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Translational ecology defines a collaborative effort among scientists and stakeholders to rapidly translate environmental problems into action. This approach can be applied in a fisheries management context when information needed to inform regulations is unavailable, yet conservation concerns exist. Our research uses a translational ecology framework to assess the stock status and develop research priorities for the crevalle jack (Caranx hippos) in the Florida Keys, USA, a currently unregulated species. Interview data that compiled expert fishing guide knowledge were used to develop hypotheses tested using existing fisheries-dependent datasets to check for agreement among sources and assess the consistency of observed patterns. Six hypotheses were developed concerning the status and trends of the crevalle jack population in the Florida Keys, and four of these hypotheses received clear support, with agreement between guide observations and one or more of the fisheries-dependent datasets. The results of our study outline an effective translational ecology approach for recreational fisheries management designed to rapidly recognize potential management needs as identified by fishing guides, which allows for actionable science and proactive management. 

ABSTRACT Using deep images from the Hyper Suprime-Cam (HSC) survey and taking advantage of its unprecedented weak lensing capabilities, we reveal a remarkably tight connection between the stellar mass distribution of massive central galaxies and their host dark matter halo mass. Massive galaxies with more extended stellar mass distributions tend to live in more massive dark matter haloes. We explain this connection with a phenomenological model that assumes, (1) a tight relation between the halo mass and the total stellar content in the halo, (2) that the fraction of in situ and ex situ mass at r <10 kpc depends on halo mass. This model provides an excellent description of the stellar mass functions (SMFs) of total stellar mass ($M_{\star }^{\mathrm{max}}$) and stellar mass within inner 10 kpc ($M_{\star }^{10}$) and also reproduces the HSC weak lensing signals of massive galaxies with different stellar mass distributions. The best-fitting model shows that halo mass varies significantly at fixed total stellar mass (as much as 0.4 dex) with a clear dependence on $M_{\star }^{10}$. Our two-parameter $M_{\star }^{\mathrm{max}}$–$M_{\star }^{10}$ description provides a more accurate picture of the galaxy–halo connection at the high-mass end than the simple stellar–halo mass relation (SHMR) and opens a new window to connect the assembly history of haloes with those of central galaxies. The model also predicts that the ex situ component dominates the mass profiles of galaxies at r < 10 kpc for log M⋆ ≥ 11.7. The code used for this paper is available online https://github.com/dr-guangtou/asap 

Although photometric redshifts (photo-z’s) are crucial ingredients for current and upcoming large-scale surveys, the high-quality spectroscopic redshifts currently available to train, validate, and test them are substantially non-representative in both magnitude and colour. We investigate the nature and structure of this bias by tracking how objects from a heterogeneous training sample contribute to photo-z predictions as a function of magnitude and colour, and illustrate that the underlying redshift distribution at fixed colour can evolve strongly as a function of magnitude. We then test the robustness of the galaxy–galaxy lensing signal in 120 deg2 of HSC–SSP DR1 data to spectroscopic completeness and photo-z biases, and find that their impacts are sub-dominant to current statistical uncertainties. Our methodology provides a framework to investigate how spectroscopic incompleteness can impact photo-z-based weak lensing predictions in future surveys such as LSST and WFIRST.