Substantial interannual variability in marine fish recruitment (i.e., the number of young fish entering a fishery each year) has been hypothesized to be related to whether the timing of fish spawning ...matches that of seasonal plankton blooms. Environmental processes that control the phenology of blooms, such as stratification, may differ from those that influence fish spawning, such as temperature‐linked reproductive maturation. These different controlling mechanisms could cause the timing of these events to diverge under climate change with negative consequences for fisheries. We use an earth system model to examine the impact of a high‐emissions, climate‐warming scenario (RCP8.5) on the future spawning time of two classes of temperate, epipelagic fishes: “geographic spawners” whose spawning grounds are defined by fixed geographic features (e.g., rivers, estuaries, reefs) and “environmental spawners” whose spawning grounds move responding to variations in environmental properties, such as temperature. By the century's end, our results indicate that projections of increased stratification cause spring and summer phytoplankton blooms to start 16 days earlier on average (±0.05 days SE) at latitudes >40°N. The temperature‐linked phenology of geographic spawners changes at a rate twice as fast as phytoplankton, causing these fishes to spawn before the bloom starts across >85% of this region. “Extreme events,” defined here as seasonal mismatches >30 days that could lead to fish recruitment failure, increase 10‐fold for geographic spawners in many areas under the RCP8.5 scenario. Mismatches between environmental spawners and phytoplankton were smaller and less widespread, although sizable mismatches still emerged in some regions. This indicates that range shifts undertaken by environmental spawners may increase the resiliency of fishes to climate change impacts associated with phenological mismatches, potentially buffering against declines in larval fish survival, recruitment, and fisheries. Our model results are supported by empirical evidence from ecosystems with multidecadal observations of both fish and phytoplankton phenology.
We modeled the impacts of climate change on the timing of phytoplankton blooms and spawning of two classes of fishes: “geographic spawners” whose spawning grounds are defined by fixed features and “environmental spawners” whose spawning grounds move responding to environmental change. Phytoplankton blooms occurred 16 days earlier compared to baseline conditions. The phenology of geographic spawners changed twice as fast as phytoplankton, causing them to often spawn before the bloom. Trophic mismatches were less widespread for environmental spawners, indicating this behavioral mode increased resiliency to phenological mismatches. Mismatches experienced by geographic spawners could lead to declines in survival and recruitment.
Anthropogenic climate change has shifted the biogeography and phenology of many terrestrial and marine species.Marine phytoplankton communities appear sensitive to climate change, yet understanding ...of how individual species may respond to anthropogenic climate change remains limited. Here, using historical environmental and phytoplankton observations, we characterize the realized ecological niches for 87 North Atlantic diatom and dinoflagellate taxa and project changes in species biogeography between mean historical (1951–2000) and future (2051–2100) ocean conditions. We find that the central positions of the core range of 74% of taxa shift poleward at a median rate of 12.9 km per decade (km·dec−1), and 90% of taxa shift eastward at a median rate of 42.7 km·dec−1. The poleward shift is faster than previously reported for marine taxa, and the predominance of longitudinal shifts is driven by dynamic changes in multiple environmental drivers, rather than a strictly poleward, temperature-driven redistribution of ocean habitats. A century of climate change significantly shuffles community composition by a basin-wide median value of 16%, compared with seasonal variations of 46%. The North Atlantic phytoplankton community appears poised for marked shift and shuffle, which may have broad effects on food webs and biogeochemical cycles.
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.
Numerical models of ocean biogeochemistry are relied upon to make projections about the impact of climate change on marine resources and test hypotheses regarding the drivers of past changes in ...climate and ecosystems. In large areas of the ocean, iron availability regulates the functioning of marine ecosystems and hence the ocean carbon cycle. Accordingly, our ability to quantify the drivers and impacts of fluctuations in ocean ecosystems and carbon cycling in space and time relies on first achieving an appropriate representation of the modern marine iron cycle in models. When the iron distributions from 13 global ocean biogeochemistry models are compared against the latest oceanic sections from the GEOTRACES program, we find that all models struggle to reproduce many aspects of the observed spatial patterns. Models that reflect the emerging evidence for multiple iron sources or subtleties of its internal cycling perform much better in capturing observed features than their simpler contemporaries, particularly in the ocean interior. We show that the substantial uncertainty in the input fluxes of iron results in a very wide range of residence times across models, which has implications for the response of ecosystems and global carbon cycling to perturbations. Given this large uncertainty, iron fertilization experiments based on any single current generation model should be interpreted with caution. Improvements to how such models represent iron scavenging and also biological cycling are needed to raise confidence in their projections of global biogeochemical change in the ocean.
