Introduction

Step 9: Detailed Assessments

Multiple performance indicators from independent data streams that are related to fishery goals can be selected, in order to gain a more complete understanding of the fishery and reduce uncertainty associated with any single model or data type.

Once priorities for assessment are identified and precautionary measures are taken, data should be carefully evaluated and matched to appropriate data-limited assessment methods in order to set catch limits or other fishing mortality controls for high priority stocks. The available data will dictate the type of assessment methods that can be used. Data-limited assessment methods are relatively simple to use but require a great deal of care in interpreting the results to generate useful management guidance. Multiple analyses are recommended to increase the dependability of the results, however, you will likely only be using one of the methods below, depending upon the data you have available. Use the Method Matrix to determine the methods that are most appropriate for your stocks. 

It is good practice to use several methods, ideally methods that use independent sources of data – for example, F and SPR from length composition of the catch plus MPA density ratio from fishery independent surveys –  to see if they yield consistent results.  If they appear to conflict, work with your experts and fishermen to come up with plausible explanations. For example, F might be high and SPR low indicating possible overfishing while the MPA density ratio is high indicating healthy stocks. In this case, experts might explain that most of the catch occurred in nursery grounds, biasing the length composition toward small individuals, which would result in high estimates of F and low SPR estimates. If the MPA is not in the nursery areas, the MPA density ratio calculation would not be affected by this bias.

Several data-limited assessment methods that are recommended on FISHE are available in a statistical toolkit developed by the Natural Resources Defense Council (NRDC). The NRDC Toolkit enables users to quickly apply multiple data-limited methods to a large number of stocks, and to test the performance of these methods for a given stock under given circumstances (i.e. life history parameters, data availability, fishery characteristics), with a built-in closed-loop MSE (Management Strategy Evaluation). We encourage users to explore the NRDC toolkit. A working understanding of the R statistical environment and the methods presented in the toolkit are both necessary for its use.

More information on the NRDC toolkit can be found in report entitled Improving the Science and Management of Data Limited Fisheries: An Evaluation of Current Methods and Recommended Approaches, and can be downloaded directly through the CRAN-R repository at http://cran.r-project.org/web/packages/DLMtool/index.html or at http://www.datalimitedtoolkit.com (Carruthers, 2014).

* The methods detailed and applied at Step 4 of this framework can also be applied at Step 9, with the inclusion of more or better data.

Methods

Biomass Dynamics

This method estimates stock biomass and fishing mortality using catch, effort, and any available indices of relative abundance without the inclusion of stock age or length structure.  This model does not reflect any age structure in a population, and the dynamics of natural mortality, growth, and recruitment are aggregated into a single intrinsic rate of population biomass increase, modified by fishing mortality. Estimated biomass and fishing mortality can be examined relative to reference points to determine stock status.

Inputs:

  • Total catch, stock biomass (if discards are low, then can be just landings)
  • Preferably more than 10 years of catch and abundance data
  • Catchability
  • Effort
  • Index of relative abundance

Input Sensitivities:

  • Life history phenomena not incorporated (e.g., age of recruitment);
  • Survival
  • Growth

Outputs:

  • estimate of MSY

Assumptions:

  • Catch is known without error
  • Stock is undifferentiated (no age, size, or gender differences)
  • Catch and/or index is linearly related to the stock abundance
  • Entire population covered by catch and index

Reference points:

  • Stock status based reference point for estimating sustainable yield
  • FMSY
  • F10%B
  • F40%B
  • BMSY

Recommendations:

  • Fishing mortality is adjusted through harvest control methods (e.g. catch limits, seasons, or spatial closures) based on how far apart these values are from TRP & LRP.
  • Surplus production models produce relative estimates of MSY and FMSY, good estimates of q (the parameter that scales abundance indices into biomass estimates) and are scaled to steepness of the recruitment curve increase the certainty.

Depletion-Corrected Average Catch (DCAC)

Depletion-Corrected Average Catch (DCAC) uses historical catch data (preferably ten years or more) and an estimated natural mortality rate (preferably 0.2 or smaller) to determine potential sustainable yield. An extension of potential-yield models, DCAC is based on the theory that average catch is sustainable if stock abundance has not changed substantially. The method differs from simple extrapolation of average catch to estimate sustainable yield by correcting for the initial depletion in fish abundance typical of many fisheries. DCAC divides the target stock into two categories: a sustainable yield component and an unsustainable “windfall” component, which is based upon a one-time drop in stock abundance for a newly established fishery. DCAC calculates a sustainable fishery yield, provided the stock is kept at historical abundance levels.

Software for conducting DCAC can be downloaded free of charge from the NOAA Fisheries Toolbox website at http://nft.nefsc.noaa.gov/ 

Inputs:

  • Historical catch data (preferably ten years or more), including average catch and any approximate relative changes in stock size during the period the catch was taken
  • Natural mortality rate (M) (preferably .02 or smaller)
  • Ratio of the fishing rate at Maximum Sustainable Yield (Fmsy) to the natural mortality rate (M) (Fmsy/M)

Input Sensitivities:

  • Performs poorly with low starting abundance levels and should be used with caution for targets that are in rebuilding programs

Outputs:

  • Sustainable Yield* (based on average catch).

*Not to be used for setting overfishing limits (OFLs) because it does not account for low stock size.

Assumptions:

  • Change in relative stock status over time is known
  • Average catch has been sustainable if abundance has not chaned
  • Catch is composed of both Sustainable catch and "Windfall" (unsustainable) catch. (Model adjusts average catch to account for the Windfall)
  • Summing the catch over the time series (years of available data) represents relationships of FMSY/M and BMSY/B0

Reference points:

  • stock status based reference point to estimate sustainable yield, as a reference value to control F.
  • FMSY /M
  • BMSY /Bo

Recommendations:

Fishing mortality is adjusted through harvest control methods (e.g. catch limits, seasons, or spatial closures) based on how far apart these values are from TRP & LRP for OFL.

