NOAA National Marine Fisheries Service Office of Science and Technology

Ecosystem transformation involves the emergence of persistent ecological or social–ecological systems that diverge, dramatically and irreversibly, from prior ecosystem structure and function. Such transformations are occurring at increasing rates across the planet in response to changes in climate, land use, and other factors. Consequently, a dynamic view of ecosystem processes that accommodates rapid, irreversible change will be critical for effectively conserving fish, wildlife, and other natural resources, and maintaining ecosystem services. However, managing ecosystems toward states with novel structure and function is an inherently unpredictable and difficult task. Managers navigating ecosystem transformation can benefit from considering broader objectives, beyond a traditional focus on resisting ecosystem change, by also considering whether accepting inevitable change or directing it along some desirable pathway is more feasible (that is, practical and appropriate) under some circumstances (the RAD framework). By explicitly acknowledging transformation and implementing an iterative RAD approach, natural resource managers can be deliberate and strategic in addressing profound ecosystem change.

Abstract Marine ecosystems evolve under many interconnected and area‐specific pressures. To fulfil society's intensifying and diversifying needs while ensuring ecologically sustainable development, more effective marine spatial planning and broader‐scope management of marine resources is necessary. Integrated ecological–economic fisheries models ( IEEFM s) of marine systems are needed to evaluate impacts and sustainability of potential management actions and understand, and anticipate ecological, economic and social dynamics at a range of scales from local to national and regional. To make these models most effective, it is important to determine how model characteristics and methods of communicating results influence the model implementation, the nature of the advice that can be provided and the impact on decisions taken by managers. This article presents a global review and comparative evaluation of 35 IEEFM s applied to marine fisheries and marine ecosystem resources to identify the characteristics that determine their usefulness, effectiveness and implementation. The focus is on fully integrated models that allow for feedbacks between ecological and human processes although not all the models reviewed achieve that. Modellers must invest more time to make models user friendly and to participate in management fora where models and model results can be explained and discussed. Such involvement is beneficial to all parties, leading to improvement of mo‐dels and more effective implementation of advice, but demands substantial resources which must be built into the governance process. It takes time to develop effective processes for using IEEFM s requiring a long‐term commitment to integrating multidisciplinary modelling advice into management decision‐making.

Between 1999 and 2009, autonomous hydrophones were deployed to monitor seismic activity from 16° N to 50° N along the Mid-Atlantic Ridge. These data were examined for airgun sounds produced during offshore surveys for oil and gas deposits, as well as the 20 Hz pulse sounds from fin whales, which may be masked by airgun noise. An automatic detection algorithm was used to identify airgun sound patterns, and fin whale calling levels were summarized via long-term spectral analysis. Both airgun and fin whale sounds were recorded at all sites. Fin whale calling rates were higher at sites north of 32° N, increased during the late summer and fall months at all sites, and peaked during the winter months, a time when airgun noise was often prevalent. Seismic survey vessels were acoustically located off the coasts of three major areas: Newfoundland, northeast Brazil, and Senegal and Mauritania in West Africa. In some cases, airgun sounds were recorded almost 4000 km from the survey vessel in areas that are likely occupied by fin whales, and at some locations airgun sounds were recorded more than 80% days/month for more than 12 consecutive months.

Abstract Ecosystem transformation can be defined as the emergence of a self-organizing, self-sustaining, ecological or social–ecological system that deviates from prior ecosystem structure and function. These transformations are occurring across the globe; consequently, a static view of ecosystem processes is likely no longer sufficient for managing fish, wildlife, and other species. We present a framework that encompasses three strategies for fish and wildlife managers dealing with ecosystems vulnerable to transformation. Specifically, managers can resist change and strive to maintain existing ecosystem composition, structure, and function; accept transformation when it is not feasible to resist change or when changes are deemed socially acceptable; or direct change to a future ecosystem configuration that would yield desirable outcomes. Choice of a particular option likely hinges on anticipating future change, while also acknowledging that temporal and spatial scales, recent history and current state of the system, and magnitude of change can factor into the decision. This suite of management strategies can be implemented using a structured approach of learning and adapting as ecosystems change.

