ABSTRACTRationaleClosely related whale species can appear similar yet occupy distinct ecological niches. Sato's beaked whale (Berardius minimus) was only recently recognized as a separate species and was previously grouped with Baird's beaked whale (Berardius bairdii), limiting our understanding of their ecological differences. Clarifying their trophic ecology is essential for accurate species‐specific conservation and management.MethodsSkin biopsy and necropsy samples of B. bairdii and B. minimus were collected in the western North Pacific in 2017–2025. Carbon (δ13C) and nitrogen (δ15N) stable isotope ratios were measured from three separately analyzed epidermal layers of skin samples using isotope ratio mass spectrometry.ResultsB. bairdii exhibited significantly higher δ13C values than B. minimus, whereas δ15N values were broadly similar, indicating comparable trophic positions but distinct foraging habitats. Higher δ13C values in B. bairdii suggest greater reliance on benthic or coastal food webs, whereas lower δ13C values in B. minimus reflect stronger associations with offshore ecosystems. Isotopic variation of different epidermal layers revealed temporal dietary shifts within individuals.ConclusionsThese results demonstrate clear ecological differentiation between B. bairdii and the recently described B. minimus. Historical data attributed to B. bairdii should be re‐evaluated to ensure accurate species‐specific interpretations of diet and habitat use, improving ecological understanding and conservation assessments.

ABSTRACT Rationale Portable mass spectrometry systems such as miniRUEDI enable rapid and low‐cost field analysis of dissolved gases with high temporal resolution. However, they remain poorly suited for discrete small‐volume water samples. This study presents an approach based on passive sampling for groundwater and surface waters dissolved gases and gas tracer analyses. Methods Passive samplers (≈25 mL) were deployed in near‐air‐saturated water for several days to equilibrate with dissolved gases. After retrieval and locking, gas samples were analysed in the laboratory using the miniRUEDI portable mass spectrometry combined with gas chromatography–electron capture detection (GC‐ECD). Results The combined miniRUEDI and GC‐ECD approach enabled reliable and simultaneous measurements of major gases (N 2 and O 2 ), noble gases (He, Ar and Kr), and transient tracers including SF 6 , CFC‐12 and CFC‐113 from a single 25 mL gas sample. The time required for complete equilibration within the passive samplers was found to be approximately 2 days. Conclusions This method extends portable mass spectrometry to discrete low‐volume water samples and facilitates the use of transient anthropogenic gas tracers for determining young groundwater ages (< 70 years). Its simplicity, low cost and multi‐gas capability also make it promising for tracer plume mapping and environmental monitoring applications.

ABSTRACTRationaleLyon and coworkers demonstrated that multiple random fragmentation events can bias intensity distributions toward smaller terminal fragment ions. With any high‐yield method of dissociation, such as high‐energy collisional activation, this phenomenon can greatly influence the intensity distribution of product ions in MS/MS spectra. Previously, multiple fragmentation events were simulated with computationally intensive stochastic studies. The goal of this work is to provide a mathematical model that explains the results obtained from computational stochastic studies.MethodsWe present a probabilistic model that predicts terminal and internal product ion intensities based on polypeptide size and the number of fragmentation events. This model is validated by demonstrating convergence with the previous stochastic model and described that the intensity trend from smaller fragments to larger fragments follows the probability of multiple fragmentation events on peptide backbone.ResultsUnder the stated assumptions, the analytical expressions formally demonstrate that the “missing middle” is a necessary mathematical consequence of multiple fragmentation events, and they reproduce the stochastic simulation results with exact agreement while reducing computation time from hours to less than 1 s. Our method consistently offers greater accuracy and mathematically proves the mechanistic necessity of “missing middle” phenomenon in top‐down MS. The abundances of fragments from stochastic simulation distribute around the average value calculated by the probability formula within twofold coefficient variance (%CV).ConclusionThe closed‐form probability expressions accurately describe the combinatorial consequences of multiple fragmentation events under the stated assumptions. Because they are computationally inexpensive and differentiable, these expressions could be integrated with sequence‐dependent fragmentation propensities in future machine learning models for MS/MS spectral prediction.