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24Habitat use and distribution is a critical aspect in the management and conservation of a species, shortcomings of conventional HSIs: 1) the abundance indices from survey catch data typically 58 incorporated in these models do not account for changes in catchability over a time series; and 2) 59 the commonly used abundance indices, and therefore HSIs, are unable to incorporate surveys 60 from multiple gear types which sample different segments of the population and likely cover 61 different types of habitat. These issues need to be addressed in order to produce an unbiased 62 evaluation of spatio-temporal changes in habitat quality for a species over its distributional 63 range. Conventional HSIs use available data from sampled locations, hereinafter referred to as sample- 78based HSIs, which are often restricted to the locations of occurrence and typically processed to 79 assume that the samples are representative (i.e., the species is effectively sampled) and are 80 comparable through time (i.e., no changes in sampling distribution and efficiency). Therefore, 81 the sample-based HSIs might not be appropriate in at least the following two situations: 1) the 82 survey misses a significant portion or type of the species' habitat; and 2) sampling efficiency 83 (i.e., catchability) changes over space and/or through time due to density-dependent processes. 84Density-dependent habitat selection is a likely process for species in decline (MacCall 1990). 85When a species population is high, individuals move into previously marginal habitat because 86 high quality habitat is saturated; thus, the overall suitability of all occupied habitat declines on 87 average (MacCall 1990 Cusk (Brosme brosme) in the Gulf of Maine is one species where assessment is difficult using 104 conventional HSIs. It is a data-limited species, with low abundance and low catchability. central GOM to better sample species that primarily reside in complex habitat (Hoey et al. 2013). 146Six survey strata were selected for the LLS from ten offshore and four inshore strata from the The study area was divided into 5,710 cells (0.05º x 0.05º) for predicting grid-based densities, The second stage of the model approximates positive catches (c): 199The probability density function Gamma (c, x, y) is evaluated at c given a gamma distribution, knots that are generated based on the proportional density of survey data over the defined 208 domain (i.e., the 0.05º x 0.05º grid; Thorson et al. 2015). The spatial (ω) and spato-temporal (ε) 209 random effects were used in both spring and fall density estimates. 211Encounter probability p and positive catch rates λ are approximated using linear predictors 212( Thorson et al. 2015): 215where ‫‬ and ߣ are the expected probabilities of an occupied habitat and positive catches given 216 occupied habitat for sample i at a given location; ݀ ் () is the average reference density 217(encounters/positive catch rates) in year ܶ () ; ܳ is catchability for each survey; w i is the area 218 swept for sample i;...

At a time when society appears mistrustful of science, it is critical to understand how scientific credibility is evaluated. Scientists often view the peer review process as establishing the credibility of their science, operating under the assumption that sound design and rigorous analysis stand alone. However, scientific knowledge is sometimes rejected by the very stakeholder groups that it is intended to serve. To understand how fisheries stakeholders assess scientific credibility, marine resource stakeholders from Maine were asked to discuss perceptions of credible science. Text analysis of six small group conversations revealed that stakeholders evaluate credibility based on communication style, relationships, and relatability. These attributes are self‐reinforcing and are influenced by transparency. We present examples of how efforts to promote transparency and trust can be incorporated into scientists’ stakeholder engagement strategies and propose that researchers consider these commitments within their respective fields before they design and implement scientific projects, so they may be assigned greater credibility outside of the scientific community.

Bycatch remains a global problem in managing sustainable fisheries. A critical aspect of management is understanding the timing and spatial extent of bycatch. Fisheries management often relies on observed bycatch data, which are not always available due to a lack of reporting or observer coverage. Alternatively, analyzing the overlap in suitable habitat for the target and non-target species can provide a spatial management tool to understand where bycatch interactions are likely to occur. Potential bycatch hotspots based on suitable habitat were predicted for cusk Brosme brosme incidentally caught in the Gulf of Maine American lobster Homarus americanus fishery. Data from multiple fisheries-independent surveys were combined in a delta-generalized linear mixed model to generate spatially explicit density estimates for use in an independent habitat suitability index. The habitat suitability indices for American lobster and cusk were then compared to predict potential bycatch hotspot locations. Suitable habitat for American lobster has increased between 1980 and 2013 while suitable habitat for cusk decreased throughout most of the Gulf of Maine, except for Georges Basin and the Great South Channel. The proportion of overlap in suitable habitat varied interannually but decreased slightly in the spring and remained relatively stable in the fall over the time series. As Gulf of Maine temperatures continue to increase, the interactions between American lobster and cusk are predicted to decline as cusk habitat continues to constrict. This framework can contribute to fisheries managers’ understanding of changes in habitat overlap as climate conditions continue to change and alter where bycatch interactions could occur.