Recent warm temperatures driven by climate change have caused mass coral bleaching and mortality across the world, prompting managers, policymakers, and conservation practitioners to embrace restoration as a strategy to sustain coral reefs. Despite a proliferation of new coral reef restoration efforts globally and increasing scientific recognition and research on interventions aimed at supporting reef resilience to climate impacts, few restoration programs are currently incorporating climate change and resilience in project design. As climate change will continue to degrade coral reefs for decades to come, guidance is needed to support managers and restoration practitioners to conduct restoration that promotes resilience through enhanced coral reef recovery, resistance, and adaptation. Here, we address this critical implementation gap by providing recommendations that integrate resilience principles into restoration design and practice, including for project planning and design, coral selection, site selection, and broader ecosystem context. We also discuss future opportunities to improve restoration methods to support enhanced outcomes for coral reefs in response to climate change. As coral reefs are one of the most vulnerable ecosystems to climate change, interventions that enhance reef resilience will help to ensure restoration efforts have a greater chance of success in a warming world. They are also more likely to provide essential contributions to global targets to protect natural biodiversity and the human communities that rely on reefs.

Projecting the future distributions of commercially and ecologically important species has become a critical approach for ecosystem managers to strategically anticipate change, but large uncertainties in projections limit climate adaptation planning. Although distribution projections are primarily used to understand the scope of potential change-rather than accurately predict specific outcomes-it is nonetheless essential to understand where and why projections can give implausible results and to identify which processes contribute to uncertainty. Here, we use a series of simulated species distributions, an ensemble of 252 species distribution models, and an ensemble of three regional ocean climate projections, to isolate the influences of uncertainty from earth system model spread and from ecological modeling. The simulations encompass marine species with different functional traits and ecological preferences to more broadly address resource manager and fishery stakeholder needs, and provide a simulated true state with which to evaluate projections. We present our results relative to the degree of environmental extrapolation from historical conditions, which helps facilitate interpretation by ecological modelers working in diverse systems. We found uncertainty associated with species distribution models can exceed uncertainty generated from diverging earth system models (up to 70% of total uncertainty by 2100), and that this result was consistent across species traits. Species distribution model uncertainty increased through time and was primarily related to the degree to which models extrapolated into novel environmental conditions but moderated by how well models captured the underlying dynamics driving species distributions. The predictive power of simulated species distribution models remained relatively high in the first 30 years of projections, in alignment with the time period in which stakeholders make strategic decisions based on climate information. By understanding sources of uncertainty, and how they change at different forecast horizons, we provide recommendations for projecting species distribution models under global climate change.

For decades, the bio-duck sound has been recorded in the Southern Ocean, but the animal producing it has remained a mystery. Heard mainly during austral winter in the Southern Ocean, this ubiquitous sound has been recorded in Antarctic waters and contemporaneously off the Australian west coast. Here, we present conclusive evidence that the bio-duck sound is produced by Antarctic minke whales (Balaenoptera bonaerensis). We analysed data from multi-sensor acoustic recording tags that included intense bio-duck sounds as well as singular downsweeps that have previously been attributed to this species. This finding allows the interpretation of a wealth of long-term acoustic recordings for this previously acoustically concealed species, which will improve our understanding of the distribution, abundance and behaviour of Antarctic minke whales. This is critical information for a species that inhabits a difficult to access sea-ice environment that is changing rapidly in some regions and has been the subject of contentious lethal sampling efforts and ongoing international legal action.

In response to dramatic seasonal sea ice loss and other physical changes influencing biological communities, a Distributed Biological Observatory (DBO) was proposed in 2009 as a “change detection array” to measure biological responses to physical variability along a latitudinal gradient extending from the northern Bering Sea to the Beaufort Sea in the Pacific Arctic sector. In 2010, the Pacific Arctic Group (PAG) initiated a pilot program, focused on developing standardized sampling protocols in five regions of high productivity, biodiversity, and rates of change. In 2012, an academic team received funding to sample all five DBO regions, with collateral support from the Interagency Arctic Research Policy Committee (IARPC) DBO Collaboration Team. The IARPC team met monthly from 2012 to 2016 and advanced the DBO from a pilot phase to an implementation phase, including 1) the addition of three new sampling regions in the Beaufort Sea, 2) the goal of linking the observatory to existing community-based observation programs, and 3) the development of a plan for a periodic Pacific Arctic Regional Marine Assessment (PARMA) beginning in 2018. The long-term future of the DBO will depend on active involvement of international and national partners focused on the common goal of improved pan-Arctic assessments of regional marine ecosystems in an era of rapid change.

