Ecological risk assessments for the effects of fishing: A comparison and validation of PSA and SAFE

Two tools to assess impacts of fisheries on fish species have been developed for use as part of the Ecological Risk Assessment for the Effects of Fishing (ERAEF) toolbox, namely, the Productivity and Susceptibility Analysis (PSA) and the Sustainability Assessment for Fishing Effect (SAFE). Both have been applied to major Australian Commonwealth fisheries and, with various modifications, adopted internationally. However, there has been no formal comparison between the two approaches and no validation against other data-rich assessment methods. Here, we conduct three comparisons: between PSA and SAFE, between PSA, SAFE and Fishery Status Reports (FSR), and between PSA, SAFE and data-rich quantitative stock assessments. PSA and SAFE use similar data. However, PSA typically downgrades quantitative information into an ordinal scale between 1 and 3, whereas SAFE uses the quantitative information as continuous numerical variables in equations at each assessment step. As intended in its original design, PSA is more precautionary toward protecting species, classifying many more species at medium or high risk than SAFE. A comparison with FSR for overfishing classification shows an overall misclassification rate of 27% (26 stocks) by PSA (overestimating risk in all these cases) and 8% (59 stocks) by SAFE (overestimating risk in 3% and underestimating risk in 5% of cases). A comparison with Tier 1 stock assessments (18 stocks) shows an overall misclassification rate of 50% by PSA and 11% by SAFE (all overestimating risk). These comparisons show that the performance of these two ERA tools may deliver the expected benefits in terms of prioritizing high risk species, but, in the case of PSA, the screening may be too precautionary. Validation with more quantitative methods is an important step to guide the further improvement of these important tools.

[1]  Richard D. Methot,et al.  Stock synthesis: A biological and statistical framework for fish stock assessment and fishery management , 2013 .

[2]  Terrance J. Quinn,et al.  Quantitative Fish Dynamics , 1999 .

[3]  N. Graham,et al.  The Influence of Fisher Knowledge on the Susceptibility of Reef Fish Aggregations to Fishing , 2014, PloS one.

[4]  F. Carvalho,et al.  Ecological risk assessment of pelagic sharks caught in Atlantic pelagic longline fisheries , 2010 .

[5]  I. Stobutzki.  Bycatch diversity and variation in a tropical Australian penaeid fishery; the implications for monitoring , 2001 .

[6]  Keith Sainsbury,et al.  A flexible and practical framework for reporting on ecologically sustainable development for wild capture fisheries , 2005 .

[7]  S. Jennings,et al.  Life–history correlates of maximum population growth rates in marine fishes , 2002, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[8]  J. Thorson,et al.  Linking fishing mortality reference points to life history traits: an empirical study , 2012 .

[9]  S. Griffiths,et al.  Sustainability assessment for fishing effects (SAFE) on highly diverse and data-limited fish bycatch in a tropical prawn trawl fishery , 2009 .

[10]  P. Spencer,et al.  An assessment of vulnerability in Alaska groundfish , 2011 .

[11]  D. Milton.  Assessing the susceptibility to fishing of populations of rare trawl bycatch : sea snakes caught by Australia's Northern Prawn Fishery , 2001 .

[12]  S. Sloan,et al.  Status of key Australian fish stocks reports 2012 , 2012 .

[13]  Kelly L. Ames,et al.  An Approach to Defining Stock Complexes for U.S. West Coast Groundfishes Using Vulnerabilities and Ecological Distributions , 2011 .

[14]  F. Micheli,et al.  A risk-based framework for assessing the cumulative impact of multiple fisheries , 2014 .

[15]  Shijie Zhou,et al.  Sustainability Assessment for Fishing Effects (SAFE): A new quantitative ecological risk assessment method and its application to elasmobranch bycatch in an Australian trawl fishery , 2008 .

[16]  D. Milton,et al.  Integrated risk analysis for rare marine species impacted by fishing: sustainability assessment and population trend modelling , 2012 .

[17]  P. Spencer,et al.  Using productivity and susceptibility indices to assess the vulnerability of United States fish stocks to overfishing , 2010 .

[18]  A. L. Jensen.  Beverton and Holt life history invariants result from optimal trade-off of reproduction and survival , 1996 .

[19]  S. J. Metcalf,et al.  An Ecosystem Based Fisheries Management framework: the efficient, regional-level planning tool for management agencies , 2010 .

[20]  Jm Hoenig,et al.  Empirical use of longevity data to estimate mortality rates , 1983 .

[21]  Anthony D. M. Smith,et al.  Quantitative ecological risk assessment for fishing effects on diverse data-poor non-target species in a multi-sector and multi-gear fishery , 2011 .

[22]  Alistair J. Hobday,et al.  Ecological risk assessment for the effects of fishing , 2011 .

[23]  E. Charnov,et al.  Evolutionary assembly rules for fish life histories , 2013 .

[24]  K. Astles,et al.  A qualitative risk-based assessment of impacts on marine habitats and harvested species for a data deficient wild capture fishery , 2009 .

[25]  D. Brewer,et al.  Sustainability of fishery bycatch: a process for assessing highly diverse and numerous bycatch , 2001, Environmental Conservation.

[26]  D. Heales,et al.  Validating ecological risk assessments for fisheries: assessing the impacts of turtle excluder devices on elasmobranch bycatch populations in an Australian trawl fishery , 2006 .

[27]  Zhengyuan Zhu,et al.  Modelling multiple fishing gear efficiencies and abundance for aggregated populations using fishery or survey data , 2014 .