scholarly journals Self-starting cumulative sum harvest control rule (SS-CUSUM-HCR) for status-quo management of data-limited fisheries

2016 ◽  
Vol 73 (3) ◽  
pp. 366-381 ◽  
Author(s):  
Deepak George Pazhayamadom ◽  
Ciarán J. Kelly ◽  
Emer Rogan ◽  
Edward A. Codling
Keyword(s):  
Time Series ◽  
Temporal Trends ◽  
Status Quo ◽  
Reference Points ◽  
Fish Stock ◽  
Cumulative Sum ◽  
Total Allowable Catch ◽  
Control Rule ◽  
Wide Range ◽  
Harvest Control Rule

We demonstrate a harvest control rule based on the self-starting cumulative sum (SS-CUSUM) control chart that can maintain a fish stock at its starting (status-quo) level. The SS-CUSUM is an indicator monitoring tool commonly used in quality control engineering and does not require a long time series or predefined reference point for detecting temporal trends. The reference points in SS-CUSUM are calibrated in the form of running means that are updated on an ongoing basis when new observations become available. The SS-CUSUM can be initiated with as few as two observations in the time series and can be applied long before many other methods, soon after initial data become available. A wide range of stock indicators can be monitored, but in this study, we demonstrate the method using an equally weighted sum of two indicators: a recruitment indicator and a large fish indicator from a simulated fishery. We assume that no life history data are available other than 2 years of both indicator data and current harvest levels when the SS-CUSUM initiates. The signals generated from SS-CUSUM trigger a harvest control rule (SS-CUSUM-HCR), where the shift that occurs in the indicator time series is computed and is used as an adjustment factor for updating the total allowable catch. Our study shows that the SS-CUSUM-HCR can maintain the fish stock at its starting status-quo level (even for overfished initial states) but has limited scope if the fishery is already in an undesirable state such as a stock collapse. We discuss how the SS-CUSUM approach could be adapted to move beyond a status-quo management strategy, if additional information on the desirable state of the fishery is available.

scholarly journals Linking the performance of a data-limited empirical catch rule to life-history traits

2020 ◽  
Vol 77 (5) ◽  
pp. 1914-1926
Author(s):  
Simon H Fischer ◽  
José A A De Oliveira ◽  
Laurence T Kell
Keyword(s):  
Time Series ◽  
Life History ◽  
Life Histories ◽  
Life History Traits ◽  
Growth Parameter ◽  
Reference Points ◽  
Total Allowable Catch ◽  
Fish Stocks ◽  
Wide Range ◽  
Spawning Stock

Abstract Worldwide, the majorities of fish stocks are data-limited and lack fully quantitative stock assessments. Within ICES, such data-limited stocks are currently managed by setting total allowable catch without the use of target reference points. To ensure that such advice is precautionary, we used management strategy evaluation to evaluate an empirical rule that bases catch advice on recent catches, information from a biomass survey index, catch length frequencies, and MSY reference point proxies. Twenty-nine fish stocks were simulated covering a wide range of life histories. The performance of the rule varied substantially between stocks, and the risk of breaching limit reference points was inversely correlated to the von Bertalanffy growth parameter k. Stocks with k>0.32 year−1 had a high probability of stock collapse. A time series cluster analysis revealed four types of dynamics, i.e. groups with similar terminal spawning stock biomass (collapsed, BMSY, 2BMSY, 3BMSY). It was shown that a single generic catch rule cannot be applied across all life histories, and management should instead be linked to life-history traits, and in particular, the nature of the time series of stock metrics. The lessons learnt can help future work to shape scientific research into data-limited fisheries management and to ensure that fisheries are MSY compliant and precautionary.

Optimal shape of the harvest control rule for different fishery management objectives

2020 ◽  
Author(s):  
Tatsunori Yagi ◽  
Takashi Yamakawa
Keyword(s):  
Fisheries Management ◽  
Fishery Management ◽  
Optimal Shape ◽  
Reference Points ◽  
Control Rule ◽  
Management Objectives ◽  
Harvest Control Rule ◽  
Optimal Values ◽  
Average Catch ◽  
Stock Collapse