Abstract Multispecies models have existed in a fisheries context since at least the 1970s, but despite much exploration, advancement, and consideration of multispecies models, there remain limited examples of their operational use in fishery management. Given that species and fleet interactions are inherently multispecies problems and the push towards ecosystem-based fisheries management, the lack of more regular operational use is both surprising and compelling. We identify impediments hampering the regular operational use of multispecies models and provide recommendations to address those impediments. These recommendations are: (1) engage stakeholders and managers early and often; (2) improve messaging and communication about the various uses of multispecies models; (3) move forward with multispecies management under current authorities while exploring more inclusive governance structures and flexible decision-making frameworks for handling tradeoffs; (4) evaluate when a multispecies modelling approach may be more appropriate; (5) tailor the multispecies model to a clearly defined purpose; (6) develop interdisciplinary solutions to promoting multispecies model applications; (7) make guidelines available for multispecies model review and application; and (8) ensure code and models are well documented and reproducible. These recommendations draw from a global assemblage of subject matter experts who participated in a workshop entitled “Multispecies Modeling Applications in Fisheries Management”.

Fishing capacity has been an important national and international topic for over a decade. Led by the Food and Agriculture Organization of the United Nations (FAO), an international effort was undertaken in 1998 to define and measure fishing capacity, during which three methods to measure fishing capacity were identified–data envelopment analysis (DEA), stochastic production frontiers (SPF), and the peak-to-peak approach. Most estimates of capacity have been carried out using DEA. This study introduces “order-m” frontiers and the free disposal hull (FDH) as additional methods to estimate fishing capacity, and compares capacity estimates for a group of fishing vessels based on the DEA, FDH, and order-m models. Our results show a large difference between capacity estimates using DEA when compared to the other two methods.

By ending the “race to fish” catch share programs may be expected to lead to improved productivity at the fishery level by retiring redundant capital and by allowing fishing firms to become more technically efficient in their harvesting activities by, among other things, changing the composition of inputs and outputs. Yet, there have been relatively few empirical studies of productivity changes in catch share fisheries and no comprehensive treatment of a cross-section of programs using a common measure of productivity change. In this study estimates of multi-factor productivity change for 20 catch share fisheries in the U.S. using a Lowe index are provided. With few exceptions, productivity increased relative to baseline conditions during the first three years of catch share program implementation. For five of six of the most established catch share programs, these initial productivity gains have been maintained or have continued to improve.

Abstract The welfare effects of the 2010 transition from Days‐at‐Sea to catch share management in the Northeast U.S. groundfish fishery are examined by combining a model of groundfish demand with a simulation‐based model of supply. Counterfactual supply is constructed based on the Days‐at‐Sea system that was recalibrated to meet mandated conservation goals. Due to the decreases in catch that were required to meet those goals, the 2010 policy undoubtedly resulted in worse outcomes for both producers and consumers compared to 2009. However, the conservation‐equivalent Days‐at‐Sea system would have been far worse for both consumers and producers.

