Funding Opportunities & Funded Projects

FY23 Research Opportunities

For both competitions, Science for the 21st Century Western U.S. Hydroclimate and Products for Areas of Climate Risk, and Projections for Societally-Relevant Problems

LOIs are due September 1, 2022 by 5pm and Full Proposals are due November 21, 2022 by 5pm.



   Search     
Enter Search Value:
- without any prefix or suffix to find all records where a column contains the value you enter, e.g. Net
- with | prefix to find all records where a column starts with the value you enter, e.g. |Network
- with | suffix to find all records where a column ends with the value you enter, e.g. Network|
- with | prefix and suffix to find all records containing the value you enter exactly, e.g. |Network|

Future Climate Impacts on the Pelagic and Coastal Fisheries of Hawai‘i

Hawai‘i has the sixth-largest commercial fish landings in the country, and the industry
is significant economically, socially, and culturally to the state. As the only oceanic state, many people rely on the ocean for their livelihood, from subsistence living to commercial enterprises. Hawaiian fisheries are comprised of two primary types: pelagic long-line fisheries and coastal/reef fisheries. How the health and productivity of fisheries evolve due to interannual-to-decadal variability and climate change is an existential question for this state. Over the past thirty years, the variability of extreme events has likely increased and will further increase in the future (prolonged marine heat waves, potentially stronger El Niño impacts, etc.); however, the climate itself has not yet significantly shifted. Two important questions related to climate change are: (i) how will interannual-to-decadal variability change over the coming decades; (ii) and, when will climate change emerge as the dominant signal? Each of these issues impact the pelagic and reef fisheries in different ways. The current pelagic longline fishery is located northeast of the islands within the subtropical gyre.

Over the next decades, the variability of the gyre (including prolonged heat waves, increased stratification, etc.) will be the primary stressor on the fishery, particularly at the lower trophic levels (leaving human fishing from discussion). However, as climate change emerges, the gyre is projected to expand poleward and eastward, making it likely that fishers move closer to California than Hawai‘i. For the reef fisheries, variability over the next decades may subject them to changes in ocean circulation, marine heat waves, oscillating from low to high nutrients, enhanced vertical mixing, etc. As climate change emerges at the reef, the primary stressors may include alteration of the mean circulation and water masses, increased acidification, and reduction in retained larvae. We propose to utilize a suite of Earth System Models (LENS and CMIP6) with a regional, coupled physical and biogeochemical
model (ROMS/COBALT) to identify the regional impacts of global variability and climate change. These models will be used to force both pelagic and coastal/reef fishery models to understand the physical and biogeochemical drivers that change the fishery (marine health, stock assessment, etc.) and to make projections for future planning and resilience.

This proposal is an end-to-end research-based approach to identify the role of interannual-to-decadal variability and climate change forcing on Hawaiian fisheries. It addresses the goal of CPO by advancing our scientific understanding, decision support research, and out- reach/education (including two Ph.D. students) of Earth’s climate system. Our state-of-the- art model hierarchy from planetary to coastal scale provides a unique toolset for the scientific community to evaluate regional variability and climate change in the context of climate scenarios. By utilizing two fishery models, we will broaden CPO’s success by quantitatively addressing the climate impacts on marine health, fishery productivity, and ultimately, the
sustainability and resiliency of the marine ecosystem for the critical fisheries of Hawai‘i.

