Precision of Structures Used to Estimate Age and Growth of Apache Trout from Arizona

The Apache Trout Oncorhynchus apache is endemic to streams in the White Mountains of east-central Arizona and represents one of the southernmost species of Oncorhynchus. Although populations are present in high-elevation streams in the Black, White, and Little Colorado river drainages (Miller 1972), they now occupy about 281 km of streams instead of the estimated 965–1,320 km they once occupied (USFWS 2009, 2022). The White Mountain Apache Tribe first recognized declining Apache Trout populations in the late 1940s, and attempted to protect remaining populations by implementing fishing prohibitions and protecting important habitats during the 1950s (USFWS 1979). A variety of factors contributed to the decline of Apache Trout, including the introduction of nonnative salmonids, extensive habitat alteration, and overexploitation. Interactions (i.e., competition, predation) with nonnative Brown Trout Salmo trutta and Brook Trout Salvelinus fontinalis led to widespread declines of Apache Trout, and hybridization with Rainbow Trout Oncorhynchus mykiss and Cutthroat Trout Oncorhynchus clarkii reduced the distribution of genetically pure Apache Trout (Rinne and Minckley 1985; Carmichael et al. 1993). Timber harvest, livestock grazing, and water development have also had detrimental effects on Apache Trout habitat. Primary effects from these alterations include changes to riparian corridors and streambank morphology, altered hydrology and thermal characteristics, reduced quantity and quality of spawning habitat, and reduced production of macroinvertebrates (USFWS 2009). Initial federal protections for the species came along with listing as endangered under the U.S. Endangered Species Preservation Act in 1967 (USFWS 1967, 2022). Apache Trout were subsequently downlisted as threatened under the U.S. Endangered Species Act (ESA 1973, as amended) in 1975 due to the discovery of additional populations, successful captive culturing, removal of overexploitation as a threat, and reduction of logging and hybridization as threats (USFWS 1975, 2022). The U.S. Fish and Wildlife Service (USFWS) released the first Apache Trout Recovery Plan in 1979, with revisions in 1983 and 2009 (USFWS 1979, 2009).

Recovery objectives are not a statutory requirement of recovery plans, but wildlife managers often develop them to define the outcome that they intend recovery actions to accomplish. The recovery objective for Apache Trout is to establish and maintain 30 self-sustaining discrete populations of pure Apache Trout within its historical range (USFWS 2009). A detailed discussion on the merits of the recovery objectives is beyond the scope of this paper. However, assessing the occurrence and extent of self-sustaining Apache Trout populations is reliant on obtaining information on their population demographics and dynamics. For instance, a self-sustaining population implies the presence of periodic reproduction and multiple age classes (e.g., Allen and Hightower 2010). Age estimation is a fundamental component of fish population assessments and provides the foundation for estimating other rate functions (e.g., growth, recruitment, mortality). With regard to Apache Trout, understanding the age structure and dynamic of populations is important for informing decisions during the ongoing recovery process and managing populations into the future. Information on age structure, coupled with information on growth and mortality, is also important for better understanding the ecology of Apache Trout and their response to management and conservation actions regardless of their listing status.

The most frequently used technique to estimate fish age involves using calcified or hard structures (Quist et al. 2012). Cleithra, scales, otoliths, spines, and fin rays are among the hard structures commonly used for age estimation with the most reliable structure often varying among species and geographic location (Maceina et al. 2007; Branigan et al. 2019). When choosing a structure for age and growth analysis, scientists must consider a variety of factors such as lethality involved with structure extraction and whether the structure provides precise and accurate age estimates (Phelps et al. 2017). For example, otoliths consistently provide accurate age estimates, but they are time consuming to process and require sacrificing fish (Isermann et al. 2003; Long and Grabowski 2017). Nonlethal structures (e.g., scales, fin rays, spines) may be preferred for species of high conservation concern where any additional mortality must be avoided (Quist et al. 2012; Phelps et al. 2017).

Investigations on the age and growth of Apache Trout are limited to two studies. Harper (1976) collected otoliths from 37 Apache Trout in the headwaters of Big Bonito Creek, Arizona, to estimate age and growth. Kitcheyan (1999) used scales to estimate age of Apache Trout from two creeks in Arizona. However, no research has evaluated precision of ageing structures for Apache Trout. Identifying which hard structures provide the most replicable age estimates with the highest level of confidence should lead to improved estimates of population rate functions and better inform management decisions. Identifying whether a nonlethal structure provides reliable age estimates would be particularly useful.

