CAFA Publications

Author(s): Thorson, J. T., W. Cheng, A. J. Hermann, J. N. Ianelli, M. A. Litzow, C. A. O’Leary, G. G. Thompson.

Project PI: Hollowed
DOI: http://doi.org/10.1111/gcb.15149

Ecologists and oceanographers inform population and ecosystem management by identifying the physical drivers of ecological dynamics. However, different research communities use different analytical tools where, for example, physical oceanographers often apply rank-reduction techniques (a.k.a. empirical orthogonal functions [EOF]) to identify indicators that represent dominant modes of physical variability, whereas population ecologists use dynamical models that incorporate physical indicators as covariates. Simultaneously modeling physical and biological processes would have several benefits, including improved communication across sub-fields; more efficient use of limited data; and the ability to compare importance of physical and biological drivers for population dynamics. Here, we develop a new statistical technique, EOF regression, which jointly models population-scale dynamics and spatially distributed physical dynamics. EOF regression is fitted using maximum-likelihood techniques and applies a generalized EOF analysis to environmental measurements, estimates one or more time series representing modes of environmental variability, and simultaneously estimates the association of this time series with biological measurements. By doing so, it identifies a spatial map of environmental conditions that are best correlated with annual variability in the biological process. We demonstrate this method using a linear (Ricker) model for early-life survival (“recruitment”) of three groundfish species in the eastern Bering Sea from 1982 to 2016, combined with measurements and end-of-century projections for bottom and sea surface temperature. Results suggest that (a) we can forecast biological dynamics while applying delta-correction and statistical downscaling to calibrate measurements and projected physical variables, (b) physical drivers are statistically significant for Pacific cod and walleye pollock recruitment, (c) separately analyzing physical and biological variables fails to identify the significant association for walleye pollock, and (d) cod and pollock will likely have reduced recruitment given forecasted temperatures over future decades.

Author(s): Kang, D., and E.N. Curchitser

Project PI: Curchister
DOI: https://doi.org/10.1175/JPO-D-14-0200.1

A detailed energetics analysis of the Gulf Stream (GS) and associated eddies is performed using a highresolution multidecadal regional ocean model simulation. The energy equations for the time-mean and timevarying flows are derived as a theoretical framework for the analysis. The eddy–mean flow energy components and their conversions show complex spatial distributions. In the along-coast region, the cross-stream and cross-bump variations are seen in the eddy–mean flow energy conversions, whereas in the off-coast region, a mixed positive–negative conversion pattern is observed. The local variations of the eddy–mean flow interaction are influenced by the varying bottom topography. When considering the domain-averaged energetics, the eddy–mean flow interaction shows significant along-stream variability. Upstream of Cape Hatteras, the energy is mainly transferred from the mean flow to the eddy field through barotropic and baroclinic instabilities. Upon separating from the coast, the GS becomes highly unstable and both energy conversions intensify. When the GS flows into the off-coast region, an inverse conversion from the eddy field to the mean flow dominates the power transfer. For the entire GS region, the mean current is intrinsically unstable and transfers 28.26 GW of kinetic energy and 26.80 GW of available potential energy to the eddy field. The mesoscale eddy kinetic energy is generated by mixed barotropic and baroclinic instabilities, contributing 28.26 and 9.15 GW, respectively. Beyond directly supplying the barotropic pathway, mean kinetic energy also provides 11.55 GW of power to mean available potential energy and subsequently facilitates the baroclinic instability pathway.

Author(s): Reum, J., J. L. Blanchard, K. K. Holsman, K. Aydin, A. B. Hollowed, A. Hermann, W. Cheng, A. Faig, A. Haynie, A. E. Punt.