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Brian Powell

Co-PI (s):Ryan Rykaczewski, Mariska Weijerman, Malte Stuecker, Tobias Friedrich

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

Improving the Utility of Global Climate Forecasts for Regional Fisheries Applications

Managers of fisheries and other living marine resources (LMRs) are tasked with balancing
environmental and economic interests, where the maintenance of productive industries (e.g.,
fishing and shipping) must be pursued while minimizing risks to protected species (e.g., from
bycatch and ship strikes) and ensuring that fish stocks are sustainable. To that end, forecasts of
ocean conditions in U.S. Large Marine Ecosystems (LMEs) have been identified as foundational
for emerging national efforts to increase the resilience of coastal communities. Forewarning of
ocean conditions can enable proactive decision making by fishers and fishery managers, and
incorporating climate information in fisheries management is a top priority of the NOAA National
Marine Fisheries Service [NOAA, 2015]. A key asset in this regard is the suite of subseasonal-to-
seasonal (2 week – 12 month) global climate forecasts run routinely at climate modeling centers
in the U.S. and elsewhere, which have demonstrable forecast skill for conditions over the North
American continent and in U.S. waters. However, uptake of these forecasts in LMR management
will require optimization for regional scales, and the MAPP program has identified a need to better
understand the processes underlying climate impacts on marine ecosystems and the associated
uncertainties. To address this need, we propose to quantify the dependence of forecast skill for
LMR-relevant variables in the California Current LME (CCLME) on the climate state and to
document mechanistic links between short-lead forecast skill (e.g., in the tropics) and longer-
lead forecast skill in the CCLME. In doing so, we will provide several valuable products: (i)
confidence assessments that document forecast uncertainty based on the climate state and (ii)
metrics that diagnose how well tropical-extratropical connections are captured in model forecasts
and inform CCLME forecast skill improvements. Key elements of the proposed work plan are to
(1) evaluate subseasonal-to-seasonal reforecasts from the S2S, SubX, and NMME archives for
ocean variables identified as highly impactful on LMR in the CCLME, (2) quantify hypothesized
relationships between short- and long-lead forecast skill, with the aim of using short-lead metrics
to diagnose whether forecasts are likely to be skillful at longer leads, and (3) compare skill
enhancements related to these new metrics with skill improvements enabled by dynamically
downscaled regional forecasts. The downscaled forecasts and the high-resolution regional ocean
reanalysis outputs needed for skill evaluation are available from prior projects.

Relevance to the Competition and NOAA’s Long-Term Climate Research Goals:
The proposed project directly addresses Priority Areas B and C of the competition. It addresses
Priority Area B by identifying key linkages between tropical conditions (and the broader basin-
scale climate) and forecast skill along the U.S. west coast, and between short-lead tropical forecast
skill and longer-lead U.S. west coast forecast skill for LMR-relevant physical variables. It
addresses Priority Area C by assessing model fidelity for predictability pathways, improving
prediction methodologies, and assessing the advantages of higher resolution. By enabling
improved forecasts of CCLME conditions and providing uncertainty estimates, which are crucial
to the implementation of climate-based management strategies, this project would also address
NOAA’s long-term goals for climate adaptation and mitigation and resilient coastal communities
and economies and NMFS National Climate Science Strategy objectives to track change and
provide early warning, project future conditions, and support adaptive management processes.

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Michael Jacox

Co-PI (s):Michael Alexander, Juliana Dias, Desiree Tommasi

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

Potential impacts of climate variability and change on the recent declines in coastal species along the U.S. Gulf and South Atlantic Bight

