Larval Billfish Data from Plankton Tows Conducted off the Kona Coast in West Hawai'i between 1997 and 2018

This is a 20-year (1997-2018) dataset of neustonic ichthyoplankton collections from West Hawai'i and beyond focusing on four species of billfishes (Blue Marlin /Makaira nigricans/, Striped Marlin /Kajikia audax/, Shortbilled Spearfish /Tetrapturus angustirostris/, and Swordfish /Xiphias gladius/). We compiled observations of 1963 larvae over this 20- year period (from 998 discrete ichthyoplankton tows in West Hawaii), and provide specimen information and species level identifications for 1109 larvae using both existing and new genetic assignments. Additionally, we filtered these data to tows with consistent methodologies revealing 1761 larval billfishes (from 771 discrete surface tows in West Hawaii). We also constructed a thorough dataset of environmental variables (temperature, salinity, chlorophyll) associated with each occurrence of larval billfish and all absences using oceanographic data collected in-situ during cruises and satellite data. We present the first complete multispecies larval billfish dataset with coupled environmental data in the Pacific Islands Region ready for statistical analysis. This dataset will be critical for improving our understanding of how oceanographic features and environmental changes will affect larval growth, survival, and ultimately population replenishment.

Understanding the habitat requirements of species throughout their life history provides insight into the environmental drivers that regulate their distribution and abundance. Identifying essential habitats used by larval and juvenile fishes has become a critical component of Ecosystem-Based Fisheries Management (EBFM) especially for recreationally and commercially important fisheries species. Billfishes (Blue Marlin Makaira nigricans, Striped Marlin Kajikia audax, Shortbilled Spearfish Tetrapturus angustirostris, and Swordfish Xiphias gladius) are popular sportfishing targets in West Hawai'i Island. Despite their commercial and recreational value, there is currently no published information on larval distribution and habitat requirements for billfishes in Hawaiian waters. To address this knowledge gap we created this dataset combining larval billfish specimen information, environmental measurements at the location where the larva was collected, and plankton tow information to normalize observations across years.

Generally, monitoring ichyoplankton levels helps us understand the composition of the neustonic plankton communities across space and time, with focus on larval dynamics of commercially and culturally important larval species. These data represent a strong mechanism to monitor spawning, recruitment, and phenology of larvae. Understanding the habitat requirements of species throughout their life history provides insight into the environmental drivers that regulate their distribution and abundance.

For genetic identification of larvae:

Hyde J, Humphreys RL, Musyl M, West A and Vetter R. Shipboard Identification of fish eggs and larvae by multiplex PCR, and description of fertilized eggs of blue marlin, shortbill spearfish and wahoo. Marine Ecology ProgressSeries 2005. 286:269-277.

For plankton tow methodology:

Whitney JL, Gove JM, McManus MA, Smith KA, Lecky J, Neubauer P, Phipps, JE, Contreras EA, Kobayashi, DR, Asner GP. 2021. Surface slicks are pelagic nurseries for diverse ocean fauna. Sci Rep. 11(1): 3197. https://doi.org/10.1038/s41598-021-81407-00.

For remotely sensed 8-day averaged chlorophyll-a data:

Sathyendranath, S.; Jackson, T.; Brockmann, C.; Brotas, V.; Calton, B.; Chuprin, A.; Clements, O.; Cipollini, P.; Danne, O.; Dingle, J.; Donlon, C.; Grant, M.; Groom, S.; Krasemann, H.; Lavender, S.; Mazeran, C.; Mélin, F.; Müller, D.; Steinmetz, F.; Valente, A.; Zühlke, M.; Feldman, G.; Franz, B.; Frouin, R.; Werdell, J.; Platt, T. (2021): ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 5.0 Data. NERC EDS Centre for Environmental Data Analysis, 19 May 2021. doi:10.5285/1dbe7a109c0244aaad713e078fd3059a. http://dx.doi.org/10.5285/1dbe7a109c0244aaad713e078fd3059a

For remotely sensed daily Sea Surface Temperature data:

ERDAPP dataset id: noaacrwsstDaily

For remotely sensed and modeled salinity data:

Global Ocean Physics Reanalysis. E.U. Copernicus Marine Service Information (CMEMS). Marine Data Store (MDS). DOI: https://doi.org/10.48670/moi-00021 (Accessed on 01-11-2024)

The data described here include tow data collected as a part of PIFSC/ESD's West Hawai'i Ichthyoplankton Time Series Project. The West Hawai'i Ichthyoplankton Time Series began in 1997, when ichthyoplankton was collected by neuston tows off West Hawai'i to assess the spatial and temporal variability in larval distribution and abundance. After samples are processed and fish are identified, environmental metadata helps us monitor seasonal occurrence, vertical distribution, habitat and temperature associations, and cross-shore distribution of larvae. The response of larvae to oceanographic conditions can provide insight into how the environment may modulate recruitment.

https://www.fisheries.noaa.gov/inport/item/74320

While every effort has been made to ensure that these data are accurate and reliable within the limits of the current state of the art, NOAA cannot assume liability for any damages caused by errors or omissions in the data, nor as a result of the failure of the data to function on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.

