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Abstract Otolith microstructure analysis provides critical biological and ecological information about the early life history of fishes. This information is particularly important to interpret and predict population dynamics for socio‐economically important fisheries species; nonetheless, several key assumptions underpin the use of otolith techniques. The authors validated the use of this analysis for cabezon (Scorpaenichthys marmoratus; Ayres, 1854), a long‐lived, large‐bodied cottid constituent of nearshore fisheries from Baja California, Mexico, to Alaska, USA. To test three critical assumptions, the authors coupled otolith and morphometric analyses from an opportunistic rearing study of cabezon eggs and larvae with a long‐term time series of juvenile cabezon field collections. The authors confirmed the daily otolith increment deposition in laboratory‐reared larvae, identified the timing of first otolith increment deposition and examined the relationship between otolith growth and somatic growth in field‐collected juveniles, validating the use of otolith microstructure analysis in biological and ecological interpretations of early life‐history traits for this species. The findings of this study also indicated that the absorption of yolk‐sac reserves, and likely the transition to exogenous feeding, plays an important role in regulating otolith increment deposition. Finally, the authors found within‐brood size‐at‐age variation, which may be an advantage for young fish in prey‐limited environments. 

Abstract The advent of community-science databases in conjunction with museum specimen locality information has exponentially increased the power and accuracy of ecological niche modeling (ENM). Increased occurrence data has provided colossal potential to understand the distributions of lesser known or endangered species, including arthropods. Although niche modeling of termites has been conducted in the context of invasive and pest species, few studies have been performed to understand the distribution of basal termite genera. Using specimen records from the American Museum of Natural History (AMNH) as well as locality databases, we generated ecological niche models for 12 basal termite species belonging to six genera and three families. We extracted environmental data from the Worldclim 19 bioclimatic dataset v2, along with SoilGrids datasets and generated models using MaxEnt. We chose Optimal models based on partial Receiving Operating characteristic (pROC) and omission rate criterion and determined variable importance using permutation analysis. We also calculated response curves to understand changes in suitability with changes in environmental variables. Optimal models for our 12 termite species ranged in complexity, but no discernible pattern was noted among genera, families, or geographic range. Permutation analysis revealed that habitat suitability is affected predominantly by seasonal or monthly temperature and precipitation variation. Our findings not only highlight the efficacy of largely community-science and museum-based datasets, but our models provide a baseline for predictions of future abundance of lesser-known arthropod species in the face of habitat destruction and climate change.