Coastal migratory pelagic species, such as king mackerel and greater amberjack, are key
commercial and recreational fishery species in the U.S. Gulf of Mexico (GoM) and South
Atlantic Bight (SAB) regions that support a billion-dollar economy (Karnauskas et al. 2013). The
most recent stock assessments for this suite of species indicated that recruitment of most stocks
began declining in the late 2000s, a signal indicative of either reduced population productivity,
migration out of the management area, or a combination of both factors (SEDAR, 2013; 2014a,
b, c). Concurrently, the upper ocean temperatures in the SAB and GoM have abruptly increased,
partly due to the increased westerly and trade wind system in the North Atlantic and the
associated upper ocean heat accumulation in the subtropical North Atlantic (e.g., Volkov et al.,
2019). Therefore, it is reasonable to hypothesize that the recent anomalous accumulation of the
upper ocean heat in the subtropical North Atlantic increased the stratification to suppress the
vertical entrainment of nutrients and biological productivity along the GoM and SAB, and thus
affecting productivity of prey populations for the coastal pelagic species. A competing
hypothesis is that a series of La Niña events that prevailed from late 2005 to early 2012
decreased the river discharges of freshwater and nutrients across the northern GoM and west
Florida coast to cause the decline of the coastal pelagic species in the GoM (e.g., Gomez et al.,
2019). The primary objective of this proposed research is to elucidate potential large-scale
climate drivers of plankton biomass and range shifts - and their combined influences - for a suite
of coastal pelagic species in the GoM and SAB. In order to achieve this objective, we will first
explore the link between the two key environmental drivers (i.e., upper ocean heat content and
river discharge) and the coastal pelagic stocks in the GoM and SAB, by analyzing available
fisheries and satellite data, ocean reanalysis products and a high-resolution regional ocean-
biogeochemical hindcast simulation. Then, we will explore large-scale climate processes that
influence the upper ocean heat content, river discharge and the associated nutrient availability
and plankton biomass in the GoM and SAB, by using a series of high-resolution regional ocean-
biogeochemical model experiments. Such climate processes include North Atlantic sea surface
height (SSH) tripole mode, El Niño - Southern Oscillation (ENSO), North Atlantic Oscillation
(NAO), Atlantic Multidecadal Oscillation (AMO) and Atlantic Meridional Overturning
Circulation (AMOC). Finally, we will use a suite of CMIP6 models and dynamic downscaling
simulations to explore the potential influence of anthropogenic global warming (AGW) on the
coastal pelagic stocks.

The proposed work contributes directly to NOAA CPO FY2020 MAPP funding
Competition-4 Modeling Climate Impacts on the Predictability of Fisheries and Other Living
Marine Resources, Type-1, Priority Area-A: The proposed work will identify key climate and
oceanic processes that affect ocean-biogeochemistry of relevance to the coastal pelagic species
assessed and managed by NMFS/SEFSC and the regional Fishery Management Councils in the
U.S. Gulf and South Atlantic Bight.

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Sang-Ki Lee, Mandy Karnauskas, Kevin Craig

Co-PI (s):Fabian Gomez

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

Incorporating fish in Earth system predictions

.Living marine resources (LMRs) are exquisitely sensitive to climate variability and change, displaying dramatic fluctuations on seasonal-to-decadal scales and significant vulnerability to anthropogenic warming, deoxygenation, and acidification trends. The ability to predict the response of fisheries to climate variations is essential to sound LMR management. Earth system models (ESMs) are an important tool in this context and have demonstrated predictive skill for physical and biogeochemical variables on seasonal to decadal time scales. ESM predictions have not directly simulated fish, however, thereby precluding a dynamical representation of feedbacks and nonlinear interactions. Our objective is to extend ESM predictions to include fish explicitly. We will couple an existing Fisheries Size and Functional Type model (FEISTY) to the MOM6 ocean general circulation model (OGCM), thereby enabling direct simulation and prediction of potential fish catch, fish distributions, and food web structure in the Geophysical Fluid Dynamics Laboratory (GFDL) and National Center for Atmospheric Research (NCAR) ESMs. Rationale. There is a compelling need for projections of future fisheries yields with accurate estimates of uncertainty; current projections suggest changes could be large, but uncertainties are also very large. Uncertainty arises from climate scenarios, internal climate variability, and structural differences in ESM frameworks. The recent adoption of NOAA’s MOM6 ocean model by the two major US modeling centers (NCAR and GFDL) provides an opportunity to accelerate research into large-scale fisheries responses to climate variability and change and the associated uncertainties. Summary of work. We will couple FEISTY to MOM6. We will evaluate and understand the dependencies and interactions between the higher trophic levels in FEISTY and the lower trophic levels (phytoplankton, zooplankton, etc.) represented in the underlying ocean biogeochemistry model. We will tune and optimize solutions, relying on empirical datasets constraining distributions of biogeochemical tracers and algal, zooplankton and fish biomass. Our ultimate scientific product will be analysis of global ocean-sea-ice hindcast integrations of MOM6 that include prognostic biogeochemistry and explicitly simulate spatiotemporal variability in potential fish catch, fish distributions, and food web structure—as well as interactions coupling higher trophic level dynamics explicitly down through nutrient and oxygen cycling. This project will open extensive possibilities for future work, including fully-coupled ESM predictions and regional simulations.
Broader impacts and relevance. The proposed work comprises an essential step in developing explicit representations of linkages connecting large-scale climate dynamics to ecosystems sustaining LMRs. This work will enable scientists and resource managers to leverage improving ESM predictions, inclusive of explicit higher-trophic level forecasts. Ultimately, this work builds towards a comprehensive framework for integrated ecosystem assessment, inclusive of uncertainties stemming from structural differences in models, internal climate variability, and differences in climate scenarios.