Project PI: Hollowed
DOI: http://doi.org/10.3389/fmars.2020.00124

Characterization of uncertainty (variance) in ecosystem projections under climate change is still rare despite its importance for informing decision-making and prioritizing research. We developed an ensemble modeling framework to evaluate the relative importance of different uncertainty sources for food web projections of the eastern Bering Sea (EBS). Specifically, dynamically downscaled projections from Earth System Models (ESM) under different greenhouse gas emission scenarios (GHG) were used to force a multispecies size spectrum model (MSSM) of the EBS food web. In addition to ESM and GHG uncertainty, we incorporated uncertainty from different plausible fisheries management scenarios reflecting shifts in the total allowable catch of flatfish and gadids and different assumptions regarding temperature-dependencies on biological rates in the MSSM. Relative to historical averages (1994–2014), end-of-century (2080–2100 average) ensemble projections of community spawner stock biomass, catches, and mean body size (±standard deviation) decreased by 36% (±21%), 61% (±27%), and 38% (±25%), respectively. Long-term trends were, on average, also negative for the majority of species, but the level of trend consistency between ensemble projections was low for most species. Projection uncertainty for model outputs from ∼2020 to 2040 was driven by inter-annual climate variability for 85% of species and the community as a whole. Thereafter, structural uncertainty (different ESMs, temperature-dependency assumptions) dominated projection uncertainty. Fishery management and GHG emissions scenarios contributed little (<10%) to projection uncertainty, with the exception of catches for a subset of flatfishes which were dominated by fishery management scenarios. Long-term outcomes were improved in most cases under a moderate “mitigation” relative to a high “business-as-usual” GHG emissions scenario and we show how inclusion of temperature-dependencies on processes related to body growth and intrinsic (non-predation) natural mortality can strongly influence projections in potentially non-additive ways. Narrowing the spread of long-term projections in future ensemble simulations will depend primarily on whether the set of ESMs and food web models considered behave more or less similarly to one another relative to the present models sets. Further model skill assessment and data integration are needed to aid in the reduction and quantification of uncertainties if we are to advance predictive ecology.

Author(s): Punt, André E., M. G. Dalton, W. Cheng, A. J.Hermann, K. K.Holsman, T. P. Hurst, J. N.Ianelli, K. A. Kearney, C. R.McGilliard, D. J.Pilcher, M. Véron.

Project PI: Hollowed
DOI: http://doi.org/10.1016/j.dsr2.2021.104951

Climate-enhanced stock assessment models represent potentially vital tools for managing living marine resources under climate change. We present a climate-enhanced stock assessment where environmental variables are integrated within a population dynamics model assessment of biomass, fishing mortality and recruitment that also accounts for process error in demographic parameters. Probability distributions for the impact of the associated environmental factors on recruitment and growth can either be obtained from Bayesian analyses that involve fitting the population dynamics model to the available data or from auxiliary analyses. The results of the assessment form the basis for the calculation of biological and economic target and limit reference points, and projections under alternative harvest strategies. The approach is applied to northern rock sole (Lepidopsetta polyxystra), an important component of the flatfish fisheries in the Eastern Bering Sea. The assessment involves fitting to data on catches, a survey index of abundance, fishery and survey age-compositions and survey weight-at-age, with the relationship between recruitment and cold pool extent and that between growth increment in weight and temperature integrated into the assessment. The projections also allow for an impact of ocean pH on expected recruitment based on auxiliary analyses. Several alternative models are explored to assess the consequences of different ways to model environmental impacts on population demography. The estimates of historical biomass, recruitment and fishing mortality for northern rock sole are not markedly impacted by including climate and environmental factors, but estimates of target and limit reference points are sensitive to whether and how environmental variables are included in stock assessments and projections.

Author(s): Brodie, S, et al

Project PI: Jacox
DOI: https://doi.org/10.1111/ecog.05504

Accurate forecasts of how animals respond to climate-driven environmental change are needed to prepare for future redistributions, however, it is unclear which temporal scales of environmental variability give rise to predictability of species distributions. We examined the temporal scales of environmental variability that best predicted spatial abundance of a marine predator, swordfish Xiphias gladius, in the California Current. To understand which temporal scales of environmental variability provide biological predictability, we decomposed physical variables into three components: a monthly climatology (long-term average), a low frequency component representing interannual variability, and a high frequency (sub-annual) component that captures ephemeral features. We then assessed each component's contribution to predictive skill for spatially-explicit swordfish catch. The monthly climatology was the primary source of predictability in swordfish spatial catch, reflecting the spatial distribution associated with seasonal movements in this region. Importantly, we found that the low frequency component (capturing interannual variability) provided significant skill in predicting anomalous swordfish distribution and catch, which the monthly climatology cannot. The addition of the high frequency component added only minor improvement in predictability. By examining models' ability to predict species distribution anomalies, we assess the models in a way that is consistent with the goal of distribution forecasts – to predict deviations of species distributions from their average historical locations. The critical importance of low frequency climate variability in describing anomalous swordfish distributions and catch matches the target timescales of physical climate forecasts, suggesting potential for skillful ecological forecasts of swordfish distributions across short (seasonal) and long (climate) timescales. Understanding sources of prediction skill for species environmental responses gives confidence in our ability to accurately predict species distributions and abundance, and to know which responses are likely less predictable, under future climate change. This is important as climate change continues to cause an unprecedented redistribution of life on Earth.

