Please cite as: Akiona, Anela K.; Zgliczynski, Brian J.; Sandin, Stuart A. (2021): Data from: Length-weight relationships for 18 coral reef fish species from the central Pacific. UC San Diego Library Digital Collections. Dataset. https://doi.org/10.6075/J0BP02XC Corresponding author: Anela Akiona . https://orcid.org/0000-0002-3457-1966. Scripps Institution of Oceanography Center for Marine Biodiversity and Conservation, University of California, San Diego, La Jolla, CA 92037. Primary associated publication: Akiona, A. K., Zgliczynski, B. J., & Sandin, S. A. (In press). Length-weight relationships for 18 coral reef fish species from the central Pacific. Journal of Applied Ichthyology. Description of contents: Data file: Fish_LW_Data_NLI.csv The associated CSV file contains metadata, length, and weight data for 18 species of coral reef fish collected from the Northern Line Islands from 2006-2011. Methods: Fish were collected during multiple expeditions to the NLI from 2006-2011 using a variety of methods including hand nets, 3-prong spears, spearguns, handlines, fishing poles, and fish anesthetic (see Supplemental Table 1 for expedition details).  Total length (TL) and weight were taken immediately after collection when possible, but in some cases field conditions (e.g., ship-based operations preventing collection of reliable weight estimates) required that specimens be frozen and brought to the laboratory for analysis.  To account for the potential effects of freezing on fish body weight, we compared the fresh weight to thawed weight across taxa for specimens that had both measurements (Ajah & Nunoo, 2003; Florin & Lingman, 2008; Hay, 1984; Ogle, 2009).  Changes in fish weight (g) were expressed in terms of percent weight loss for each specimen and mean percent was calculated for each species. Due to high surface-to-volume ratios, smaller fishes lost a greater proportion of weight during the freezing process.   The change in weight (WFresh - WFrozen) was log-transformed and plotted against the log-transformed frozen weight, resulting in a robust linear model. All assumptions of linear regression were met. The intercept (α1) and slope (α2) were estimated for each species based on the following equation: ln(ΔW) = ln(α1) + α2ln(WFrozen),  supporting a power function, ΔW = α1WFrozenα2,  where ΔW is the change in weight of the fish (g) and WFrozen is the frozen weight (g) of the fish. Since no appreciable differences in parameter estimates were observed across species of differing body sizes, we re-ran the model incorporating all of the fish species and calculated a mean estimate to be used as the conversion factor for all species across all body weights.  The conversion factors were estimated as: α1 = 0.0946 (SE 0.0063), α2 = 0.5620 (SE 0.0147), and the coefficient of determination was r2 = 0.705. Thus, fishes collected for this study that lacked initial weights from the field could have their frozen weights converted to initial ‘fresh’ weights using the following equation: WFresh = WFrozen + α1WFrozenα2. Data dictionary: Expedition_ID: unique code for each field expedition. Island: island that the fish was collected on. Field_Date: date of fish capture (MM/DD/YYYY). Species: abbreviated species code for the fish caught. Species codes are the following: Species Species code Acanthurus nigricans AC.NIGR Ctenochaetus marginatus CT.MARG Sufflamen chrysopterum SU.CHRY Chaetodon ornatissimus CH.ORNA Chaetodon lunulatus CH.LUNULAT Cirrhitichthys oxycephalus CI.OXYC Paracirrhites arcatus PA.ARCA Paracirrhites forsteri PA.FORS Thalassoma amblycephalum TH.AMBL Parupeneus multifasciatus PA.MULT Centropyge flavissima CE.FLAV Chromis margaritifer CH.MARG Plectroglyphidodon dickii PL.DICK Pomacentrus coelestis PO.COEL Stegastes aureus ST.AURE Pseudanthias bartlettorum PS.BART Pseudanthias cooperi PS.COOP Pseudanthias dispar PS.DISP Unique_ID: unique identifier for each fish. Year: year of fish collection. Station: name of the site the fish was caught at. There are multiple sites per island. Code: unique code for each fish combining Expedition_ID and Unique_ID. TL_Ave: the average fish total length in mm, calculated by averaging TL_Thawed and TL_Field. Fish_Weight_Ave: the average wet weight of the whole fish in g, calculated by averaging Fish_Weight_Thawed and Fish_Weight_Field. Dissection_Date: date of fish dissection (MM/DD/YYYY). TL_Thawed: fish total length in mm after being frozen in the field, transported back to the lab, and then thawed. FL_Thawed: fish fork length in mm after being frozen in the field, transported back to the lab, and then thawed. SL_Thawed: fish standard length in mm after being frozen in the field, transported back to the lab, and then thawed. Fish_Weight_Thawed: fish wet weight in g after being frozen in the field, transported back to the lab, and then thawed. Fish_Weight_Frozen: fish wet weight in g after being frozen in the field and prior to being thawed. TL_Field: fish total length in mm when collected in the field. FL_Field: fish fork length in mm when collected in the field. SL_Field: fish standard length in mm when collected in the field. Fish_Weight_Field: fish wet weight in g when collected in the field. Technical details: Data analysis was done using R statistical software. R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.