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Matthew Long, Colleen Petrik, Samantha Siedlecki

Co-PI (s):Gokhan Danabasoglu

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

Mechanisms of US West Coast Climate Variability and Change in Observations and Models

The US West Coast (USWC) hosts an extremely productive marine ecosystem and supports
important ecosystem services. The El Niño Southern Oscillation (ENSO) is known to influence
USWC upwelling through both atmospheric teleconnections and oceanic wave processes, but not
all El Niño events have a significant impact on USWC sea surface temperatures (SSTs).

Conversely, extreme SST conditions can occur in this region even without significant El Niño
warming in the tropical Pacific. Other modes of variability like the Pacific Decadal Oscillation
(PDO) and the North Pacific Gyre Oscillation (NPGO) modulate USWC conditions at decadal
timescales, but their interplay in USWC variability, and their roles in the development, evolution
and decay of extreme USWC conditions are not fully understood. Similarly, not much is known
about the influence of long-term climate change on USWC conditions. While the frequency and
severity of extreme warm conditions are generally projected to increase in a warming climate, the
exact mechanisms and characteristics of these extreme conditions have not yet been investigated.
To address the above gaps in knowledge, this project will: 1) Examine the leading dynamical
processes responsible for interannual/decadal temperature variations along the USWC and their
extreme expressions; 2) Assess the fidelity of the latest generation of climate models in simulating
USWC variability in general and extreme USWC conditions in particular, and how they are
influenced by larger-scale climate variability; and 3) Investigate how USWC variability and its
extremes will change in a warming climate.

We will use observational data sets in conjunction with oceanic and coupled reanalysis products
to identify the key dynamical processes underlying temperature variations along the USWC and
their extremes, and to provide a baseline for evaluating the fidelity of state-of-the-art climate
models in representing the full range of observed USWC conditions. The more realistic models in
this regard will then be used to examine how USWC conditions will change in the future. The
above questions will be addressed using a broad set of diagnostic approaches, ranging from heat-
budget analysis for process understanding to multivariate regressions and Linear Inverse Modeling
methodologies.

The proposed project directly addresses Priority Area A of the solicitation in seeking to “identify
key climate/oceanic processes that affect ocean biogeochemistry of relevance to fisheries and
other living marine resources” along the USWC, a region of great value for NMFS. The careful
inter-comparisons of models and observations performed in this project will provide an assessment
of the models’ ability to realistically simulate climate variability along the USWC for the right
reasons, and will thus also closely align with Priority Areas B and C.

