GLORIA

GEOMAR Library Ocean Research Information Access

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    In: Global Change Biology, Wiley, Vol. 28, No. 22 ( 2022-11), p. 6586-6601
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 1354-1013 , 1365-2486
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 2020313-5
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    In: ICES Journal of Marine Science, Oxford University Press (OUP), Vol. 80, No. 2 ( 2023-03-14), p. 243-257
    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”.
    Type of Medium: Online Resource
    ISSN: 1054-3139 , 1095-9289
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 2463178-4
    detail.hit.zdb_id: 1468003-8
    detail.hit.zdb_id: 29056-7
    SSG: 12
    SSG: 21,3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    In: ICES Journal of Marine Science, Oxford University Press (OUP), Vol. 71, No. 8 ( 2014-10-01), p. 2208-2220
    Abstract: The ability of management strategies to achieve the fishery management goals are impacted by environmental variation and, therefore, also by global climate change. Management strategies can be modified to use environmental data using the “dynamic B0” concept, and changing the set of years used to define biomass reference points. Two approaches have been developed to apply management strategy evaluation to evaluate the impact of environmental variation on the performance of management strategies. The “mechanistic approach” estimates the relationship between the environment and elements of the population dynamics of the fished species and makes predictions for population trends using the outputs from global climate models. In contrast, the “empirical approach” examines possible broad scenarios without explicitly identifying mechanisms. Many reviewed studies have found that modifying management strategies to include environmental factors does not improve the ability to achieve management goals much, if at all, and only if the manner in which these factors drive the system is well known. As such, until the skill of stock projection models improves, it seems more appropriate to consider the implications of plausible broad forecasts related to how biological parameters may change in the future as a way to assess the robustness of management strategies, rather than attempting specific predictions per se.
    Type of Medium: Online Resource
    ISSN: 1095-9289 , 1054-3139
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2014
    detail.hit.zdb_id: 2463178-4
    detail.hit.zdb_id: 1468003-8
    detail.hit.zdb_id: 29056-7
    SSG: 12
    SSG: 21,3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 4
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2019
    In:  ICES Journal of Marine Science Vol. 76, No. 6 ( 2019-12-01), p. 1524-1542
    In: ICES Journal of Marine Science, Oxford University Press (OUP), Vol. 76, No. 6 ( 2019-12-01), p. 1524-1542
    Abstract: US West Coast sablefish are economically valuable, with landings of 11.8 million pounds valued at over $31 million during 2016, making assessing and understanding the impact of climate change on the California Current (CC) stock a priority for (1) forecasting future stock productivity, and (2) testing the robustness of management strategies to climate impacts. Sablefish recruitment is related to large-scale climate forcing indexed by regionally correlated sea level (SL) and zooplankton communities that pelagic young-of-the-year sablefish feed upon. This study forecasts trends in future sablefish productivity using SL from Global Climate Models (GCMs) and explores the robustness of harvest control rules (HCRs) to climate driven changes in recruitment using management strategy evaluation (MSE). Future sablefish recruitment is likely to be similar to historical recruitment but may be less variable. Most GCMs suggest that decadal SL trends result in recruitments persisting at lower levels through about 2040 followed by higher levels that are more favorable for sablefish recruitment through 2060. Although this MSE suggests that spawning biomass and catches will decline, and then stabilize, into the future under both HCRs, the sablefish stock does not fall below the stock size that leads to fishery closures.