Sampling occurred off the Kona coast from 1997 through 2018.

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NOAA Ecosystem Science Division (ESD) Data Sharing Recommendations, version 9.0 updated August 12, 2015:

ESD welcomes the opportunity to collaborate on research issues contributing to the scientific basis for better management of marine ecosystems. ESD has a very diverse set of field activities that generates large volumes of data using an array of data collection protocols.

The following recommendations are for your consideration as you use this data:

1) Data analyses should take all field exigencies into account. The most effective way to do this would be active collaboration with ESD principal investigators.

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Example citation:

"This publication makes use of data products provided by the Ecosystem Science Division (ESD), Pacific Islands Fisheries Science Center (PIFSC), National Marine Fisheries Service (NMFS), National Oceanic and Atmospheric Administration (NOAA), with funding support from the NOAA Ocean Acidification Program (OAP). The analysis and interpretations presented here are solely that of the current authors.

Data can be accessed online via the NOAA National Centers for Environmental Information (NCEI) Ocean Archive.

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Please cite NOAA Fisheries, Ecosystem Science Division (ESD) when using the data.

Example:

Pacific Islands Fisheries Science Center, 2025: Larval Billfish Data from Plankton Tows Conducted off the Kona Coast in West Hawai'i between 1997 and 2018, https://www.fisheries.noaa.gov/inport/item/74319.

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A GPS unit was used to record distance to shore, and coordinates of each tow. The mean depth value was recorded by entering coordinates in ArcGIS using SRTM15+ v2 global bathymetry dataset (15 arc second resolution).

Larval fish of certain taxa are notoriously difficult to identify to species. We utilized DNA barcoding to confirm ID's of larvae, and utilized the morphological characteristics of those larvae to identify others. Larvae smaller than 2mm were unable to be confidently identified. A total of 1891 billfish larvae were collected as a part of this sampling effort, of which 729 had been previously identified to species while 1162 were simply listed as "unknown Istiophoridae". We utilized a suite of genetics methods to identify available larval billfishes to species that were inventoried from the wet archive at PIFSC.

Our first investigation identified observations of 1888 larvae, of which 726 (38%) were already identified to the species-level. Through the inventory effort a total of 2048 larvae observations (records of larvae both identified and not identified to species) were compiled (including the addition of 160 specimens that were discovered after our initial assessment of 1888). The length measurements and identities of the Kajikia audax specimens in this dataset came from a publication by researchers at PIFSC (Hyde et al. 2006). Of those 2048, 1322 had unknown identities (i.e., unknown Istiophoridae). Physical specimens were located for 1137 of 1322 larval records still to be identified, 81 of those were too damaged, desiccated or had too little tissue to have their DNA extracted. The remaining 1056 larvae with physical specimens were the focus of our genetic efforts and specimen examination. We physically examined, measured larval length to the nearest 0.5mm (for specimens 7mm in length or shorter) of 1395 larvae (some of these already had been identified) and noted the developmental stage of 949 larvae (preflexion, flexion or post flexion). Specimens longer than 7mm were measured to the nearest 1mm. Many of these larger larvae were curled up or were otherwise slightly warped by their preservation in ethanol -- this was the most accurate measurement for the larger sizes without further damaging those specimens.

We extracted DNA (eyeballs, tail tissue or entire specimens) for all 1056 larvae utilizing the HOTSHOT protocol (following Truett et al. 2000). Species-specific multiplex PCR-based genetic assays (as described in Hyde et al. 2005) were conducted multiple times on 110 of these larvae. Despite months of troubleshooting, we ultimately found this methodology to be troublesome and assay performance was below our standards. Ultimately we abandoned multiplex reactions in favor of more reliable singleplex reactions for all larvae. Makaira nigricans and Tetrapturus angustirostrisis are the two most common species we would expect to see, based on the ratios of the existing species-level identifications. For 210 of the larvae remaining unidentified (i.e., not identified in M. nigricans and T. angustirostris singleplex assays) we extracted DNA a second-time from 210 larvae utilizing a different technique (DNEazy Blood and Tissue Kit, QIAGEN, Germantown MD) and then barcoded using COI specific primers (after Ward et al. 2005). We selected larvae that were 5mm total length or longer in an attempt to increase the chance of successful extractions. Gel electrophoresis revealed bands in 84 of these larval extracts, which were Sanger sequenced at the Center for Advanced Studies in Genomics, Proteomics and Bioinformatics (ASGPB) at University of Hawai'i at Manoa. Sequences were then trimmed of N-heavy ends, aligned in Geneious (Geneious Prime 2023.2.1,(https://www.geneious.com)) using the MUSCLE alignment, and ambiguities annotated. Cleaned sequences were BLASTed against NCBI's nucleotide (nt) database and all pairwise identities 98% or higher were kept as positive identifications (98.7% of successfully sequenced larvae had pairwise identities greater than 99%).

