scholarly journals Comment on “Impacts of historical warming on marine fisheries production”

Science ◽  
2019 ◽  
Vol 365 (6454) ◽  
pp. eaax5721 ◽  
Author(s):  
Cody Szuwalski
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Maximum Sustainable Yield ◽  
Structured Data ◽  
Sea Surface ◽  
Sustainable Yield ◽  
Surplus Production ◽  
Production Models ◽  
Fitting Production ◽  
Age Structured

Free et al. (Reports, 1 March 2019, p. 979) linked sea surface temperature (SST) to surplus production and estimated a 4% decline in maximum sustainable yield (MSY) since 1930. Changes in MSY are expected when fitting production models to age-structured data, so attributing observed changes to SST is problematic. Analyses of recruitment (a metric of productivity in the same database) showed increases in global productivity.

Estimation of maximum sustainable yield of Gelidium robustum seaweed fishery in Mexico

2005 ◽  
Vol 85 (4) ◽  
pp. 775-778 ◽  
Author(s):  
M. Casas-Valdez ◽  
D. Lluch-Belda ◽  
S. Ortega-García ◽  
S. Hernández-Vázquez ◽  
E. Serviere-Zaragoza ◽  
...  
Keyword(s):  
Dynamic Model ◽  
West Coast ◽  
Baja California ◽  
Maximum Sustainable Yield ◽  
Sustainable Yield ◽  
Red Seaweed ◽  
The West ◽  
Surplus Production ◽  
Production Models ◽  
Gelidium Robustum

Surplus production models were used to assess the fishery condition of red seaweed Gelidium robustum off the west coast of the Baja California Peninsula from 1985 to 1997. The maximum sustainable yield and optimum effort estimated by the Schaefer model were 705 tn and 457 teams, while the Fox model estimated 670 tn and 510 teams. The determination coefficients were r2=0·62 for the Fox and r2=0·58 for the Schaefer model. These results suggest that the resource is not overexploited. Fitting the data to Hilborn & Walters' dynamic model was not satisfactory.

Fitting Surplus Production Models: Comparing Methods and Measuring Uncertainty

1993 ◽  
Vol 50 (12) ◽  
pp. 2597-2607 ◽  
Author(s):  
Tom Polacheck ◽  
Ray Hilborn ◽  
Andre E. Punt
Keyword(s):  
Maximum Sustainable Yield ◽  
Parameter Estimates ◽  
Error Estimator ◽  
Sustainable Yield ◽  
Observation Error ◽  
Error Estimators ◽  
Averaging Methods ◽  
Surplus Production ◽  
Production Models ◽  
Process Error

Three approaches are commonly used to fit surplus production models to observed data: effort-averaging methods; process-error estimators; and observation-error estimators. We compare these approaches using real and simulated data sets, and conclude that they yield substantially different interpretations of productivity. Effort-averaging methods assume the stock is in equilibrium relative to the recent effort; this assumption is rarely satisfied and usually leads to overestimation of potential yield and optimum effort. Effort-averaging methods will almost always produce what appears to be "reasonable" estimates of maximum sustainable yield and optimum effort, and the r2 statistic used to evaluate the goodness of fit can provide an unrealistic illusion of confidence about the parameter estimates obtained. Process-error estimators produce much less reliable estimates than observation-error estimators. The observation-error estimator provides the lowest estimates of maximum sustainable yield and optimum effort and is the least biased and the most precise (shown in Monte-Carlo trials). We suggest that observation-error estimators be used when fitting surplus production models, that effort-averaging methods be abandoned, and that process-error estimators should only be applied if simulation studies and practical experience suggest that they will be superior to observation-error estimators.

Bayesian and Related Approaches to Fitting Surplus Production Models

1994 ◽  
Vol 51 (8) ◽  
pp. 1823-1831 ◽  
Author(s):  
John M. Hoenig ◽  
William G. Warren ◽  
Max Stocker
Keyword(s):  
Prior Distribution ◽  
Empirical Bayes ◽  
Fishing Effort ◽  
Maximum Sustainable Yield ◽  
Bayes Estimator ◽  
Production Model ◽  
Sustainable Yield ◽  
Cancer Magister ◽  
Surplus Production ◽  
Production Models

The Schaefer surplus production model relates equilibrium yield to fishing effort and can be fitted using just information on catch and fishing effort. Sometimes, the fitted model predicts a maximum sustainable yield (height of the parabola) that is clearly unrealistic. In this case, one may wish to use prior information on maximum sustainable yield either to constrain the height of the parabola or to provide a prior distribution for Bayesian estimation. To construct a Bayes estimator, one would generally specify a noninformative prior on the residual error variance and, possibly, on the width of the parabola; the prior distribution for height could be obtained by examining fisheries for similar stocks or species on a per unit area basis. Another possibility is to use an empirical Bayes estimator when data from several fisheries (e.g., individual lakes) are available for several years. The methodology is illustrated on catch and effort data for big-eye tuna (Thunnus obesus) and Dungeness crab (Cancer magister). The approach can be extended to other fishery models, including nonequilibrium production models. The prior distribution parameters can be allowed to depend on covariates.