    Type of Medium: Online Resource
    ISSN: 1054-3139 , 1095-9289
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 2463178-4
    detail.hit.zdb_id: 1468003-8
    detail.hit.zdb_id: 29056-7
    SSG: 12
    SSG: 21,3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 5
    Online Resource
    Online Resource
    Canadian Science Publishing ; 2015
    In:  Canadian Journal of Fisheries and Aquatic Sciences Vol. 72, No. 9 ( 2015-09), p. 1316-1328
    In: Canadian Journal of Fisheries and Aquatic Sciences, Canadian Science Publishing, Vol. 72, No. 9 ( 2015-09), p. 1316-1328
    Abstract: Understanding demographic variation in recruitment and somatic growth is key to improving our understanding of population dynamics and forecasting ability. Although recruitment variability has been extensively studied, somatic growth variation has received less attention, in part because of difficulties in modeling growth from individual size-at-age estimates. Here we develop a Bayesian state-space approach to test for the prevalence of alternative forms of growth rate variability (e.g., annual, cohort-level, or in the first year recruited to the fishery) in size-at-age data. We apply this technique to 29 Pacific groundfish species across the California Current, Gulf of Alaska, and Bering Sea – Aleutian Islands marine ecosystems. About 40% of modeled stocks were estimated to exhibit temporal growth variation. In the majority of stocks, growth trends fluctuated annually across ages in a single year, suggesting that either there are shared environmental features that dictate growth across multiple ages or the presence of some systematic (within-year) observation errors. This method represents a novel way to use size-at-age data from fishery or other sources to test hypotheses about growth dynamics variability.
    Type of Medium: Online Resource
    ISSN: 0706-652X , 1205-7533
    Language: English
    Publisher: Canadian Science Publishing
    Publication Date: 2015
    detail.hit.zdb_id: 7966-2
    detail.hit.zdb_id: 1473089-3
    SSG: 21,3
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 6
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 1998
    In:  Nature Vol. 393, No. 6680 ( 1998-5), p. 27-28
    In: Nature, Springer Science and Business Media LLC, Vol. 393, No. 6680 ( 1998-5), p. 27-28
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
    RVK:
    RVK:
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 1998
    detail.hit.zdb_id: 120714-3
    detail.hit.zdb_id: 1413423-8
    SSG: 11
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 7
    Online Resource
    Online Resource
    Canadian Science Publishing ; 2017
    In:  Canadian Journal of Fisheries and Aquatic Sciences Vol. 74, No. 11 ( 2017-11), p. 1794-1807
    In: Canadian Journal of Fisheries and Aquatic Sciences, Canadian Science Publishing, Vol. 74, No. 11 ( 2017-11), p. 1794-1807
    Abstract: Estimating trends in abundance from fishery catch rates is one of the oldest endeavors in fisheries science. However, many jurisdictions do not analyze fishery catch rates due to concerns that these data confound changes in fishing behavior (adjustments in fishing location or gear operation) with trends in abundance. In response, we developed a spatial dynamic factor analysis (SDFA) model that decomposes covariation in multispecies catch rates into components representing spatial variation and fishing behavior. SDFA estimates spatiotemporal variation in fish density for multiple species and accounts for fisher behavior at large spatial scales (i.e., choice of fishing location) while controlling for fisher behavior at fine spatial scales (e.g., daily timing of fishing activity). We first use a multispecies simulation experiment to show that SDFA decreases bias in abundance indices relative to ignoring spatial adjustments and fishing tactics. We then present results for a case study involving petrale sole (Eopsetta jordani) in the California Current, for which SDFA estimates initially stable and then increasing abundance for the period 1986–2003, in accordance with fishery-independent survey and stock assessment estimates.