Depletion-Based Stock Reduction Analysis (DB-SRA)

Depletion-Based Stock Reduction Analysis (DB-SRA) combines DCAC with a probability analysis to more closely link stock production with biomass and evaluate potential changes in abundance over time. Using Monte Carlo simulations, DB-SRA provides probability distributions for stock size over a given time period, under varying recruitment rates. The addition of a probability analysis increases the reliability and decreases uncertainties associated with historical biomass estimates generated from DCAC.

Inputs:

  • Complete time series of historical catches
  • Level of current depletion 
  • Estimate of age at recruitment to the fishery
  • Natural mortality rate (M)
  • Ratio of the fishing rate at Maximum Sustainable Yield (FMSY) to the natural mortality rate (M) (FMSY/M)
  • The most productive stock size relative to unfished (BMSY/ B0)

Input Sensitivities:

  • Performs poorly with low starting abundance levels and should be used with caution for targets that are in rebuilding programs

    Outputs:

    • Probability distributions for biological reference points such as: unfishied biomass; MSY; the overfishing limit (OFL), and the distributions of stock size over time

    Assumptions:

    • Change in relative stock status over time is known
    • Average catch has been sustainable if abundance has not changed
    • Catch is composed of both Sustainable catch and "Windfall" (unsustainable) catch. (Model adjusts average catch to account for the Windfall)
    • Summing the catch over the time series (years of available data) represents relationships of FMSY/M and BMSY/B0

    Reference points:

    • stock status based reference point to estimate sustainable yield, as a reference value to control F
    • FMSY /M
    • BMSY /B0

    Recommendations:

    Fishing mortality is adjusted through harvest control methods (e.g. catch limits, seasons, or spatial closures) based on how far apart these values are from TRP & LRP for OFL.

    Marine Protected Area-Based Decision Tree

    The Marine Protected Area-Based Decision Tree uses spatially explicit, easy to gather catch and age-length data to set and further refine total allowable catch. Additionally, data gathered from inside no-take marine protected areas (MPAs) are used as a baseline for an unfished population. Model inputs are life-history characteristics such as size and age at maturity and natural mortality, catch-per-unit effort (CPUE) information, and age-length data collected from inside and outside marine reserves. Total allowable catch (TAC) is calculated using the current CPUE and target CPUE levels, and then further adjusted with each successive step of the decision tree. Although the MPA-Based Decision Tree allows managers to set and refine TAC, the model assumes populations within MPAs are representative of an unfished baseline. Also, because marine reserves are usually relatively small compared to fishing grounds, care must be taken when extrapolating results to areas that are significantly larger than the MPAs used as reference areas.

    Inputs:

    • Life-history characteristics such as size and age at maturity and natural mortality rate (M)
    • Fishery-independent monitoring of catch-per-unit-effort (CPUE) by size class, OR age-length data collected from inside and outside a well-enforced marine protected area (MPA)
    • Current catches or running average can be used to set initial (hypothetical) Total Allowable Catch (TAC) for decision tree

    Input Sensitivities:

    • Accuracy of individual fish length measurements
    • Accuracy of length-at-age relationships
    • Accuracy of the mean generation time of the target from FishBase

    Outputs:

    • Total Allowable Catch (TAC)

    Assumptions:

    • Habitat quality and productivity is similar inside and outside of MPA for sampled areas
    • Populations within MPA are representative of unfished populations (i.e., MPA is old enough and well-enforced enough for fish populations to have equilibrated to unfished conditions)
    • Results from relatively small MPAs can be extrapolated to generally much larger fishing areas

    Reference points:

    • Proxy reference point to size-specific catch rate (inside/outside no-take zone), as a reference value to control F
    • Size-specific CPUE reserve : CPUE fished

    Recommendations:

     

    Fishing mortality is adjusted through harvest control methods (e.g. TAC or spatial closures) based on how far apart these values are from TRP & LRP for OFL.

    Catch-MSY

    The Catch-MSY assessment method uses a time series of removals (catch plus discards), estimated ranges of stock size in the first and final years of the catch data, and life history information to calculate Maximum Sustainable Yield (MSY). The method assumes population growth and carrying capacity do not change over time.

    Inputs:

    • Catch time series (including discards)
    • Estimated ranges of stock size in the first and final years of catch data (Binitial and Bfinal)
    • Life history information (i.e. r and K growth rates)

    Input Sensitivities:

    • r and K are assumed to be constant
    • Biomass as to be a fraction of the carrying capacity at both the beginning and end of the time series of catch data and the growth rate
    • Based on Schaefer surplus production model, the overall effects of recruitment, growth, and mortality are pooled into a single production function

    Outputs:

    • Maximum Sustainable Yield (MSY)

    Assumptions:

    • Population growth and carrying capacity do not change over time
    • Catch is known without error
    • Stock is undifferentiated (no age, size, or gender differences)
    • Only a narrow range of r-K combinations can maintain the population
    • Population does not collapse or exceed the carrying capacity
    • Ignores the age structure of the stock and does not consider individual growth, recruitment, or the vulnerability of the fish to the fishing gear

    Reference points:

    • Stock status based reference point to estimate sustainable yield, as a reference value to control F
    • MSY is calculated as:
    • MSY=r*k/4
    • BMSY =k/2
    • FMSY =r/2

    Recommendations: 

    Fishing mortality is adjusted through harvest control methods (e.g. catch limits, seasons, or spatial closures) based on how far apart these values are from TRP & LRP for OFL.