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Antonietta Capotondi

Co-PI (s):Prashant D. Sardeshmukh

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

The role of biogeochemical processes in controlling LMR-relevant properties in an Eastern Bering Sea climate-to-fish modeling framework

This project aims to better constrain uncertainty related to local biogeochemistry when down-scaling climate model output to predict changes in primary and secondary production of the Eastern Bering Sea (EBS). Due to its economic and cultural importance, changes in the EBS ecosystem have prompted a series of contemporary research efforts to advance our understanding of key ecosystem processes, their relationship to the physical environment, and their probable response to future changes in the global climate. Central to these research efforts has been the development of a dynamical downscaling framework to connect drivers from global Earth System Models (ESMs) to an ensemble of ecosystem models in the EBS via a10-km horizontal resolution Regional Ocean Modeling System domain (Bering10K ROMS). To provide credible Living Marine Resource (LMR) predictions, a model must capture not only the physical dynamics of a system, but also local biogeochemical processes; these processes
are poorly constrained by data but exert tight controls over the simulated levels of primary and
secondary production.

To better quantify the biophysical linkages within this Bering Sea modeling framework, and the sensitivity of regional climate projections to the assumptions inherent within the bio-geochemical module, we propose to conduct a biogeochemical model intercomparison for the Bering Sea. Our model intercomparison will couple four existing biogeochemical models, all with contrasting but equally justifiable representations of the lower trophic level dynamics of the Bering Sea, to an identical hydrodynamic model forced with historical atmospheric and lateral ocean boundary conditions. This approach will allow us to better quantify the inter-model uncertainty range, and isolate uncertainty that can be attributed to biogeochemical model structure and parameterization as opposed to variations in ocean model hydrodynamics and forcing. By analyzing which physical drivers elicit a consistent response across model frameworks, versus those whose effect on LMR-relevant metrics are variable, we can better identify which physical drivers lead to outcomes that are robust to biogeochemical uncertainty. Our proposed research specifically addresses focus areas A and C in Competition 4, namely, to identify key climate/oceanic processes that affect ocean biogeochemistry of relevance to fisheries and other LMRs, and to improve modeling of climate-ocean predictability pathways. It will allow explicit quantification of variability associated with an often-overlooked aspect of climate-to-fish modeling: the lower trophic level biogeochemical models that "translate" climate drivers into LMR-relevant indices. We believe this work will lead to more reliable predictions within the Bering Sea modeling framework, which has and continues to support a variety of research projects to predict climate effects on socio-ecological components of the
Bering Sea ecosystem. In a larger context, it will inform similar applications using regional
downscaling of climate models to predict changes in living marine resources. Ultimately this
work promotes climate-resilient fisheries and coastal communities in the Bering Sea through
integrated climate-informed decision making and ecosystem-based fisheries management. As
such, it is aligned with MAPP’s focus on "coupling, integration, and application of Earth System models and analyses across NOAA", and NOAA’s long term goals of providing service to climate adaptation and mitigation, healthy oceans, and resilient coastal communities and Economies.

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Albert Hermann

Co-PI (s):Kelly Kearney, Wei Cheng, Darren Pilcher, Kerim Aydin

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

Towards the prediction of fisheries on seasonal to multi-annual time scales

Global climate change is disrupting the species composition and food web structure of marine ecosystems. These impacts are driven by variability in ocean conditions that affect the productivity and distribution of marine organisms. Ecosystem based fisheries management can help reduce repercussions and promote resilience in the face of changing ocean conditions. 

Rationale: Coupled global Earth System Models (ESMs) have demonstrated sNill in predicting physical and biological variables important to fish and fisheries on seasonal to decadal time scales of significance to management (ParN et al. 2019, Tommasi et al. 2017, Yeager et al. 2018). This potential has only recently been recognized and documented and is thus underutilized for management activities. Our objective is to more deeply examine the variability, uncertainty, and source of predictability of these environmental drivers, and the sensitivity of fisheries to them. These analyses will provide a broader understanding of the physical and biogeochemical (BGC) processes necessary for robust fisheries projections. 