    Type of Medium: Online Resource
    ISSN: 0706-652X , 1205-7533
    Language: English
    Publisher: Canadian Science Publishing
    Publication Date: 2017
    detail.hit.zdb_id: 7966-2
    detail.hit.zdb_id: 1473089-3
    SSG: 21,3
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 8
    Online Resource
    Online Resource
    Canadian Science Publishing ; 2019
    In:  Canadian Journal of Fisheries and Aquatic Sciences Vol. 76, No. 3 ( 2019-03), p. 401-414
    In: Canadian Journal of Fisheries and Aquatic Sciences, Canadian Science Publishing, Vol. 76, No. 3 ( 2019-03), p. 401-414
    Abstract: Stock assessment models are fitted to abundance-index, fishery catch, and age–length–sex composition data that are estimated from survey and fishery records. Research has developed spatiotemporal methods to estimate abundance indices, but there is little research regarding model-based methods to generate age–length–sex composition data. We demonstrate a spatiotemporal approach to generate composition data and a multinomial sample size that approximates the estimated imprecision. A simulation experiment comparing spatiotemporal and design-based methods demonstrates a 32% increase in input sample size for the spatiotemporal estimator. A Stock Synthesis assessment used to manage lingcod (Ophiodon elongatus) in the California Current also shows a 17% increase in sample size and better model fit using the spatiotemporal estimator, resulting in smaller standard errors when estimating spawning biomass. We conclude that spatiotemporal approaches are feasible for estimating both abundance-index and compositional data, thereby providing a unified approach for generating inputs for stock assessments. We hypothesize that spatiotemporal methods will improve statistical efficiency for composition data in many stock assessments and recommend that future research explore the impact of including additional habitat or sampling covariates.
    Type of Medium: Online Resource
    ISSN: 0706-652X , 1205-7533
    Language: English
    Publisher: Canadian Science Publishing
    Publication Date: 2019
    detail.hit.zdb_id: 7966-2
    detail.hit.zdb_id: 1473089-3
    SSG: 21,3
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 9
    In: Ecography, Wiley, Vol. 43, No. 1 ( 2020-01), p. 11-24
    Abstract: Species distribution models (SDMs) are a common approach to describing species’ space‐use and spatially‐explicit abundance. With a myriad of model types, methods and parameterization options available, it is challenging to make informed decisions about how to build robust SDMs appropriate for a given purpose. One key component of SDM development is the appropriate parameterization of covariates, such as the inclusion of covariates that reflect underlying processes (e.g. abiotic and biotic covariates) and covariates that act as proxies for unobserved processes (e.g. space and time covariates). It is unclear how different SDMs apportion variance among a suite of covariates, and how parameterization decisions influence model accuracy and performance. To examine trade‐offs in covariation parameterization in SDMs, we explore the attribution of spatiotemporal and environmental variation across a suite of SDMs. We first used simulated species distributions with known environmental preferences to compare three types of SDM: a machine learning model (boosted regression tree), a semi‐parametric model (generalized additive model) and a spatiotemporal mixed‐effects model (vector autoregressive spatiotemporal model, VAST). We then applied the same comparative framework to a case study with three fish species (arrowtooth flounder, pacific cod and walleye pollock) in the eastern Bering Sea, USA. Model type and covariate parameterization both had significant effects on model accuracy and performance. We found that including either spatiotemporal or environmental covariates typically reproduced patterns of species distribution and abundance across the three models tested, but model accuracy and performance was maximized when including both spatiotemporal and environmental covariates in the same model framework. Our results reveal trade‐offs in the current generation of SDM tools between accurately estimating species abundance, accurately estimating spatial patterns, and accurately quantifying underlying species–environment relationships. These comparisons between model types and parameterization options can help SDM users better understand sources of model bias and estimate error.
    Type of Medium: Online Resource
    ISSN: 0906-7590 , 1600-0587
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2024917-2
    detail.hit.zdb_id: 1112659-0
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 10
    Online Resource
    Online Resource
    Wiley ; 2000
    In:  Limnology and Oceanography Vol. 45, No. 8 ( 2000-12), p. 1778-1787
    In: Limnology and Oceanography, Wiley, Vol. 45, No. 8 ( 2000-12), p. 1778-1787
    Type of Medium: Online Resource
    ISSN: 0024-3590
    Language: English
    Publisher: Wiley
    Publication Date: 2000
    detail.hit.zdb_id: 2033191-5
    detail.hit.zdb_id: 412737-7
    SSG: 12
    SSG: 14
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...