Key Points
First intercomparison of 13 global iron models highlights key challenges in reproducing iron data
Wide uncertainty in iron input fluxes, which results in poorly constrained residence times
Reducing uncertainty in scavenging and biological cycling is a priority
Transfer efficiency is the proportion of energy passed between nodes in food webs. It is an emergent, unitless property that is difficult to measure, and responds dynamically to environmental and ...ecosystem changes. Because the consequences of changes in transfer efficiency compound through ecosystems, slight variations can have large effects on food availability for top predators. Here, we review the processes controlling transfer efficiency, approaches to estimate it, and known variations across ocean biomes. Both process-level analysis and observed macroscale variations suggest that ecosystem-scale transfer efficiency is highly variable, impacted by fishing, and will decline with climate change. It is important that we more fully resolve the processes controlling transfer efficiency in models to effectively anticipate changes in marine ecosystems and fisheries resources.
Transfer efficiency is a key parameter describing ecosystem structure and function and is used to estimate fisheries production; however, it is also one of the most uncertain parameters.Questions remain about how habitats, food resources, fishing pressure, spatiotemporal scales, as well as temperature, primary production, and other climate drivers impact transfer efficiency.Direct measurements of transfer efficiency are difficult, but observations of marine population abundances, diets, productivity, stable isotope analysis, and models integrating these constraints can provide transfer efficiency estimates.Recent estimates suggest that transfer efficiency is more variable than previously thought, compounding uncertainties in marine ecosystem predictions and projections.Increased understanding of factors contributing to variation in transfer efficiency will improve projections of fishing and climate change impacts on marine ecosystems.
Accurate representation of the remineralization of sinking organic matter is crucial for reliable projections of the marine carbon cycle. Both water temperature and oxygen concentration are thought ...to influence remineralization rates, but limited data constraints have caused disagreement concerning the degree of these influences. We analyze a compilation of particulate organic carbon (POC) flux measurements from 19 globally distributed sites. Our results indicate that the attenuation of the flux of particulate organic matter depends on temperature with a Q10 between 1.5 and 2.01, and on oxygen described by a half‐saturation constant between 4 and 12 μmol/L. We assess the impact of the temperature and oxygen dependence in the biogeochemistry model Carbon, Ocean Biogeochemistry, and Lower Trophics, coupled to Geophysical Fluid Dynamics Laboratory's Earth System Model ESM2M. The new remineralization parameterization results in shallower remineralization in the low latitudes but deeper remineralization in the high latitudes, redistributing POC flux toward the poles. It also decreases the volume of the oxygen minimum zones, partly addressing a long‐standing bias in global climate models. Extrapolating temperature‐dependent remineralization rates to the surface (i.e., beyond the depth range of POC flux data) resulted in rapid recycling and excessive surface nutrients. Surface nutrients could be ameliorated by reducing near‐surface rates in a manner consistent with bacterial colonization, suggesting the need for improved remineralization constraints within the euphotic zone. The temperature and oxygen dependence cause an additional 10% decrease in global POC flux at 500 m depth, but no significant change in global POC flux at 2000 m under the RCP8.5 future projection.
Key Points
Remineralization of particulate organic matter depends on temperature (Q10 1.5–2.01) and on oxygen (half‐saturation constant 4–12 micromol/L)
The temperature and oxygen dependence cause an additional 10% decrease in carbon flux at 500 m
The temperature dependence decreases the volume of the oxygen minimum zone, reducing a ubiquitous bias in global biogeochemical simulations
Exchanges between coastal and oceanic waters shape both coastal ecosystem processes and signatures that they impart on global biogeochemical cycles. The timescales of these exchanges, however, are ...poorly represented in current‐generation, coarse‐grid climate models. Here we provide a novel global perspective on coastal residence time (CRT) and its spatio‐temporal variability using a new age tracer implemented in global ocean models. Simulated CRTs range widely from several days in narrow boundary currents to multiple years on broader shelves and in semi‐enclosed seas, in agreement with available observations. Overall, CRT is better characterized in high‐resolution models (1/8° and 1/4°) than in the coarser (1° and 1/2°) versions. This is in large part because coastal and open ocean grid cells are more directly connected in coarse models, prone to erroneous coastal flushing and an underestimated CRT. Additionally, we find that geometric enclosure of a coastal system places an important constraint on CRT.