Author(s): Essington, T. E., M. E. Matta, B. A. Black, T. E. Helser, P. D. Spencer.

Project PI: Hollowed
DOI: http://doi.org/10.1139/cjfas-2021-0046

Identifying changes in fish growth is important for accurate scientific advice used for fisheries management, because environmental change is affecting fish growth and size-at-age is a critical component of contemporary stock assessment methods. Growth-increment biochronologies are time series of growth-increments derived from hard parts of marine organisms that may reveal dynamics of somatic fish growth. Here we use time series of otolith increments of two fish stocks to fit and compare a biologically derived growth model and a generalized statistical model. Both models produced similar trajectories of annual growth trends, but the biologically based one was more precise and predicted smaller interannual fluctuations than the statistical model. The biologically based model strongly indicated covariance between anabolic and catabolic rates among individuals. Otolith size-at-age did not closely match fish length-at-age, and consequently the growth model could not accurately hindcast observed fish length-at-age. For these reasons, fitted growth dynamics from otolith biochronologies may best suited to identify growth rate fluctuations, understand past drivers of growth dynamics, and improve ecological forecast in the face of rapid environmental change.

Author(s): Thorson, J. T., M. L. Arimitsu, L. A. K. Barnett, W. Cheng, L. B. Eisner, A.C. Haynie, A. J. Hermann, K. Holsman, D. G. Kimmel, M. W. Lomas, J. Richar. E. C. Siddon.

Project PI: Hollowed
DOI: http://doi.org/10.1111/ecog.05471

Ecosystems are increasingly impacted by human activities, altering linkages among physical and biological components. Spatial community reassembly occurs when these human impacts modify the spatial overlap between system components, and there is need for practical tools to forecast spatial community reassembly at landscape scales using monitoring data. To illustrate a new approach, we extend a generalization of empirical orthogonal function (EOF) analysis, which involves a spatio-temporal ecosystem model that approximates coupled physical, biological and human dynamics. We then demonstrate its application to five trophic levels for the eastern Bering Sea by fitting to multiple, spatially unbalanced datasets measuring physical characteristics (temperature measurements and climate-linked forecasts), primary producers (spring and fall size-fractionated chlorophyll-a), secondary producers (copepods), juveniles (age-0 walleye pollock), adult consumers (five commercially important fishes), human activities (seasonal fishing effort) and mobile predators (seabirds). We identify the spatial niche for each ecosystem component, as well as dominant modes of variability that are highly correlated with a known bottom–up driver of dynamics. We then measure spatial overlap between interacting variables (using Schoener's-D) and identify that age-0 pollock have decreased spatial overlap with copepods and increased overlap with adult pollock during warm years, and also that adult pollock have increased overlap with arrowtooth flounder and decreased overlap with catcher–processor fishing effort during these warm years. Given the warming conditions that are projected for the coming decade, the model forecasts increased prey and competitor overlap involving adult pollock (between age-0 pollock, adult pollock and arrowtooth flounder) and decreased overlap with the copepod forage base and with the catcher–processor fishery during future warming. We recommend that joint species distribution models be extended to incorporate ‘ecological teleconnections' (correlations between distant locations arising from known mechanisms) arising from behavioral adaptation by mobile animals as well as passive advection of nutrients and planktonic juvenile stages.

Author(s): J. Schmidt, S. Bograd, H. Arrizabalaga, et al.