Abstract As the urgency to evaluate the impacts of climate change on marine ecosystems increases, there is a need to develop robust projections and improve the uptake of ecosystem model outputs in policy and planning. Standardizing input and output data is a crucial step in evaluating and communicating results, but can be challenging when using models with diverse structures, assumptions, and outputs that address region‐specific issues. We developed an implementation framework and workflow to standardize the climate and fishing forcings used by regional models contributing to the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) and to facilitate comparative analyses across models and a wide range of regions, in line with the FishMIP 3a protocol. We applied our workflow to three case study areas‐models: the Baltic Sea Mizer, Hawai'i‐based Longline fisheries therMizer, and the southern Benguela ecosystem Atlantis marine ecosystem models. We then selected the most challenging steps of the workflow and illustrated their implementation in different model types and regions. Our workflow is adaptable across a wide range of regional models, from non‐spatially explicit to spatially explicit and fully‐depth resolved models and models that include one or several fishing fleets. This workflow will facilitate the development of regional marine ecosystem model ensembles and enhance future research on marine ecosystem model development and applications, model evaluation and benchmarking, and global‐to‐regional model comparisons.

As the urgency to evaluate the impacts of climate change on marine ecosystems increases, there is a need to develop robust projections and improve the uptake of ecosystem model outputs in policy and planning. Standardising input and output data is a crucial step in evaluating and communicating results, but can be challenging when using models with diverse structures, assumptions, and outputs that address region-specific issues. We developed an implementation framework and workflow to standardise the climate and fishing forcings used by regional models contributing to the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) and to facilitate comparative analyses across models and a wide range of regions, in line with the FishMIP 3a protocol. We applied our workflow to three case study areas-models: the Baltic Sea Mizer, Hawai’i-based Longline fisheries therMizer, and the southern Benguela ecosystem Atlantis marine ecosystem models. We then selected the most challenging steps of the workflow and illustrated their implementation in different model types and regions. Our workflow is adaptable across a wide range of regional models, from non-spatially explicit to spatially explicit and fully-depth resolved models and models that include one or several fishing fleets. This workflow will facilitate the development of regional marine ecosystem model ensembles and enhance future research on marine ecosystem model development and applications, model evaluation and benchmarking, and global-to-regional model comparisons.

The Gulf of Maine (GOM) is a highly complex environment and previous studies have suggested the need to account for spatial nonstationarity in species distribution models (SDMs) for the American lobster ( Homarus americanus ). To explore impacts of spatial nonstationarity on species distribution, we compared models with the following three assumptions : (1) large-scale and stationary relationships between species distributions and environmental variables; (2) meso-scale models where estimated relationships differ between eastern and western GOM, and (3) finer-scale models where estimated relationships vary across eastern, central, and western regions of the GOM. The spatial scales used in these models were largely determined by the GOM coastal currents. Lobster data were sourced from the Maine-New Hampshire Inshore Bottom Trawl Survey from years 2000–2019. We considered spatial and environmental variables including latitude and longitude, bottom temperature, bottom salinity, distance from shore, and sediment grain size in the study. We forecasted distributions for the period 2028–2055 using each of these models under the Representative Concentration Pathway (RCP) 8.5 “business as usual” climate warming scenario. We found that the model with the third assumption (i.e., finest scale) performed best. This suggests that accounting for spatial nonstationarity in the GOM leads to improved distribution estimates. Large-scale models revealed a tendency to estimate global relationships that better represented a specific location within the study area, rather than estimating relationships appropriate across all spatial areas. Forecasted distributions revealed that the largest scale models tended to comparatively overestimate most season × sex × size group lobster abundances in western GOM, underestimate in the western portion of central GOM, and overestimate in the eastern portion of central GOM, with slightly less consistent and patchy trends amongst groups in eastern GOM. The differences between model estimates were greatest between the largest and finest scale models, suggesting that fine-scale models may be useful for capturing effects of unique dependencies that may operate at localized scales. We demonstrate how estimates of season-, sex-, and size- specific American lobster spatial distribution would vary based on the spatial scale assumption of nonstationarity in the GOM. This information may help develop appropriate local adaptation measures in a region that is susceptible to climate change.