Proposed Work: The overarching task is to incorporate an offline fish model with the results of ESMs run in initialized prediction mode to generate and assess model predictions. The work to be completed includes simulating large ensembles of seasonal to decadal scale predictions of the physical and BGC variables of relevance to fish, which will then be used to force a mechanistic fish model, FEISTY (PetriN et al. 2019). FEISTY was built to be coupled with ESMs and is able to simulate the regional variability in fish catches that spans four orders of magnitude. We will force FEISTY offline with output from NCARГs CESM Decadal Prediction Large Ensemble (CESMYDPLE) and GFDLГs CM2.1 prediction experiments (Yeager et al. 2018, ParN et al. 2019). We will utilize the decadal and seasonalYtoYannual integrations that have already been completed with these two models, respectively. Analyses will I) estimate the amount of fisheries production variance explained by different physical and BGC drivers, II) estimate the spatiotemporal variability in the predictability of the most important physical and BGC drivers, III) examine the spatiotemporal variability in the predictability of fisheries, and IV) maNe comparisons between CESM and ESM2M COBALT. The ensemble approach allows for quantification of the uncertainties that arise from different climate, ocean, and BCG models. Additionally, the results of these offline ESM FEISTY simulations will provide a baseline for the predictions made with an online version to be developed under a separate proposal (PI M. Long, Incorporating fish in Earth system predictions). 

Broader Impacts and Competition Relevance: The proposed worN will address Priority Area C: Improve the modeling of climate ocean predictability pathways and its representation in prediction/projection systems. There is a strong management need for projections of future fisheries yields with accurate estimates of uncertainty. This worN provides an opportunity to accelerate research into large scale fisheries responses to climate change and the associated uncertainties. Our research will improve the modeling and understanding of climate related physical pathways that drive biogeochemical variability in U.S. marine ecosystems and their impacts on living marine resources. Ultimately, this linkage between a fish model and ESMs is an essential step in developing a comprehensive frameworK for integrated ecosystem assessment. 

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Colleen Petrik

Co-PI (s):Samantha Siedlecki, Matthew Long, Charles Stock, Stephen Yeager

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

Validation of regional ocean model hindcasts for zooplankton biomass via comparisons with thirty years of field sampling data in a rapidly changing ecosystem

The eastern Bering Sea (EBS) is one of the most productive ecosystems on the planet and
produces the largest fish catch by volume in the United States. The EBS is currently
undergoing rapid ecological change, having experienced record-low seasonal sea-ice in the
past two years. To effectively manage fisheries in the face of rapid change, predicting the
response of the ecosystem to this forcing is imperative and requires the application of
modeling. The Regional Ocean Model System (ROMS) is widely used in the EBS, North
Pacific, and nationwide to conduct forecasts and hindcasts of ocean physics. In the EBS, the
10km resolution ROMS-NPZ model (Bering10K) includes multiple functional groups for
primary and secondary producers; however, there has been relatively little work validating
these components of the model. We propose to compare spatial and temporal patterns in
Bering10K predictions of secondary producers with field-sampling records of spatial and
temporal variation. In particular, field observations of zooplankton community have not
been compared to model output. A rich time series of data on zooplankton abundance,
collected with OAR, NMFS, and NOS support are available for this comparison. The lack of
comparison is critical in that zooplankton link changes in primary production to fish
through interactions, beginning with the first year of life. Survival of juvenile fish through
their first winter relates strongly to eventual recruitment and zooplankton availability
plays a key role; zooplankton remain key diet components of many commercially and
ecologically important species after recruitment to the fishery. This lack of model to
observational comparisons also makes it difficult to assess whether Bering10K hindcasts
and forecasts of secondary producers capture observed spatial and temporal variability,
and therefore provide credible estimates in locations and times without field data. This
uncertainty then makes it impractical to use the Bering10K model to inform the short-term
(1-5 year) forecasts/hindcasts of fish distribution that are currently used in the Alaska
pollock stock assessment and to develop adaptive sampling designs for fisheries (cod,
pollock) and protected species (e.g., subarctic cetaceans, including the critically
endangered N. Pacific right whale). This proposal aims to evaluate the Bering 10K output
by comparison to field observations of the zooplankton community. This comparison will
be evaluated using several statistical approaches and will identify areas for model
improvement. Furthermore, we will use the comparisons to test short time-scale scenarios
designed to simulate recent warming trends. The overall outcome of this research will be to
advance the capability of Bering 10K to predict zooplankton biomass, providing vital
ecosystem information that can be used to estimate fisheries production in a rapidly changing
Bering Sea.