Project PI: Jacox
DOI: https://doi.org/10.3389/fmars.2019.00550

Advances in ocean observing technologies and modeling provide the capacity to revolutionize the management of living marine resources. While traditional fisheries management approaches like single-species stock assessments are still common, a global effort is underway to adopt ecosystem-based fisheries management (EBFM) approaches. These approaches consider changes in the physical environment and interactions between ecosystem elements, including human uses, holistically. For example, integrated ecosystem assessments aim to synthesize a suite of observations (physical, biological, socioeconomic) and modeling platforms [ocean circulation models, ecological models, short-term forecasts, management strategy evaluations (MSEs)] to assess the current status and recent and future trends of ecosystem components. This information provides guidance for better management strategies. A common thread in EBFM approaches is the need for high-quality observations of ocean conditions, at scales that resolve critical physical-biological processes and are timely for management needs. Here we explore options for a future observing system that meets the needs of EBFM by (i) identifying observing needs for different user groups, (ii) reviewing relevant datasets and existing technologies, (iii) showcasing regional case studies, and (iv) recommending observational approaches required to implement EBFM. We recommend linking ocean observing within the context of Global Ocean Observing System (GOOS) and other regional ocean observing efforts with fisheries observations, new forecasting methods, and capacity development, in a comprehensive ocean observing framework.

Author(s): Thorson, J. T., A. J. Hermann, K. Siwicke, M. Zimmermann.

Project PI: Hollowed
DOI: http://doi.org/10.1093/icesjms/fsaa236

Spatial management has been adopted worldwide to mitigate habitat impacts while achieving fisheries management objectives. However, there is little theory or practice for predicting the impact of spatial regulations on future fishery production; this would provide scientific basis for greater flexibility in fisheries management when balancing fishery and conservation goals. We propose that predicting changes in fishery production resulting from human activities within specific habitats is a “Grand Challenge” for habitat science in the coming decade(s). We then outline three difficulties in resolving this Grand Habitat Challenge, including: (i) stage-structured responses to habitat impacts, (ii) nonlocal responses, and (iii) mechanistic associations among habitat variables. We next discuss analytical approaches to address each difficulty, respectively: (i) ongoing developments for spatial demographic models; (ii) individual movement models and rank-reduction approaches to identify regional variability; (iii) causal analysis involving structural equation models. We demonstrate nonlocal effects in detail using a diffusion-taxis movement model applied to sablefish (Anoplopoma fimbria) in the Gulf of Alaska and discuss all three approaches for deep-sea corals. Despite isolated progress to resolve individual difficulties, we argue that resolving this Grand Habitat Challenge will require a coordinated commitment from science agencies worldwide.

Author(s): Chen, C., Zhao, L., Gallager, S., Ji, R., He, P., Davis, C. S., Beardsley, R.C., Hart, D., Gentleman, W.C., Wang, L., Li, S., Lin, H., Stokesbury, K., Bethoney, D.

Project PI: Ji/David/Rubao
DOI: https://doi.org/10.1016/j.pocean.2021.102604

Sea scallops (Placopecten magellanicus) are a highly fecund species that supports one of the most commercially valuable fisheries in the northeast U.S. continental shelf region. Scallop landings exhibit significant interannual variability, with abundances widely varied due to a combination of anthropogenic and natural factors. By coupling a pelagic-stage Individual-Based scallop population dynamics Model (hereafter referred to as Scallop-IBM) with the Northeast Coastal Ocean Forecast System (NECOFS) and considering the persistent aggregations over Georges Bank (GB)/Great South Channel (GSC) as source beds, we have examined the dispersion and settlement of scallop larvae over 1978–2016. The results demonstrated that the significant interannual variability of larval dispersal was driven by biophysical interactions associated with scallop larval swimming behaviors in their early stages. The duration, frequency, and stimulus of larval vertical migration in the ocean mixed layer (OML) affected the residence time of larvae in the water column over GB. It thus sustained the persistent aggregations of scallops in the GB/GSC and Southern New England region. In addition to larval behavior in the OML, the larval transport to the Middle Atlantic Bight (MAB) was also closely related to the intensity and duration of northeasterly wind in autumn. There was no conspicuous connectivity of scallop larvae between GB/GSC and MAB in the past 39 years except in the autumn of 2009. In 2009, the significant larval transport to the MAB was produced by unusually strong northeasterly winds. Ignoring larval behavior in the OML could overestimate the scallop population’s connectivity between GB and the MAB and thus provide an unrealistic prediction of scallop larval recruitment in the region. Both satellite-derived SST and NECOFS show that the northeast U.S. shelf experienced climate change-induced warming. The extreme warming at the shelfbreak off GB tends to intensify the cross-isobath water temperature gradient and enhance the clockwise subtidal gyre over GB. This change can increase the larval retention rate over GB/GSC, facilitating enhanced productivity on GB.