ABSTRACT In the Southern Hemisphere and northern Indian Ocean, there are at least five populations of pygmy blue whales, Balaenoptera musculus brevicauda , residing in the Northwest Indian Ocean (NWIO, Oman), central Indian Ocean (CIO, Sri Lanka), Southwest Indian Ocean (SWIO, Madagascar to Subantarctic), Southeast Indian Ocean (SEIO, Australia to Indonesia), and Southwest Pacific Ocean (SWPO, New Zealand). Each population produces a distinctive repeated song, but none have population assessments or reliable measures of historical whaling pressure. Here we created pygmy blue whale catch time series by removing Antarctic blue whale catches using length data and then fitting generalized additive models (based on latitude, longitude, and month) to contemporary song data (largely from 1995 to 2023) to allocate historical catches to the five populations. Most pygmy blue whale catches (97% of 12,207) were taken by Japanese and Soviet operations during 1959/1960 to 1971/1972, with the highest totals taken from the SWIO (6514), SEIO (2593), and CIO (2023), and lower catches from the NWIO (549) and SWPO (528). The resulting predicted annual catch assignments provide the first indication of the magnitude of whaling pressure on each population and are a key step toward assessing the status of these five pygmy blue whale populations.

Abstract Climate-driven changes in marine ecosystem structure and function adversely impact the biodiversity and sustainability of living marine resources, food security, and the resilience of coastal communities. Understanding how climate change impacts marine ecosystem biodiversity and global fisheries, i.e. the “climate-biodiversity-fisheries nexus”, is a fundamental element of the UN Decade of Ocean Science for Sustainable Development. Several Ocean Decade-endorsed Programmes within the climate-biodiversity-fisheries nexus are building global networks to transform our capacity to understand, forecast, manage, and adapt to climate-driven changes in ocean ecosystems, including sustaining blue food resources that provide essential food security and nutrition in a rapidly changing world. We compare the scope, objectives, global partnerships, and capacities of these Programmes, facilitating effective collaboration and identifying critical gaps in developing solutions to climate-driven changes in marine food webs, species assemblages, and global fisheries. This work complements the Ocean Decade Vision 2030 process by providing an assessment of actions that are underway and guidance to establish new actions needed to monitor and understand marine biodiversity and manage global fisheries within a changing climate. We provide recommendations for new and existing Ocean Decade Actions around the climate-biodiversity-fisheries nexus to help achieve the Ocean Decade outcomes of a “productive, predicted, healthy, and resilient ocean” by 2030.

To address our climate emergency, "we must rapidly, radically reshape society"-Johnson & Wilkinson, All We Can Save. In science, reshaping requires formidable technical (cloud, coding, reproducibility) and cultural shifts (mindsets, hybrid collaboration, inclusion). We are a group of cross-government and academic scientists that are exploring better ways of working and not being too entrenched in our bureaucracies to do better science, support colleagues, and change the culture at our organizations. We share much-needed success stories and action for what we can all do to reshape science as part of the Open Science movement and 2023 Year of Open Science.