Given the conservation status of Apache Trout, sacrificing fish specifically for comparing structures is not feasible. However, fisheries managers brought wild Apache Trout from the East Fork White River, Arizona, into a hatchery with the goal of incorporating genetics from wild fish into the hatchery broodstock program. While in captivity, an accident killed 78 of the wild fish, thereby presenting an opportunity to evaluate the use of hard structures for ageing. The objective of this study was to evaluate the precision and readability of scales (two body locations), sectioned fin rays (pectoral, pelvic, anal), and sectioned sagittal otoliths for estimating age of Apache Trout.

The East Fork White River is located on the Fort Apache Indian Reservation, Arizona, and contains a population of wild, genetically pure Apache Trout. The East Fork White River is a high-elevation, high-gradient system located on the southwestern slope of Mount Baldy. Apache Trout is the only fish species present and the fish occur in an ∼8.2-km stretch of river located upstream of a natural barrier.

Staff from the White Mountain Apache Tribe Game and Fish Department, Arizona Fish and Wildlife Conservation Office, and Alchesay-William Creek National Fish Hatchery Complex sampled Apache Trout from the East Fork White River in October 2017 with a backpack electrofisher. Individuals greater than 100 mm were collected (n = 100) and transported to Williams Creek National Fish Hatchery, Arizona. The Williams Creek Hatchery is spring fed with a near constant water temperature around 11°C. Hatchery staff held the fish for approximately 6 mo, then examined them for indications of sex, measured them to the nearest millimeter (total length), weighed them to the nearest gram, and implanted them with a passive integrated transponder tag. After 10 mo in the hatchery (August 8, 2018), all remaining fish died when a water supply that was thought to be unconnected to the quarantine facility was treated with chlorine. Hatchery staff froze the fish, which were later flown to the University of Idaho for age and growth analyses.

We measured total length of individual fish to the nearest millimeter. We removed scales from two locations: 1) just posterior to the insertion of the pectoral fin (hereafter pectoral scales) and 2) dorsal to the lateral line and just posterior to the dorsal fin (hereafter dorsal scales; Quist et al. 2012). We removed scales with the tip of a knife, placed them onto a folded piece of paper that was inserted into a coin envelope, and allowed them to air dry (McInerny 2017). Once dry, we separated scales and pressed between two glass microscope slides that we taped at each end. We removed the marginal pectoral, pelvic, and anal fin rays with scissors at the articulation of the fin ray with the body wall following the procedure outlined in Koch et al. (2008). We placed fin rays into labeled coin envelopes and allowed them to dry. We then mounted fin rays in epoxy following Koch and Quist (2007) and cross-sectioned (∼0.8 mm thick) with a Buehler Isomet low-speed saw (Buehler, Lake Bluff, IL). We removed sagittal otoliths following Schneidervin and Hubert (1986). We stored otoliths in a microcentrifuge tube that we placed in a coin envelope. We placed a small mark on the nucleus of the otolith using a micropen to ensure that cross-sections included the nucleus. We mounted otoliths in epoxy and sectioned (∼1.3 mm thick) in the dorsoventral plane (Quist et al. 2012; Long and Grabowski 2017). Although sectioned otoliths take more time to process than whole otoliths (e.g., Isermann et al. 2003), sectioned otoliths regularly provide more accurate and precise age estimates than whole otoliths (e.g., Hyndes et al. 1992; Newman et al 2000; Gallagher et al. 2016). We polished fin ray and otolith sections with progressively finer abrasive paper until additional efforts failed to improve clarity. We used an image analysis system consisting of a stereoscope coupled to a computer using image analysis software (Image Pro-Plus; Media Cybernetics, Rockville, MD) to read the structures.

Two readers independently enumerated annuli on each hard structure. Both readers had extensive experience ageing fishes using a variety of structures from a diversity of fish species and geographic locations. Readers had no prior knowledge of fish length or age estimates from other structures. Each reader estimated an initial age independently and assigned a confidence rating from 0 to 3. A confidence rating of 0 indicated that the reader had no confidence in their age estimate and a rating of 3 indicated high confidence (Koch et. al 2008; Spiegel et al. 2010). After each reader estimated age for a given structure, they compared presumptive ages. If age estimates differed, readers would discuss the structure until they reached a consensus age. If they could not reach a consensus age, we removed the structure from further analyses.

We used age-bias plots to evaluate between-reader and between-structure (i.e., consensus age) precision (Campana et al. 1995; Buckmeier et al. 2017). We conducted between-structure comparisons in relation to sectioned otoliths. We calculated percentage of exact agreement (PA) and percentage of agreement within 1 y (PA-1) between readers and structures. We also calculated the coefficient of variation (CV = [SD/mean] × 100) as an additional estimate of precision in age estimates between readers and structures (Campana et al. 1995).