Holocene sea surface temperature variations recorded in corals from Kikai Island, Japan

2017 ◽  
Vol 51 (4) ◽  
pp. e9-e14 ◽  
Author(s):  
Hiroto Kajita ◽  
Atsuko Yamazaki ◽  
Takaaki Watanabe ◽  
Chung-Che Wu ◽  
Chuan-Chou Shen ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Temperature Variations

PENENTUAN DAERAH POTENSIAL BUDIDAYA RUMPUT LAUT KAPPAPHYCUS ALVAREZII DI PROVINSI NUSA TENGGARA TIMUR

2019 ◽  
Vol 3 ◽  
pp. 929
Author(s):  
Marianus Filipe Logo ◽  
N M. R. R. Cahya Perbani ◽  
Bayu Priyono
Keyword(s):  
Dissolved Oxygen ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Kappaphycus Alvarezii ◽  
Sea Surface

Provinsi Nusa Tenggara Timur (NTT) merupakan penghasil rumput laut kappaphycus alvarezii kedua terbesar di Indonesia berdasarkan data Badan Pusat Statistik (2016). Oleh karena itu diperlukan zonasi daerah potensial budidaya rumput laut kappaphycus alvarezii untuk pengembangan lebih lanjut. Penelitian ini bertujuan untuk menentukan daerah yang potensial untuk budidaya rumput laut kappaphycus alvarezii di Provinsi NTT berdasarkan parameter sea surface temperature (SST), salinitas, kedalaman, arus, dissolved oxygen (DO), nitrat, fosfat, klorofil-a, dan muara sungai. Penentuan kesesuaian lokasi budidaya dilakukan dengan memberikan bobot dan skor bagi setiap parameter untuk budidaya rumput laut kappaphycus alvarezii menggunakan sistem informasi geografis melalui overlay peta tematik setiap parameter. Dari penelitian ini diperoleh bahwa kadar nitrat, arus, kedalaman, dan lokasi muara sungai menjadi parameter penentu utama. Jarak maksimum dari bibir pantai adalah sekitar 10 km. Potensial budidaya rumput laut kappaphycus alvarezii ditemukan di Pulau Flores bagian barat, kepulauan di Kabupaten Flores Timur dan Alor, selatan Pulau Sumba, Pulau Rote, dan Teluk Kupang.

EXTREME VALUES OF SEA SURFACE TEMPERATURE ASSOCIATED WITH LONG-PERIOD PHENOMENA OCCURRED DURING 1960-2015 IN THE COLOMBIAN PACIFIC OCEAN

2017 ◽  
Author(s):  
Diaz Juan Navia ◽  
Diaz Juan Navia ◽  
Bolaños Nancy Villegas ◽  
Bolaños Nancy Villegas ◽  
Igor Malikov ◽  
...  
Keyword(s):  
Time Series ◽  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Extreme Values ◽  
Sea Surface ◽  
Absolute Maximum ◽  
Data Set ◽  
Arctic Oscillation Index ◽  
Colombian Pacific

Sea Surface Temperature Anomalies (SSTA), in four coastal hydrographic stations of Colombian Pacific Ocean, were analyzed. The selected hydrographic stations were: Tumaco (1°48'N-78°45'W), Gorgona island (2°58'N-78°11'W), Solano Bay (6°13'N-77°24'W) and Malpelo island (4°0'N-81°36'W). SSTA time series for 1960-2015 were calculated from monthly Sea Surface Temperature obtained from International Comprehensive Ocean Atmosphere Data Set (ICOADS). SSTA time series, Oceanic Nino Index (ONI), Pacific Decadal Oscillation index (PDO), Arctic Oscillation index (AO) and sunspots number (associated to solar activity), were compared. It was found that the SSTA absolute minimum has occurred in Tumaco (-3.93°C) in March 2009, in Gorgona (-3.71°C) in October 2007, in Solano Bay (-4.23°C) in April 2014 and Malpelo (-4.21°C) in December 2005. The SSTA absolute maximum was observed in Tumaco (3.45°C) in January 2002, in Gorgona (5.01°C) in July 1978, in Solano Bay (5.27°C) in March 1998 and Malpelo (3.64°C) in July 2015. A high correlation between SST and ONI in large part of study period, followed by a good correlation with PDO, was identified. The AO and SSTA have showed an inverse relationship in some periods. Solar Cycle has showed to be a modulator of behavior of SSTA in the selected stations. It was determined that extreme values of SST are related to the analyzed large scale oscillations.

On the relation between atmospheric CO2 and equatorial sea-surface temperature

Tellus B ◽  
1987 ◽  
Vol 39 (1-2) ◽  
pp. 171-183 ◽  
Author(s):  
William P. Elliott ◽  
James K. Angell
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Atmospheric Co2
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