The big tuna: length regressions and size estimations of tunas, mackerels, and bonitos (Scombridae) for historical ecology
Year: 2025
Type: article
Abstract: Historical ecology, which often examines how organisms were embedded within past socio-ecological systems, has become a critical approach for understanding long-term change and informing conservation strategies. To integrate historical archives with modern conservation science, historical ecology studies can produce data on important biological metrics, such as body size. Here, we estimated length of tunas ( Thunnus spp.) and their relatives (mackerels and bonitos) from cranial and vertebral measurements by utilizing regression equations. Scombrids (family Scombridae) are key members of pelagic food webs and have been culturally and economically significant for millennia, resulting in extensive historical records for comparison with modern data sets. We measured 73 individuals from Smithsonian Ichthyological Collections with metadata on fork length at capture, spanning all 8 Thunnus species and 5 additional scombrids from tribes Thunnini, Sardini, and Scombrini. We took 2973 measurements across 121 skeletal variables, grouping them into 22 regression models. Of these, 21 models exhibited strong predictive power, with mean errors <10.7%. The most accurate models used width or height of caudal and peduncle vertebrae, with cranial length also a strong predictor. Application of our models to historical Pacific bluefin tuna T. orientalis skeletons from Guadalupe and Santa Catalina Islands ca. AD 1940 reveals a size distribution of 683 to 987 mm in fork length, which is comparable to the size of bluefin caught in the same region between 2008 and 2016 (mean 831 mm). This study advances historical marine ecology by providing robust methods for reconstructing fish size, improving our ability to assess long-term ecological change and inform conservation baselines.
Source: Marine Ecology Progress Series
DOI: 10.3354/meps15015
Authors: Emma A Elliott Smith, Caitlin E Zimmer, Torben C Rick
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Life below water
Open Access status: hybrid
OpenAlex ID: W4415376232