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Aquatic ecologists are integrating mixotrophic plankton – here defined as microorganisms with photosynthetic and phagotrophic capacity – into their understanding of marine food webs and biogeochemical cycles. Understanding mixotroph temporal and spatial distributions, as well as the environmental conditions under which they flourish, is imperative to understanding their impact on trophic transfer and biogeochemical cycling. Mixotrophs are hypothesized to outcompete strict photoautotrophs and heterotrophs when either light or nutrients are limiting, but testing this hypothesis has been hindered by the challenge of identifying and quantifying mixotrophs in the field. Using field observations from a multi-decadal northern North Atlantic dataset, we calculated the proportion of organisms that are considered mixotrophs within individual microplankton samples. We also calculated a “trophic index” that represents the relative proportions of photoautotrophs (phytoplankton), mixotrophs, and heterotrophs (microzooplankton) in each sample. We found that the proportion of mixotrophs was positively correlated with temperature, and negatively with either light or inorganic nutrient concentration. This proportion was highest during summertime thermal stratification and nutrient limitation, and lowest during the North Atlantic spring bloom period. Between 1958 and 2015, changes in the proportion of mixotrophs coincided with changes in the Atlantic Multi-decadal Oscillation (AMO), was highest when the AMO was positive, and showed a significant uninterrupted increase in offshore regions from 1992-2015. This study provides an empirical foundation for future experimental, time series, and modeling studies of aquatic mixotrophs.

 

The oceanography of the Gulf of Maine has recently changed in ways that have not been seen previously, but that are likely to be more common in the future. Because of the rapid rate of change, some view the Gulf of Maine as a window into the ocean’s future with the idea that lessons learned can be applied in places that have yet to experience similar rapid changes. Based on a formal statistical definition of oceanographic surprises, the frequency of surprises in the Gulf of Maine is higher and has increased faster than ex- pected even given underlying trends. The analysis suggests that we should expect new kinds of surprises that are characteristically different from previ- ous ones. The implication for policymaking is that in addition to considering long-term environmental changes, it is important to consider scenarios of sudden, unexpected, and potentially extreme environmental changes. 

Abstract Predicting the impact of marine ecosystem warming on the timing and magnitude of phytoplankton production is challenging. For example, warming can advance the progression of stratification thereby changing the availability of nutrients to surface phytoplankton, or influence the surface mixed layer depth, thus affecting light availability. Here, we use a time series of sea surface temperature (SST) and chlorophyll remote sensing products to characterize the response of the phytoplankton community to increased temperature in the Northeast US Shelf Ecosystem. The rate of change in SST was higher in the summer than in winter in all ecoregions resulting in little change in the timing and magnitude of the spring thermal transition compared to a significant change in the autumn transition. Along with little phenological shift in spring thermal conditions, there was also no evidence of a change in spring bloom timing and duration. However, we observed a change in autumn bloom timing in the Georges Bank ecoregion, where bloom initiation has shifted from late September to late October between 1998 and 2020—on average 33 d later. Bloom duration in this ecoregion also shortened from ∼7.5 to 5 weeks. The shortened autumn bloom may be caused by later overturn in stratification known to initiate autumn blooms in the region, whereas the timing of light limitation at the end of the bloom remains unchanged.  These changes in bloom timing and duration appear to be related to the change in autumn thermal conditions and the significant shift in autumn thermal transition. These results suggest that the spring bloom phenology in this temperate continental shelf ecosystem may be more resilient to thermal climate change effects than blooms occurring in other times of the year. 

Ocean ecosystems are changing, and the climate envelope paradigm predicts a steady shift, approximately poleward, of species ranges. The Gulf of Maine presents a test case of this paradigm, as temperatures have warmed extremely rapidly. Some species have shifted northeastward, matching predictions. Others—namely harmful algal species like Pseudo-nitzschia australis and Karenia mikimotoi—do not appear to have followed climate trajectories, arriving as surprises in the Gulf of Maine. Rare-biosphere dynamics offer one possible ecological lens for understanding and predicting this type of surprise. Rare species in the plankton, possibly more so than southerly ones, may provide management challenges in the future. Improved monitoring and broader coordination of monitoring of the rare biosphere could help develop early warning systems for harmful and toxic algae. A better theoretical understanding of rare biosphere dynamics is also needed. A challenge for the next cohort of ecosystem projections is to predict the newly emerging harmful species of the type that catch us by surprise. 

The Gulf of Maine North Atlantic Time Series (GNATS) has been run since 1998, across the Gulf of Maine (GoM), between Maine and Nova Scotia. GNATS goals are to provide ocean color satellite validation and to examine change in this coastal ecosystem. We have sampled hydrographical, biological, chemical, biogeochemical, and bio‐optical variables. After 2008, warm water intrusions (likely North Atlantic Slope Water [NASW]) were observed in the eastern GoM at 50–180 m depths. Shallow waters (<50 m) significantly warmed in winter, summer, and fall butcooledduring spring. Surface salinity and density of the GoM also significantly increased over the 20 years. Phytoplankton standing stock and primary production showed highly‐significant decreases during the period. Concentrations of phosphate increased, silicate decreased, residual nitrate [N*; nitrate‐silicate] increased, and the ratio of dissolved inorganic nitrogen:phosphate decreased, suggesting increasing nitrogen limitation. Dissolved organic carbon (DOC) and its optical indices generally increased over two decades, suggesting changes to the DOC cycle. Surface seawater carbonate chemistry showed winter periods where the aragonite saturation (Ω_ar) dropped below 1.6 gulf‐wide due to upward winter mixing of cool, corrosive water. However, associated with increased average GoM temperatures, Ω_arhas significantly increased. These results reinforce the hypothesis that the observed decrease in surface GoM primary production resulted from a switch from Labrador Sea Water to NASW entering the GoM. A multifactor analysis shows that decreasing GoM primary production is most significantly correlated to decreases in chlorophyll and particulate organic carbon plus increases in N* and temperature.

 

Ecological forecasting provides a powerful set of methods for predicting short‐ and long‐term change in living systems. Forecasts are now widely produced, enabling proactive management for many applied ecological problems. However, despite numerous calls for an increased emphasis on prediction in ecology, the potential for forecasting to accelerate ecological theory development remains underrealized.

Here, we provide a conceptual framework describing how ecological forecasts can energize and advance ecological theory. We emphasize the many opportunities for future progress in this area through increased forecast development, comparison and synthesis.

Our framework describes how a forecasting approach can shed new light on existing ecological theories while also allowing researchers to address novel questions. Through rigorous and repeated testing of hypotheses, forecasting can help to refine theories and understand their generality across systems. Meanwhile, synthesizing across forecasts allows for the development of novel theory about the relative predictability of ecological variables across forecast horizons and scales.

We envision a future where forecasting is integrated as part of the toolset used in fundamental ecology. By outlining the relevance of forecasting methods to ecological theory, we aim to decrease barriers to entry and broaden the community of researchers using forecasting for fundamental ecological insight.