Remotely Sensed Temperature Data:

Daily Sea Surface Temperature (SST) data were obtained in July 2024 from NOAA's Coral Reef Watch (CRW) at 5km spatial extent (ERDAPP dataset id: noaacrwsstDaily). Although the daily values are coarser than the in situ data, which capture variations between cruises on the same day, it can still be useful for considering across days within a cruise (which had durations up to two weeks) and most certainly between years.

Remotely Sensed Salinity Data:

Sea surface salinity (SSS) was sourced from the GLORYS12V1 product. This product is a global ocean eddy-resolving (1/12 degree horizontal resolution, 50 vertical levels) reanalysis. This is hosted and created by the E.U. Copernicus Marine Service https://doi.org/10.48670/moi-00021. We chose to use the GLORYS reanalyzed SSS product as it includes values from the start of the time series in 1997. Due to remotely sensed salinity data not being available before 2011 (Lagerloef 2012), the use of modelled salinity values allows us to work with the entirety of the 20- year time series. Other working groups have utilized this same GLORYS12v1 product tolook at, amongst other phenomena, "The [impact of] variability of the Iberian Current System on the dispersion, growth, and survival of fish eggs and larvae of small pelagic fish" over the same time period used in this present study (IMPA, n.d.). Since the plankton tows were neustonic we felt that sea surface data from satellites were appropriate.

Chlorophyll- a Remotely Sensed Data:

Chl-a data was an eight-day composite which came from the European Space Agency's Ocean Colour Climate Change Initiative (OC-CCI) version 5 (Sathyendranath et al. 2021). We chose to use the 8-day composite to maximize our chl-a data coverage over almost the entire twenty year time series (data only goes back to September 1997 which means we do not have coverage for 1997 as that cruise occurred in April). Daily measurements for a certain spatial extent are usually collected at the same time each day and cloud coverage or other disturbances can block the ocean from the satellite and make data unavailable for a given day. Utilizing an 8-day composite makes these chl-a data best for inter-month or inter-annual comparisons. Furthermore, water depth can influence ocean color and thus chla-a values which are derived from ocean color. J. Perelman created a mask for measurements taken at the 30m isobath in order to further increase the reliability of these measurements.

The metadataset consisted of a combined 998 unique tows across the aforementioned sampling efforts. After we filtered the data to only include surface tows with relevant gear types (IKMT and 1m Neuston net), the final dataset consists of 770 samples from 19 research expeditions spanning 1997 to 2018 across the MHI. Use the volume of water filtered for a given tow to normalize larval fish densities between tows and cruises (vol.m3 column in csv file).

Proportion of Stations with matched in situ thermosalinograph (TSG) data. Only 10 tows (from three cruises) out of 771 considered in this work had any missing TSG data at all. Therefore, we provide TSG data for 98.7% of all tows. Temperature and salinity data for these 10 missing tows are supplemented with remotely-sensed data.

In short, all inventoried larval specimens were handled at least once throughout this process (minimally: to note preservation state of larva, maximally: hotshot and kit extracted, multiplexed, singplexed and COI barcoded, sequenced).

Research conducted before 2016 targeted the sampling of billfish and tuna primarily using large research vessels, and did not focus on oceanographic features (ie. surface slicks). Tows conducted between 2016-2018 were slick-focused and used both small boats and large vessels. Ichthyoplankton and larvae were processed in the same manner.

Tows with missing metadata (eg. length of tow, volume filtered, latitude/longitude) and tows that were not conducted at the surface are noted as "FALSE" in the column titled "consistent with product 1".

NOAA IRC and NOAA Fisheries ITS resources and assets.

The West Hawai'i Ichthyoplankton Time Series began in 1997, when ichthyoplankton was collected by neuston tows off West Hawai'i to assess the spatial and temporal variability in larval distribution and abundance. Samples were analyzed under microscope and larvae were identified, counted and measured for length. Environmental metadata helps us monitor seasonal occurrence, vertical distribution, habitat and temperature associations, and cross-shore distribution of larvae. The response of larvae to oceanographic conditions can provide insight into how the environment may modulate recruitment.