We estimated ages for 78 Apache Trout varying in total length from 113 to 235 mm (mean ± SD, 169.9 ± 33.7 mm; Data S1, Supplemental Material). Both readers deemed several structures from individual fish unreadable. We removed pectoral scales from the analysis because they were exceptionally small and both readers had no confidence in age estimates using the structure. They reached a consensus age for all remaining structures. This resulted in the use of samples from 77 fish for dorsal scales, 75 for otoliths, 74 for pectoral fin rays, 67 for pelvic fin rays, and 44 fish for anal fin rays. Consensus age estimates varied from 1 to 5 y for scales, 2 to 6 y for anal fin rays, 2 to 8 y for pectoral fin rays, and 2 to 9 y for pelvic fin rays and otoliths.

We first compared estimated ages for each of the ageing structures between the two readers. Percentage of exact agreement between readers was highest for dorsal scales (72.7%) and otoliths (72.0%), and lowest for pelvic (58.1%), pectoral (54.0%), and anal fin rays (31.8%; Figure 1). We observed similar patterns for PA-1 with the highest agreement observed for dorsal scales and otoliths (>96.0%), and lowest agreement for fin rays (<90%). The between-reader CV was lowest for otoliths (5.1) and highest for anal fin rays (16.9; Figure 1).

We compared consensus age estimates across structures to provide additional insight on variability among ageing structures. When compared to sectioned otoliths, percentage of agreement was generally low among structures (Figure 2). Percentage of exact agreement with otolith ages was highest for pelvic fin rays (35.7%), anal fin rays had the best agreement within 1 y (70.2%). Scales exhibited the lowest agreement (PA = 21.6%; PA-1 = 58.0%) with otolith ages. Pectoral fin rays had the lowest CV (Figure 2).

Reader 2 was generally more confident in their age estimates than reader 1 (Figure 3). Across readers, confidence was highest for otoliths (mean ± SE, 2.1 ± 0.07) and low for the other structures. The readers reported the lowest confidence for anal fin rays (0.3 ± 0.06) and scales (0.7 ± 0.05).

Researchers have not validated annulus formation on hard structures for Apache Trout and, therefore, our research can only provide insight on precision of different structures. However, sagittal otoliths have repeatedly been shown to provide accurate age estimates for a variety of fishes, including salmonids (e.g., Haglund and Mitro 2017; Phelps et al. 2017; Branigan et al. 2019). For instance, Hining et al. (2000) validated annulus formation in Rainbow Trout from southern Appalachian streams and Schill et al. (2010) validated otoliths for ageing Redband Trout Oncorhynchus mykiss gairdneri in high desert streams in southwestern Idaho. Other researchers have shown otoliths to provide accurate age estimates for Arctic Grayling Thymallus arcticus in Alaska (DeCicco and Brown 2006) and for Chinook Salmon Oncorhynchus tshawytscha along the Pacific coast of Canada (Murray 1994). Although we were unable to validate otolith ages in our study, sectioned otoliths yielded the most readable (i.e., highest confidence rating) and precise age estimates compared to the other structures.

Scales are traditionally the most common structure used to age fishes (Quist et al. 2012; McInerny 2017). Studies have shown scales to provide accurate and precise age estimates for some species, but they seem to perform best for young fish, fast-growing fish, and in systems with high seasonal variation in temperature or prey resources (McInerny 2017; Phelps et al. 2017). Unfortunately, scales regularly underestimate the age of fishes. For example, DeCicco and Brown (2006) found that scales underestimated age of Arctic Grayling by as much as 20 y in an Alaskan river system. Hining et al. (2000) found that scales were inaccurate for age-3 and older Rainbow Trout in Tennessee and North Carolina. Schill et al. (2010) reported that scales underestimated age and were unreliable for Redband Trout in Idaho. Between-reader precision was high for scales sampled from Brook Trout in West Virginia streams, but they underestimated age of age-3 and older fish compared with otoliths (Stolarski and Hartman 2008). Similar results have been reported for a diversity of trout and char (e.g., Kruse et al. 1997; Mogen and Kaeding 2005; Zymonas and McMahon 2009; Erhardt and Scarnecchia 2013). In our study, scales provided relatively high between-reader precision compared to the other structures, including otoliths. However, scales tended to underestimate age of age-3 and older Apache Trout (i.e., based on consensus otolith age) by up to 6 y. When either reader had zero confidence in a scale age, PA was 50.0% and PA-1 was 100% for age-3 and younger Apache Trout (i.e., based on consensus otolith age). When both readers had a confidence rating equal or greater than 1, PA was 45.5% and PA-1 was 100% for the same group of fish. Assuming that otoliths provide reasonably accurate age estimates, scales may provide useful age estimates for age-3 and younger Apache Trout. Unfortunately, the age distribution of fish limits our study in that only 23 age-3 and younger fish were available for study. Additional research would provide further insight on the application of ageing scales for young Apache Trout.