Abstract To determine the optimal shape of the harvest control rule (HCR) achieving common fisheries management objectives (maximizing the average catch, reducing the deviation of yields, and avoiding stock collapse) and ensure robustness to observation errors, we estimate the optimal values of biological reference points (BRPs) composing the HCR. While traditional HCRs usually consist of three BRPs based on the fishing mortality coefficient (F3-HCR), we introduce an alternative HCR defined by 21 BRPs based on the catch levels (C21-HCR) to cover various possible shapes of HCR including smooth ones. We compare the shape and the performance between the optimal C21-HCR and the optimal F3-HCR and conclude that the optimal HCR can be composed of the gradual combination of the basic strategies: the constant escapement strategy, the constant harvest rate (CHR) strategy, and the constant catch strategy. However, the current F3-HCR does not necessarily allow this combination and generally returns lower performance levels than the optimal C21-HCR (since the basic strategy is confined to CHR) excluding the range of low biomass. This result will provide a clear perspective to improve HCR according to the magnitude of assessment errors and to compromise multiple fisheries management objectives when various stakeholders are involved.

scholarly journals Evaluating a harvest control rule to improve the sustainability of Japanese fisheries

2020 ◽  
Author(s):  
Hiroshi Okamura ◽  
Momoko Ichinokawa ◽  
Ray Hilborn
Keyword(s):  
Management Strategy ◽  
Turning Point ◽  
Reference Points ◽  
Control Rule ◽  
Strategy Evaluation ◽  
Management Procedure ◽  
The World ◽  
Harvest Control Rule ◽  
Stock Recruitment ◽  
Future Status

AbstractFisheries management in Japan is currently at a turning point. MSY based reference points have historically been rejected because of impacts on the fishing industry that would result from their adoption. We propose and evaluate a new harvest control rule (HCR) that uses the biological reference points based on sustainable yield from the stochastic hockey-stick stock recruitment relationship. Management strategy evaluation simulations conditioned on data from Japanese stocks demonstrate that the new HCR avoided recruitment overfishing while providing stable and near maximum catch. The new HCR outperformed Japan’s traditional HCR in terms of conservation, and it outperformed an alternative HCR which is widely used around the world in terms of initial catch reduction and future catch variation. For forecasting and hindcasting simulations, the new HCR showed considerable improvements over traditional HCRs in terms of biomass and catch. This new management procedure can improve the current and future status of many overfished stocks in Japan as well as increase economic efficiency and better protect ecosystems.

scholarly journals Subjective judgement in data subsetting: implications for CPUE standardisation and stock assessment of non-target chondrichthyans

2011 ◽  
Vol 62 (6) ◽  
pp. 734 ◽  
Author(s):  
J. M. Braccini ◽  
M.-P. Etienne ◽  
S. J. D. Martell
Keyword(s):  
Ad Hoc ◽  
Stock Assessment ◽  
Fishing Effort ◽  
Reference Points ◽  
Fish Stock ◽  
Model Parameters ◽  
Total Allowable Catch ◽  
Subjective Judgement ◽  
Definition Of ◽  
Catch Per Effort

Standardisation of catch-per-effort (CPUE) data is an essential component for nearly all stock assessments. The first step in CPUE standardisation is to separate the comparable from the non-comparable catch and effort records and this is normally done based on subjective rules. In the present study, we used catch-and-effort data from the elephant fish (Callorhinchus milii) to illustrate the differences in CPUE when using expert judgement to define different ad hoc selection criteria used to subset these data. The data subsets were then used in the standardisation of CPUE and the stock assessment of elephant fish. The catch-and-effort subsets produced different patterns of precision and trends, each of which led to different estimates (and related uncertainty) of model parameters and management reference points. For most CPUE series, there was a very high probability that the elephant fish stock is overexploited and that overfishing is occurring. The estimates of total allowable catch (TAC) and the uncertainty around these estimates also varied considerably depending on the CPUE series used. Our study shows how sensitive TAC estimation is when there is high uncertainty in the definition of the fishing effort targeted at the species analysed.

