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laurie

laurie

Recently Published

Operating Mocdel
Length Based Methods
JABBAt
Length Base Methods
CAPAM Diagnostic Workshop: Hiundcasting
There two ways to conduct a hindcast based either on observations, i.e. crossvalidation, or model estimates, e.g. as a backtest. While there are three reasons for doing so, namely to find the "best assessment", select and weight models in an ensemble, or condition Operating and Observation Error Models when conducting Management Strategy Evaluation. We review how stock assessment models are currently validated, summarise the use of the hindcast by the RMFOs, and propose how to adopt hindcasting as an objective approach for selecting, screening and weighting hypotheses.
Allee Effects
Impact of Allee effects on reference points
Conditioning simulation models on life history relationships: Length Based Indicators and Methods
Simulation testing of length-based methods, using Operating Models based on life history relationships
length simulations
Lengt
Length Based Indicators
Evaluation of LBIs for detecting overfishing and recovery.
clinate scenarios
Atlantic Bigeye
Atlantic Yellowfin
Document
Performance Metrics
Examples of processing MSE outputs
Western Mediterranean Hake
Summary
NEA Mackerel Stock Recruitment Relationships
Beverton and Holt Stock Recruitment Relationships with two regimes, variable $SPR_0$ and autocorrelation.
mackerel refpts
Tuna RFMO Stock Trends
Selected tuna RFMO stock trends relative to BMSY
Evaluation of Catch-Only Models using the RAM Legacy DB
The RAM DB is used to generate data poor time series and then JABBA configured as a catch-only model is used to estimate final depletion. Results are then compared using Receiver Operator Characteristics
r Priors
Derivation of priors for population growth rate, based on the Leslie matrix using life history parameters
RAM Legacy Database Time Series
Summary of the data used to evaluate the catch-only models
COMs
NEA Mackerel Reference Points
A comparison of reference points from the Operating Model and eqsim.
Western Horse Mackerel Reference Points
A comparison of reference points estimated by SS3, for different values of steepness and natural mortality, with those estimated by msy-tools
albio2
albio2
results from MSE
ALBIO MSE
Full set of plots
albio-mse
FAO Priors
FAO-VoI
Summary of data in RAM Legacy database
ALBIO Grid
VoI for COMs
Examples for WKGMSE3
Review of tRFMO MSE
Empirical MP
Example of an empirical control rule developed using Machine Learning
mydas examples for WKLIFEX
Examples of screening indicators, and using machine learning to conduct MSE
TEAMFish
Benchmarking
ICCAT Subcommittee on Ecosystems: 2020
Validation and Screening of Indicators: Sargasso Sea Case Study
Sargasso Sea Case Study: EBFM
2020 ICCAT SUB-COMMITTEE ON ECOSYSTEM MEETING 4-6 May 2020
Pareto
Use Pareto Fronts to evaluate trade-offs
ERM
Turbot v Brill
Comparison of the dynamics of a low k stock (turbot) with a high k stock (brill)
Paretos
Multiple trade-offs
Multi Objectives
Pareto Plots to show trade-offs
MyDas MSE
MyDas Observation Error Model
MyDas Turbot Operating Model
MyDas 12 Monthly Meeting
Update on work conducted under MyDas
test
empp
emp-d
emp-d
derivative mp
emp-p
proportional
emp-d
Plot x vy
XvY
emp-p
emp-p runs
parameters for empd
r
k
ray MSE
acceptance plot
acceptance
Pass Plot
summary plot
Abacore
glmnet
Plot
MyDas Time Series Analysis
The cross correlations between recruitment and catch for a Cat 1 control rule
The cross correlations are plotted for negative lags between recruitment and catch, i.e. for lobster high catches occur 6 years after a strong recruitment, while for sprat they occur after 2 years. The hypothesis is that the performance of a harvest control is determined by the variability in recruitment and the lag between catch and recruitment, rather than the life history parameters and the production function. This can be tested by simulating stocks with different life history parameters and natural mortality vectors and various recruitment scenarios, then comparing the performance of the control rules
MyDas WKLIFE 2018
Mydas Presentation at WKLife
MyDas WKLIFE 2018
Summary of the MyDas project. MyDas is funded by the Irish exchequer and EMFF 2014-2020, and the overall aim is to develop and test a range of assessment models and methods to establish Maximum Sustainable Yield (MSY), or proxy MSY reference points across the spectrum of data-limited stocks.
Plot
mey
Plot
gislason
Plot
lh
Plot
life hist
Projection for constant F
Simulation of long-term constant Fishing Mortality to compare dynamic projections with equilibrium. Fs are for a range of per recruit reference points.
SSC SC-ECO
FLife
FLife Vignette
Elasticities 3
Elasticities 2
Elasticities
Elasticities
OM iter 2
OM iter 1
VPA Course
GBYP
Length indicator
Plot P(L>Lmega)
Proportion of stock>Lmega, i.e. save the BOFFs
Plot of P(L<LMat)
Indicator based on proportion of stock below Length at Maturity
Simulated Stock
A large pelagic that was originally at virgin, then expoited increasingly heavily over 100 years
tRFMO MSE
VPA Course
The Kobe Advice Framework
Publish Document
tentative course outline
Publish Document
Kobe Vignette
Publish Plot
Publish Plot
Publish Plot
test
Publish Plot
dl/dt by days at liberty