Comparing trophic position estimates using bulk and compound specific stable isotope analyses: applying new approaches to mackerel icefish Champsocephalus gunnari.

Quantifying the tropic position (TP) of an animal species is key to understanding its ecosystem function. While both bulk and compound-specific analyses of stable isotopes are widely used for this purpose, few studies have assessed the consistency between and within such approaches. Champsocephalus gunnari is a specialist teleost that predates almost exclusively on Antarctic krill Euphausia superba. This well-known and nearly constant trophic relationship makes C. gunnari particularly suitable for assessing consistency between TP methods under field conditions. In the present work, we produced and compared TP estimates for C. gunnari and its main prey using a standard bulk and two amino acid-specific stable isotope approaches (CSI-AA). One based on the difference between glutamate and phenylalanine (TPGlx-Phe), and the other on the proline-phenylalanine difference (TPPro-Phe). To do that, samples from C. gunnari, E. superba and four other pelagic invertebrate and fish species, all potential prey for C.gunnari, were collected off the South Orkney Islands between January and March 2019, analyzed using standard isotopic ratio mass spectrometry methods and interpreted following a Bayesian approach. Median estimates (CI95%) for C. gunnari were similar between TPbulk (3.6; CI95%: 3.0-4.8) and TPGlx-Phe(3.4; CI95%:3.2-3.6), and lower for TPPro-Phe (3.1; CI95%:3.0-3.3). TP differences between C. gunnari and E. superba were 1.4, 1.1 and 1.2, all compatible with expectations from the monospecific diet of this predator (ΔTP=1). While these results suggest greater accuracy for Glx-Phe and Pro-Phe, differences observed between both CSI-AA approaches suggests these methods may require further validation before becoming a standard tool for trophic ecology.

Modelling the Spatial and Temporal Dynamics of Paralytic Shellfish Toxins (PST) at Different Scales: Implications for Research and Management.

Harmful algal blooms, in particular recurrent blooms of the dinoflagellate Alexandrium catenella, associated with paralytic shellfish poisoning (PSP), frequently limit commercial shellfish harvests, resulting in serious socio-economic consequences. Although the PSP-inducing species that threaten the most vulnerable commercial species of shellfish are very patchy and spatially heterogeneous in their distribution, the spatial and temporal scales of their effects have largely been ignored in monitoring programs and by researchers. In this study, we examined the spatial and temporal dynamics of PSP toxicity in the clam (Ameghinomya antiqua) in two fishing grounds in southern Chile (Ovalada Island and Low Bay). During the summer of 2009, both were affected by an intense toxic bloom of A. catenella (up to 1.1 × 106 cells L-1). Generalized linear models were used to assess the potential influence of different environmental variables on the field detoxification rates of PSP toxins over a period of 12 months. This was achieved using a four parameter exponential decay model to fit and compare field detoxification rates per sampling site. The results show differences in the spatial variability and temporal dynamics of PSP toxicity, given that greater toxicities (+10-fold) and faster detoxification (20% faster) are observed at the Ovalada Island site, the less oceanic zone, and where higher amounts of clam are annually produced. Our observations support the relevance of considering different spatial and temporal scales to obtain more accurate assessments of PSP accumulation and detoxification dynamics and to improve the efficacy of fisheries management after toxic events.

Performance of maximum likelihood mixture models to estimate nursery habitat contributions to fish stocks: a case study on sea bream Sparus aurata.

BACKGROUND: Mixture models (MM) can be used to describe mixed stocks considering three sets of parameters: the total number of contributing sources, their chemical baseline signatures and their mixing proportions. When all nursery sources have been previously identified and sampled for juvenile fish to produce baseline nursery-signatures, mixing proportions are the only unknown set of parameters to be estimated from the mixed-stock data. Otherwise, the number of sources, as well as some/all nursery-signatures may need to be also estimated from the mixed-stock data. Our goal was to assess bias and uncertainty in these MM parameters when estimated using unconditional maximum likelihood approaches (ML-MM), under several incomplete sampling and nursery-signature separation scenarios. METHODS: We used a comprehensive dataset containing otolith elemental signatures of 301 juvenile Sparus aurata, sampled in three contrasting years (2008, 2010, 2011), from four distinct nursery habitats. (Mediterranean lagoons) Artificial nursery-source and mixed-stock datasets were produced considering: five different sampling scenarios where 0-4 lagoons were excluded from the nursery-source dataset and six nursery-signature separation scenarios that simulated data separated 0.5, 1.5, 2.5, 3.5, 4.5 and 5.5 standard deviations among nursery-signature centroids. Bias (BI) and uncertainty (SE) were computed to assess reliability for each of the three sets of MM parameters. RESULTS: Both bias and uncertainty in mixing proportion estimates were low (BI ≤ 0.14, SE ≤ 0.06) when all nursery-sources were sampled but exhibited large variability among cohorts and increased with the number of non-sampled sources up to BI = 0.24 and SE = 0.11. Bias and variability in baseline signature estimates also increased with the number of non-sampled sources, but tended to be less biased, and more uncertain than mixing proportion ones, across all sampling scenarios (BI < 0.13, SE < 0.29). Increasing separation among nursery signatures improved reliability of mixing proportion estimates, but lead to non-linear responses in baseline signature parameters. Low uncertainty, but a consistent underestimation bias affected the estimated number of nursery sources, across all incomplete sampling scenarios. DISCUSSION: ML-MM produced reliable estimates of mixing proportions and nursery-signatures under an important range of incomplete sampling and nursery-signature separation scenarios. This method failed, however, in estimating the true number of nursery sources, reflecting a pervasive issue affecting mixture models, within and beyond the ML framework. Large differences in bias and uncertainty found among cohorts were linked to differences in separation of chemical signatures among nursery habitats. Simulation approaches, such as those presented here, could be useful to evaluate sensitivity of MM results to separation and variability in nursery-signatures for other species, habitats or cohorts.

Tide-related biological rhythm in the oxygen consumption rate of ghost shrimp (Neotrypaea uncinata).

The effects of tidal height (high and low), acclimation to laboratory conditions (days in captivity) and oxygen level (hypoxia and normoxia) were evaluated in the oxygen consumption rate (OCR) of the ghost shrimp Neotrypaea uncinata We evaluated the hypothesis that N. uncinata reduces its OCR during low tide and increases it during high tide, regardless of oxygen level or acclimation. Additionally, the existence of an endogenous rhythm in OCR was explored, and we examined whether it synchronized with tidal, diurnal or semidiurnal cycles. Unexpectedly, high OCRs were observed at low tide, during normoxia, in non-acclimated animals. Results from a second, longer experiment under normoxic conditions suggested the presence of a tide-related metabolic rhythm, a response pattern not yet demonstrated for a burrowing decapod. Although rhythms persisted for only 2 days after capture, their period of 12.8 h closely matched the semidiurnal tidal cycle that ghost shrimp confront inside their burrows.