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

scholarly journals 1120. Impact of Training Residents to Improve HIV Screening in a Teaching Hospital in Mexico City

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S590-S590
Author(s):  
Lorena Guerrero-Torres ◽  
Isaac Núñez-Saavedra ◽  
Yanink Caro-Vega ◽  
Brenda Crabtree-Ramírez
Keyword(s):  
Emergency Department ◽  
Time Series ◽  
Hiv Testing ◽  
Teaching Hospital ◽  
Educational Intervention ◽  
Temporal Trends ◽  
Hiv Screening ◽  
Hiv Diagnosis ◽  
Post Intervention ◽  
Hiv Test

Abstract Background Among 230,000 people living with HIV in Mexico, 24% are unaware of their diagnosis, and half of newly diagnosed individuals are diagnosed with advanced disease. Early diagnosis is the goal to mitigate HIV epidemic. Missed opportunities may reflect a lack of clinicians’ consideration of HIV screening as part of routine medical care. We assessed whether an educational intervention on residents was effective to 1) improve the knowledge on HIV screening; 2) increase the rate of HIV tests requested in the hospitalization floor (HF) and the emergency department (ED); and 3) increase HIV diagnosis in HF and ED. Methods Internal Medicine and Surgery residents at a teaching hospital were invited to participate. The intervention occurred in August 2018 and consisted in 2 sessions on HIV screening with an expert. A questionnaire was applied before (BQ) and after (AQ) the intervention, which included HIV screening indications and clinical cases. The Institutional Review Board approved this study. Written informed consent was obtained from all participants. BQ and AQ scores were compared with a paired t-test. To evaluate the effect on HIV test rate in the HF and ED, an interrupted time series analysis was performed. Daily rates of tests were obtained from September 2016 to August 2019 and plotted along time. Restricted cubic splines (RCS) were used to model temporal trends. HIV diagnosis in HF and ED pre- and post-intervention were compared with a Fisher’s exact test. A p&lt; 0.05 was considered significant. Results Among 104 residents, 57 participated and completed both questionnaires. BQ score was 79/100 (SD±12) and AQ was 85/100 (SD±8), p&lt; .004. Time series of HIV testing had apparent temporal trends (Fig 1). HIV test rate in the HF increased (7.3 vs 11.1 per 100 episodes) and decreased in the ED (2.6 vs 2.3 per 100 episodes). HIV diagnosis increased in the HF, from 0/1079 (0%) pre-intervention to 5/894 (0.6%) post-intervention (p&lt; .018) (Table 1). Fig 1. HIV test rates. Gray area represents post-intervention period. Table 1. Description of episodes, HIV tests and rates pre- and post-intervention in the Emergency Department and Hospitalization Floor. Conclusion A feasible educational intervention improved residents’ knowledge on HIV screening, achieved maintenance of a constant rate of HIV testing in the HF and increased the number of HIV diagnosis in the HF. However, these results were not observed in the ED, where administrative barriers and work overload could hinder HIV screening. Disclosures All Authors: No reported disclosures

scholarly journals GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses

2019 ◽  
Vol 12 (11) ◽  
pp. 4661-4679 ◽  
Author(s):  
Bin Cao ◽  
Xiaojing Quan ◽  
Nicholas Brown ◽  
Emilie Stewart-Jones ◽  
Stephan Gruber
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Ground Surface ◽  
Reanalysis Data ◽  
Meteorological Variables ◽  
Ensemble Simulations ◽  
Driving Time ◽  
Wide Range ◽  
Global Coverage ◽  
Uncertain Input

Abstract. Simulations of land-surface processes and phenomena often require driving time series of meteorological variables. Corresponding observations, however, are unavailable in most locations, even more so, when considering the duration, continuity and data quality required. Atmospheric reanalyses provide global coverage of relevant meteorological variables, but their use is largely restricted to grid-based studies. This is because technical challenges limit the ease with which reanalysis data can be applied to models at the site scale. We present the software toolkit GlobSim, which automates the downloading, interpolation and scaling of different reanalyses – currently ERA5, ERA-Interim, JRA-55 and MERRA-2 – to produce meteorological time series for user-defined point locations. The resulting data have consistent structure and units to efficiently support ensemble simulation. The utility of GlobSim is demonstrated using an application in permafrost research. We perform ensemble simulations of ground-surface temperature for 10 terrain types in a remote tundra area in northern Canada and compare the results with observations. Simulation results reproduced seasonal cycles and variation between terrain types well, demonstrating that GlobSim can support efficient land-surface simulations. Ensemble means often yielded better accuracy than individual simulations and ensemble ranges additionally provide indications of uncertainty arising from uncertain input. By improving the usability of reanalyses for research requiring time series of climate variables for point locations, GlobSim can enable a wide range of simulation studies and model evaluations that previously were impeded by technical hurdles in obtaining suitable data.

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