Fin rays are nonlethal structures that have produced mixed results depending on the species and system. In some systems, fin rays provide age estimates that are accurate and concordant with otolith ages. Copeland et al. (2007) found that dorsal fin rays were nearly 99% accurate in estimating age of known-age Chinook Salmon in Idaho. Pelvic fin rays were 88% accurate for Bull Trout Salvelinus confluentus in Idaho and Montana streams (Zymonas and McMahon 2009). Erhardt and Scarnecchia (2013) also evaluated pelvic fin rays from Bull Trout and found that they performed well for fish in the North Fork Clearwater River system, Idaho. In contrast to these studies, other research has reported low precision and accuracy from salmonid fin rays. Pectoral fin rays from Brook Trout in West Virginia provided age estimates with low between-reader precision (Stolarski and Hartman 2008). Hubert et al. (1987) found that dorsal and pectoral fin rays underestimated ages compared with otoliths from Yellowstone Cutthroat Trout Oncorhynchus clarkii bouveri in Yellowstone Lake. Gallagher et al. (2016) reported that pectoral and pelvic fin rays underestimated age for age-5 and older Dolly Varden Salvelinus malma from the Canadian arctic. Of the different fin rays examined in our study, reader confidence was highest for pectoral fin rays, but all fin rays had poor between-reader precision and rarely agreed with otolith ages. Unlike scales, which tended to underestimate age, fin rays appeared to overestimate age at early ages and underestimate age at older ages.

A potential factor influencing the patterns observed in our study was that fish were in a hatchery for almost a year. We did not notice any obvious issues with interpreting structures that captive rearing could have caused. In addition, a single year of atypic growth cannot explain the magnitude of error observed in our study. Nevertheless, our results suggest that scales may provide useful age estimates for fish younger than age 4 but are unreliable thereafter. Similarly, fin rays tended to provide age estimates that were inconsistent between readers and with otolith ages. Otoliths appear to be the most precise structure for the full range of Apache Trout ages. Future efforts focused on other Apache Trout populations (e.g., opportunistic samples from field mortalities) with a wide range of ages and validating structures for ageing would be particularly helpful.

We thank Jennifer Johnson, Chad Baumler, Rob Bettaso, Inez Billy, Mike Figueroa, Justin Gatewood, Isaiah Paxson, Gene Okamoto, and Jonathan Walker for assistance with field collection of the fish used in this study. Zach Beard and two anonymous reviewers provided helpful comments on a previous version of this manuscript. We recognize the White Mountain Apache Tribe for their distinguished commitment to Apache Trout conservation and management and thank them for their support and authorization to pursue publishing this work. Additional support for this work was provided by the U.S. Geological Survey, Idaho Cooperative Fish and Wildlife Research Unit, which is jointly sponsored by the University of Idaho, U.S. Geological Survey, Idaho Department of Fish and Game, and Wildlife Management Institute.

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Data S1. Raw data, including fish identification number, total length (mm), age estimates for each reader, confidence ratings for each reader, and consensus age estimate by ageing structure for Apache Trout Oncorhynchus apache sampled from the East Fork White River, Arizona, in 2017.

Available: https://doi.org/10.3996/JFWM-22-021.S1 (61 KB XLSX)

Reference S1.[ESA] U.S. Endangered Species Act of 1973, as amended, Pub. L. No. 93-205, 87 Stat. 884 (Dec. 28, 1973).

Available: https://doi.org/10.3996/JFWM-22-021.S2 (228 KB PDF) and https://www.fws.gov/endangered/esa-library/pdf/ESAall.pdf

Reference S2.[USFWS] U.S. Fish and Wildlife Service. 1967. Federal Register 32:48(11 March 1967):4001.

Available: https://doi.org/10.3996/JFWM-22-021.S3 (8.490 MB PDF)

Reference S3.[USFWS] U.S. Fish and Wildlife Service. 1975. Threatened status for three species of trout. Federal Register 40:137(16 July 1975):29863–29864.

Available: https://doi.org/10.3996/JFWM-22-021.S4 (37.455 MB PDF)

Reference S4.[USFWS] U.S. Fish and Wildlife Service. 1979. Recovery plan for Arizona trout, Salmo apache, Miller, 1972. Albuquerque, New Mexico: USFWS.

Available: https://doi.org/10.3996/JFWM-22-021.S5 (1.267 MB PDF)

Reference S5.[USFWS] U.S. Fish and Wildlife Service. 2009. Apache Trout recovery plan. Second revision. Albuquerque, New Mexico: USFWS.

Available: https://doi.org/10.3996/JFWM-22-021.S6 (140 KB PDF)

Reference S6.[USFWS] U.S. Fish and Wildlife Service. 2022. Species Status Assessment for the Apache Trout Oncorhynchus apache. Flagstaff, Arizona: USFWS.

Available: https://doi.org/10.3996/JFWM-22-021.S7 (19.023 MB PDF)