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): David Kimmel

Co-PI (s):James T. Thorson, Darren J. Pilcher, Kelly Kearney, Patrick Ressler

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

Impact of climate variability on bottom water biogeochemistry in the context of demersal fisheries of the Northwest Atlantic shelf

The northwest Atlantic supports a number of important fisheries and is also the location
of rapid changes in physical and biogeochemical environment driven by warming
waters and increased atmospheric CO2. The region is highly susceptible to future ocean
acidification (OA) both ecologically and economically because of naturally low pH waters and many economic sectors of the US Northeast rely on potentially sensitive marine shellfish. These
past and potential future changes have been identified in surface waters using satellite products and underway observations, but because subsurface data has been limited until more recently, little is known about how bottom water carbonate chemistry has changed, and may change in the future. Although there has been significant investment in expanding regular monitoring of the region’s bottom water biogeochemistry, limitations in existing datasets make it difficult to evaluate the impact of specific processes such as OA on economically important species. Our proposed study will address these limitations using a data and model driven approach to develop a historical time series of bottom water carbonate chemistry at a spatial resolution that is relevant for the evaluation and management of economically important demersal fisheries in the northwest Atlantic. Summary of work: To address this goal, we will compile historical monitoring data focusing specifically on carbonate chemistry from publicly available databases that will allow us to leverage ongoing sampling programs such as the NOAA EcoMon and ECOA programs, OOI service cruises, and NES-LTER cruises. Using historical data, ocean reanalysis products, and machine learning tools, we will develop high-resolution historical bottom water carbonate chemistry fields for the U.S. Large Marine Ecosystems Northeast region (NELME) region at a horizontal resolution of 1/12 of a degree. We will complete a detailed comparison of observational bottom water biogeochemical data to the historical runs of global climate models from the CMIP5 database that will allow us to develop downscaled historical and future projections from the CMIP5 model ensemble, comparing a business-as-usual (RCP8.5) to a climate policy scenario (RCP4.5). Finally, we will explore spatial variability in bottom water carbonate chemistry to determine how the subsurface carbonate system responds to modes of climate variability.

Broader Impacts and relevance: This project addresses priority areas A and C of the RFP. In
addressing priority A, we will determine the relationship between key climate processes and
spatial and temporal variations in bottom water carbonate chemistry. Subsurface measurements
of carbonate chemistry have been recently identified as a significant monitoring gap limiting our
understanding of acidification on the NOAA LME 7 (NELME). This project leverages recent
investments in adding carbonate system measurements to regular cruises (OOI, NES-LTER,
NOAA EcoMon and ECOA) to expand our understanding of climate processes on bottom water
biogeochemical indicators. This project will also address priority C of the RFP by synthesizing
observations and output from state-of-the-art climate models using machine learning to produce
bottom water biogeochemical fields at a spatial resolution that is relevant for the management of
economically important demersal fisheries in the NELME. The results from this project will determine if the low resolution, 1 degree models with data assimilation using machine learning
will provide bottom water fields that can inform fisheries management decisions. Furthermore,
the relationships developed between key climate indices and spatial variability in carbonate
chemistry will be helpful in developing seasonal forecasting models to aid in fisheries management decisions.

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Jennie Rheuban

Co-PI (s):Ivan Lima, Zhaohui Aleck Wang

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

The predictability of oxygen and its metabolic consequences for fisheries on decadal time scales

Earth system models (ESMs) project ocean conditions that are relevant to marine fisheries; over the next several decades, the ocean will warm, oxygen content will decline, and regions with low oxygen concentrations will expand. Critically, however, these trends are not spatially uniform and certain regions will experience more rapid change than others (Bopp et al. 2013). Temperature and oxygen availability jointly limit habitat viability, but are difficult to disentangle few predictive studies incorporate this information in developing projections of impacts on living marine resources (LMRs). 

