facilitates poleward shifts corresponding to their environmental niche as overlying water warms. Evidence suggests that locally persistent populations will likely respond to environmental shifts through either failure to respond or genetic adaptation rather than via phenotypic plasticity. Regional and global ocean models insufficiently integrate changes in benthic biological activity and their feedbacks on sedimentary biogeochemical processes. The emergence of bioturbation, ventilation, and seafloor-habitat maps and progress in our mechanistic understanding of organism–sediment interactions enable incorporation of potential effects of climate change on benthic macrofaunal mediation of elemental cycles into regional and global ocean biogeochemical models. 

Inland waters are important sources of the greenhouse gasses (GHGs) carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) to the atmosphere. In the framework of the second phase of the REgional Carbon Cycle Assessment and Processes (RECCAP‐2) initiative, we synthesize existing estimates of GHG emissions from streams, rivers, lakes and reservoirs, and homogenize them with regard to underlying global maps of water surface area distribution and the effects of seasonal ice cover. We then produce regionalized estimates of GHG emissions over 10 extensive land regions. According to our synthesis, inland water GHG emissions have a global warming potential of an equivalent emission of 13.5 (9.9–20.1) and 8.3 (5.7–12.7) Pg CO₂‐eq. yr⁻¹at a 20 and 100 years horizon (GWP₂₀and GWP₁₀₀), respectively. Contributions of CO₂dominate GWP₁₀₀, with rivers being the largest emitter. For GWP₂₀, lakes and rivers are equally important emitters, and the warming potential of CH₄is more important than that of CO₂. Contributions from N₂O are about two orders of magnitude lower. Normalized to the area of RECCAP‐2 regions, S‐America and SE‐Asia show the highest emission rates, dominated by riverine CO₂emissions.

 

Constraints of temperature on spring plant phenology are closely related to plant growth, vegetation dynamics, and ecosystem carbon cycle. However, the effects of temperature on leaf onset, especially for winter chilling, are still not well understood. Using long‐term, widespread in situ phenology observations collected over China for multiple plant species, this study analyzes the quantitative response of leaf onset to temperature, and compares empirical findings with existing theories and modeling approaches, as implemented in 18 phenology algorithms. Results show that the growing degree days (GDD) required for leaf onset vary distinctly among plant species and geographical locations as well as at organizational levels (species and community), pointing to diverse adaptation strategies. Chilling durations (CHD) needed for releasing bud dormancy decline monotonously from cold to warm areas with very limited interspecies variations. Results also reveal that winter chilling is a crucial component of phenology models, and its effect is better captured with an index that accounts for the inhomogeneous effectiveness of low temperature to chilling rate than with the conventional CHD index. The impact of spring warming on leaf onset is nonlinear, better represented by a logistical function of temperature than by the linear function currently implemented in biosphere models. The optimized base temperatures for thermal accumulation and the optimal chilling temperatures are species‐dependent and average at 6.9 and 0.2°C, respectively. Overall, plants’ chilling requirement is not a constant, and more chilling generally results in less requirement of thermal accumulation for leaf onset. Our results clearly demonstrate multiple deficiencies of the parameters (e.g., base temperature) and algorithms (e.g., method for calculating GDD) in conventional phenology models to represent leaf onset. Therefore, this study not only advances our mechanistic and quantitative understanding of temperature controls on leaf onset but also provides critical information for improving existing phenology models.