Key Points
State‐of‐the‐art, high‐resolution global ocean simulations and a new tracer approach are used to estimate coastal residence times globally
Coarse models yield a negative residence time bias in 54% of the coastal ocean; this bias is particularly large in narrow boundary currents
Geometric enclosure as a function of coastal volume and open ocean boundary area places an important constraint on coastal residence time
Future projections of potential ocean ecosystem stressors, such as acidification, warming, deoxygenation, and changes in ocean productivity, are uncertain due to incomplete understanding of ...fundamental processes, internal climate variability, and divergent carbon emission scenarios. This complicates climate change impact assessments. We evaluate the relative importance of these uncertainty sources in projections of potential stressors as a function of projection lead time and spatial scale. Internally generated climate variability is the dominant source of uncertainty in middle‐to‐low latitudes and in most coastal large marine ecosystems over the next few decades, suggesting irreducible uncertainty inherent in these short projections. Uncertainty in projections of century‐scale global sea surface temperature (SST), global thermocline oxygen, and regional surface pH is dominated by scenario uncertainty, highlighting the critical importance of policy decisions on carbon emissions. In contrast, uncertainty in century‐scale projections of net primary productivity, low‐oxygen waters, and Southern Ocean SST is dominated by model uncertainty, underscoring that the importance of overcoming deficiencies in scientific understanding and improved process representation in Earth system models are critical for making more robust projections these potential stressors. We also show that changes in the combined potential stressors emerge from the noise in 39% (34–44%) of the ocean by 2016–2035 relative to the 1986–2005 reference period and in 54% (50–60%) of the ocean by 2076–2095 following a high‐carbon emission scenario. Projected large changes in surface pH and SST can be reduced substantially and rapidly with aggressive carbon emission mitigation but only marginally for oxygen. The regional importance of model uncertainty and internal variability underscores the need for expanded and improved multimodel and large initial condition ensemble projections with Earth system models for evaluating regional marine resource impacts.
Key Points
The sources of uncertainty in global and regional projections are quantified
Internal variability uncertainty is dominant on small spatial scales and short time horizons
Model and scenario uncertainties become dominant in end‐of‐century projections
The California Current System (CCS) is a biologically productive Eastern Boundary Upwelling System that experiences considerable environmental variability on seasonal and interannual timescales. ...Given that this variability drives changes in ecologically and economically important living marine resources, predictive skill for regional oceanographic conditions is highly desirable. Here, we assess the skill of seasonal sea surface temperature (SST) forecasts in the CCS using output from Global Climate Forecast Systems in the North American Multi-Model Ensemble (NMME), and describe mechanisms that underlie SST predictability. A simple persistence forecast provides considerable skill for lead times up to ~4 months, while skill above persistence is mostly confined to forecasts of late winter/spring and derives primarily from predictable evolution of ENSO-related variability. Specifically, anomalously weak (strong) equatorward winds are skillfully forecast during El Niño (La Niña) events, and drive negative (positive) upwelling anomalies and consequently warm (cold) temperature anomalies. This mechanism prevails during moderate to strong ENSO events, while years of ENSO-neutral conditions are not associated with significant forecast skill in the wind or significant skill above persistence in SST. We find also a strong latitudinal gradient in predictability within the CCS; SST forecast skill is highest off the Washington/Oregon coast and lowest off southern California, consistent with variable wind forcing being the dominant driver of SST predictability. These findings have direct implications for regional downscaling of seasonal forecasts and for short-term management of living marine resources.
•Global ecosystem model captures biome-scale carbon flows through plankton food web.•Quantitative, holistic global planktonic food web carbon budgets derived.•Respiration/remineralization highly ...distributed across the planktonic food web.•Muted cross-biome differences in mesozooplankton trophic level.•Step toward more quantitative planktonic food web predictions in changing climate.
Global-scale planktonic ecosystem models exhibit large differences in simulated net primary production (NPP) and assessment of planktonic food web fluxes beyond primary producers has been limited, diminishing confidence in carbon flux estimates from these models. In this study, a global ocean-ice-ecosystem model was assessed against a suite of observation-based planktonic food web flux estimates, many of which were not considered in previous modeling studies. The simulation successfully captured cross-biome differences and similarities in these fluxes after calibration of a limited number of highly uncertain yet influential parameters. The resulting comprehensive carbon budgets suggested that shortened food webs, elevated growth efficiencies, and tight consumer-resource coupling enable oceanic upwelling systems to support 45% of pelagic mesozooplankton production despite accounting for only 22% of ocean area and 34% of NPP. In seasonally stratified regions (42% of ocean area and 40% of NPP), weakened consumer-resource coupling tempers mesozooplankton production to 41% and enhances export below 100m to 48% of the global total. In oligotrophic systems (36% of ocean area and 26% of NPP), the dominance of small phytoplankton and low consumer growth efficiencies supported only 14% of mesozooplankton production and 17% of export globally. Bacterial production, in contrast, was maintained in nearly constant proportion to primary production across biomes through the compensating effects of increased partitioning of NPP to the microbial food web in oligotrophic ecosystems and increased bacterial growth efficiencies in more productive areas. Cross-biome differences in mesozooplankton trophic level were muted relative to those invoked by previous work such that significant differences in consumer growth efficiencies and the strength of consumer-resource coupling were needed to explain sharp cross-biome differences in mesozooplankton production. Lastly, simultaneous consideration of multiple flux constraints supports a highly distributed view of respiration across the planktonic food web rather than one dominated by heterotrophic bacteria. The solution herein is unlikely unique in its ability to explain observed cross-biome energy flow patterns and notable misfits remain. Resolution of existing uncertainties in observed biome-scale productivity and increasingly mechanistic physical and biological model components should yield significant refinements to estimates herein.
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