A Ney physiologically mechanistic framework , the Metabolic Index (Φ, Deutsch et al. 2015) was recently developed that explicitly combines the joint influence of oxygen content in the ocean with the temperature dependent metabolic demands for a given organism. When Φ = 1, the resting metabolic demands of an organism are exactly matched by the available oxygen supply.It is possible to identify critical threshold, Φcrit, a physiological energetic barrier for a particular species which likely drives habitat. When Φ <Φcrit, the environment can no longer support the aerobic demands of species’ energetic requirements. Investigation of the synergistic effects of temperature and oxygen on driving physiological vulnerability of organisms within valuable fisheries is now possible with this index. 
Global ESMs have demonstrated sNill in predicting physical and biological variables important to fish and fisheries on seasonal to decadal time scales of significance to management (Tommasi et al. 2016, ParN et al. 2019). We propose to assess an existing forecast system’s ability to forecast metabolic indices in the global ocean on decadal timescales. Our objective is to examine the predictability of fisheries relevant environmental variables beyond sea surface temperature and chlorophyll, such as oxygen and related metabolic metrics, as well as potential limitations on fisheries that this metabolic index projects. 

Our hypothesis is that demands on metabolic rates due to rising temperatures and accompanied declines in dissolved O2, will restrict overall fishing potential by limiting biomass and that the metrics (Metabolic Index, potential catch) needed to forecast such restrictions are predictable on decadal timescales using an existing suite tools. The proposed program would analyze results from an existing suite of decadalYscale forecasts from the CESM Decadal Prediction Large Ensemble (CESMYDPLE; Yeager et al. 2018). Analyses will focus on establishing the predictability of environmental variables relevant to fish metabolic processes, including: temperature, plankton biomasses, oxygen, and Φ for representative taxa in each of the Large Marine Ecosystems of interest: Eastern Bering Sea, California Current, NE Atlantic Shelf, SE Atlantic Shelf, Gulf of Mexico, and Pacific Islands. 

The proposed worN meets the primary MAPP Program objectives of: 1) improving ESMs by adding the effects of oxygen concentrations on higher trophic levels; and 4) developing integrated assessment and prediction capabilities relevant to decision makers by analyzing the predictability of environmental variables and processes of consequence to fisheries and directly analyzing the predictability of higher trophic levels. This research will improve the modeling and understanding of climate related physical pathways that drive biogeochemical variability in U.S. LMEs. Proposed worN will address MAPP Priority Areas B. and C. 

Climate Risk Area: Marine Ecosystems

Principal Investigator (s): Samantha Siedlecki, Colleen Petrik, Matthew Long

Co-PI (s):Vincent Saba

Task Force: Marine Ecosystem Task Force

Year Initially Funded:2020

Competition: Modeling Climate Impacts on the Predictability of Fisheries and Other Living Marine Resources

Final Report:

Page 4  of  25 First   Previous   1  2  3  [4]  5  6  7  8  9  10  Next   Last  


MAPP


Follow us

Contact

Dr. Annarita Mariotti
MAPP Program Director, on detail to EOP/OSTP
P: 301-734-1237
E:

Dr. Daniel Barrie
Acting MAPP Program Director
P: 301-734-1256
E:

Courtney Byrd
MAPP Program Specialist
P: 301-734-1257
E:

«August 2022»
MonTueWedThuFriSatSun
25262728293031
1234567
891011121314
15161718192021
22232425262728
2930311234

ABOUT US

Americans’ health, security and economic wellbeing are tied to climate and weather. Every day, we see communities grappling with environmental challenges due to unusual or extreme events related to climate and weather. 

CPO HEADQUARTERS

1315 East-West Highway Suite 100
Silver Spring, MD 20910