The U.S. Global Change Research Program (USGCRP) recently released its Fifth National Climate Assessment (NCA5; https://nca2023.globalchange.gov/). The report, delivered to Congress and the president, “…analyzes the effects of global change on the natural environment, agriculture, energy production and use, land and water resources, transportation, human health and welfare, human social systems, and biological diversity; and analyzes current trends in global change, both human-induced and natural, and projects major trends for the subsequent 25 to 100 years.” The NCA5 summarizes and evaluates the state of the science on climate change and provides policy-neutral information to decision-makers at local, state, and national levels, as well as Tribal governments, about potential impacts of climate change and opportunities for addressing them. Of particular interest to CSA News readers is “Chapter 11—Agriculture, Food Systems, and Rural Communities.” This chapter discusses the serious challenges climate change poses to U.S. agricultural production, food systems, and rural communities. Based on our author team’s review of pertinent literature, followed by input and detailed comments from many—including the general public, the Federal Steering Committee, and an ad hoc committee of the National Academies of Science, Engineering, and Math—three key messages emerged for this chapter of the NCA5. In Key Message 1, we highlighted several important disruptions to agriculture caused by a changing climate. The northward migration of plant hardiness zones will require changes in agricultural practices such as crop selection, equipment, and management approaches. Combatting soil degradation caused by climate change will require adoption of conservation practices that improve soil health. While increasing efficiency has lowered greenhouse gas (GHG) emissions per unit of agricultural productivity, total GHG emissions from U.S. agriculture have been steadily rising over the past 30 years. We emphasized that adopting agroecological approaches with a focus on soil health, adaptive conservation management, diversification of landscapes, and climate-smart practices that target the right amount, source, placement, and timing of nitrogen fertilizers can lead to increased productivity, resilience to climate change, and reductions in GHG emissions. We defined agroecological approaches as “land management practices that integrate biophysical, technological, and social concepts and principles to guide the design and management of food and agricultural systems.” This definition encompasses subsistence and organic farming as well as the judicious use of technological interventions (such as climate-smart practices). More high quality/high resolution data will be needed to provide decision makers with the information needed to effectively manage agriculture and improve resilience and adaptability to climate change. In Key Message 2, we emphasized that climate change is expected to adversely affect all dimensions of food security—availability, accessibility, usability, and stability. Compounding effects, such as heat waves occurring during a drought, make our complex food systems even more vulnerable. For example, climate change is projected to double the number of unsafe working days for farmworkers by mid-century while drought simultaneously reduces the income of already food-insecure farmworkers and thus their ability to buy food. Food system disruptions occur at local, regional, national, and international levels, and are projected to affect the affordability of some foods. Increased food prices are expected to disproportionally affect women, children, older adults, and low-wealth communities. Climate change may also affect the ability to obtain food through hunting, foraging, fishing, and subsistence farming. Greenhouse gas (GHG) emissions from various aspects of the food system were also discussed. Reducing food loss and waste can reduce GHG emissions and increase food security. While the impacts of climate change on food production have been measured, the socioeconomic costs to food processing, distribution, and consumption are less well understood. Agricultural Adaptation Increases Resilience in an Evolving Landscape. Climate change has increased agricultural production risks by disrupting growing zones and growing days, which depend on precipitation, air temperature, and soil moisture. Growing evidence for positive environmental and economic outcomes of conservation management has led some farmers and ranchers to adopt agroecological practices, which increases the potential for agricultural producers to limit greenhouse gas emissions and improve agricultural resilience to climate change. Climate Change Disrupts Our Food Systems in Uneven Ways. Climate change is projected to disrupt food systems in ways that reduce the availability and affordability of nutritious food, with uneven economic impacts across society. Impacts of climate change on other measures of human well-being are also distributed unevenly, such as worsening heat stress among farmworkers and disruptions to the ability of subsistence-based peoples to access food through hunting, fishing, and foraging. Rural Communities Face Unique Challenges and Opportunities. Rural communities steward much of the nation’s land and natural resources, which provide food, bioproducts, and ecosystem services. These crucial roles are at risk as climate change compounds existing stressors such as poverty, unemployment, and depopulation. Opportunities exist for rural communities to increase their resilience to climate change and protect rural livelihoods. Climate change is projected to double the number of unsafe working days for farmworkers by midcentury while drought simultaneously reduces their income. You can find read the full chapter at https://nca2023.globalchange.gov/chapter/11/.

In 2010, the Northeast groundfish fishery transitioned from an effort-control system (Days-at-Sea) to an output-control system (catch shares). Simultaneously, a large decrease in aggregate catch was imposed in order to achieve biological objectives. This research examines the welfare effects of the transition to catch-share management by combining an inverse demand model for groundfish with a simulation based model of supply. The Generalized Differential Inverse Demand System is estimated for groundfish and imports using monthly data from 1994-2011 using a Generalized Method of Moments estimator. The estimated parameters are combined with simulated landings derived from a counterfactual policy scenario had ef- fort controls been retained instead of the catch share system. The simultaneous management change to catch shares and reduction in aggregate catch reduced consumer welfare by approximately $11M. A counterfactual policy in which the Days-at-Sea system was adjusted to meet the catch reductions would have reduced consumer welfare by approximately $37M; this finding is robust to instrument choice in the demand model. Because the 2010 fishing regulations and the counterfactual regulations were designed with the same conservation goals, the difference, approximately $26M, can be attributed to the change in management institution. Finally, reversion to the Days-at-Sea regulatory structure would reduce consumer welfare by approximately $25M from the current (2010) levels.