Social-economic drivers in (political) TAC setting decisions

Sustainable use of marine resources, as targeted by Ecosystem-Based Fishery Management (EBFM), is a highly ranked policy goal. However, many marine fish stocks are still overused, challenging sustainability goals. Reasons for this policy failure are disputed and they might be manifold, including economic, institutional, and social drivers. Here, we use Generalised Additive Models (GAMs) to empirically determine and quantify the importance of interacting ecological, economic, and social drivers in a political decision making process, i.e. the setting of annual Total Allowable Catch (TAC) limits. GAMs allow non linear relationships between response and explanatory variables and due to their flexibility have successfully been applied to investigate ecosystem dynamics. Here, we use this modeling approach in a novel way to quantify social-economic-ecological feed-backs on policy decisions. European fisheries policy agreed in most cases to TACs higher than scientifically advised. We recorded this deviation for all managed European fish stocks for the time-series 1987-2014. Additionally, we make use of available time-series of socio-economic and ecological variables potentially influencing the decision, including national unemployment rates, stock status, economic growth rates, and employment in fisheries. We show that political decisions on TACs are not only driven by scientific advice on the ecological state of the stock, but that socio-economic variables have a significant effect on TACs – however not related to sound scientific advice. We conclude that scientific advice for a successful implementation of EBMF will have to address socio- economic driving forces more explicitly

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

<p>Abstract</p> <p>Background</p> <p>The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle.</p> <p>Methods</p> <p>Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models.</p> <p>Results and discussion</p> <p>On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence.</p> <p>Conclusions</p> <p>For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (−maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions.</p