Skip to main content

Some NLM-NCBI services and products are experiencing heavy traffic, which may affect performance and availability. We apologize for the inconvenience and appreciate your patience. For assistance, please contact our Help Desk at info@ncbi.nlm.nih.gov.

PLOS ONE logoLink to PLOS ONE
. 2020 Jul 15;15(7):e0235752. doi: 10.1371/journal.pone.0235752

Stable isotope analysis of multiple tissues from Hawaiian honeycreepers indicates elevational movement

Kristina L Paxton 1,*, Jeffery F Kelly 2,3, Sandra M Pletchet 2, Eben H Paxton 4
Editor: David P Gillikin5
PMCID: PMC7363098  PMID: 32667954

Abstract

We have limited knowledge of the patterns, causes, and prevalence of elevational migration despite observations of seasonal movements of animals along elevational gradients in montane systems worldwide. While a third of extant Hawaiian landbird species are estimated to be elevational migrants this assumption is based primarily on early naturalist’s observations with limited empirical evidence. In this study, we compared stable hydrogen isotopes (δ2H) of metabolically inert (feathers) and active (blood plasma, red blood cells) tissues collected from the same individual to determine if present day populations of Hawaiian honeycreepers undergo elevational movements to track areas of seasonally high flower bloom that constitute significant food resources. We also measured stable carbon isotopes (δ13C) and stable nitrogen isotopes (δ15N) to examine potential changes in diet between time periods. We found that the majority of ‘apapane (Himatione sanguinea) and Hawaiʻi ʻamakihi (Chlorodrepanis virens) captured at high elevation, high bloom flowering sites in the fall were not year-round residents at the capture locations, but had molted their feathers at lower elevations presumably in the summer after breeding. δ2H values of feathers for all individuals sampled were higher than blood plasma isotope values after accounting for differences in tissue-specific discrimination. We did not find a difference in the propensity of elevational movement between ‘apapane and Hawaiʻi ‘amakihi, even though the ‘amakihi is considered more sedentary. However, consistent with a more generalist diet, δ15N values indicated that Hawaiʻi ʻamakihi had a more diverse diet across trophic levels than ʻapapane, and a greater reliance on nectar in the fall. We demonstrate that collecting multiple tissue samples, which grow at different rates or time periods, from a single individual can provide insights into elevational movements of Hawaiian honeycreepers over an extended time period.

Introduction

The movement of animals in response to seasonal fluctuations in climate and availability of resources is a widespread and taxonomically diverse behavior occurring in animals such as birds, bats, insects, and ungulates [1, 2]. However, our understanding of ecological factors shaping migratory behavior has primarily been shaped by studies of long-distance migration across latitudinal scales. In contrast, we have limited knowledge of the patterns, causes, and prevalence of elevational migration despite observations of seasonal movements of animals along elevational gradients in montane systems worldwide [3, 4]. Unlike obligate, long-distance migration (i.e., every year the entire population migrates), elevational migration typically occurs over short distances and is facultative such that individuals may adapt their behavior in response to environmental conditions that vary from year to year [3]. Seasonal migration across elevations may be driven by ecological factors such as spatial and temporal variation in food resources, weather events, or predation risks that vary at different elevations [4]. For example, the abundance of some frugivorous and nectarivorous bird species, birds that primarily eat fruit and nectar, respectively, in tropical montane systems has been shown to vary across elevations associated with seasonal changes in fruit and flower availability [5, 6]. Alternatively, elevational migration can be in response to storms, such as seen with white-ruffed manakins (Corapipo altera) in montane wet forests in Central America that migrate to lower elevations following severe storm events as a result of reduced foraging opportunities at high elevations [7].

While elevational migration has been well documented for Neotropical frugivore and nectarivore bird species, many nectarivores outside of the Neotropics, along with other feeding guilds (e.g., insectivores, granivores), are also thought to engage in elevational migrations [3]. For example, a third of extant Hawaiian landbird species are estimated to be elevational migrants [3]. However, for many Hawaiian species this assumption is primarily based on early naturalist’s observations of Hawaiian forest birds making long, high flights over the forest canopy, seasonal changes in the abundance of birds at different elevations [811], and observations of birds in low-elevation habitat following large storms [8]. Early naturalists hypothesized that nectarivorous birds made seasonal movements across elevations as they tracked the timing of flowering ʻōhiʻa (Metrosideros polymorpha). ʻŌhiʻa is the dominant tree from sea level to tree line in Hawaiian wet tropical forests, accounting for more than 80% of the biomass of native forests [12], and is the primary nectar resource utilized by Hawaiʻi’s native nectarivorous birds [13]. Differences in the timing of ʻōhiʻa bloom by ʻōhiʻa varieties that occur at different elevations creates spatially and temporaly variable distributions of bloom [14, 15] that may drive elevational migration. However, this “Elevational-Migration Hypothesis” is based on limited empirical evidence of seasonal movements of Hawaiian forest birds across elevations (but see [16]) given the challenges in following birds across Hawaiʻi’s rugged and remote tropical forests. Moreover, recent correlative studies examining the seasonal abundance of Hawaiian forest birds at different elevations have not found strong synchrony between bird abundances and the flowering phenology of ʻōhiʻa [17, 18]. The lack of correspondence between flower and bird densities indicates that elevational movements may not be as prevalent as early naturalists thought or that present day movement strategies of native Hawaiian forest birds are potentially changing because of factors such as the loss and fragmentation of forests across the landscape [19], reduced competition for nectar resources as populations decline or become extinct [20], or higher disease prevalence of introduced diseases (e.g., avian malaria, pox, mange) at low elevations [21].

Limitations in following individuals through time in steep mountainous terrains, particularly small species that are too light to carry tracking devices [22], has hindered our ability to understand elevational movements in birds worldwide. The use of stable isotopes has been one approach to documenting movement of small animals across large geographic areas given that stable isotopes vary predictably across the landscape and are incorporated into animal tissues through biochemical processes [23]. Stable hydrogen isotopes (δ2H) in particular have become a well-established technique for studying long-distance movements of birds at continental scales (reviewed in [23]), but only a few studies in comparison have used δ2H to study elevational migration [2428]. However, δ2H values vary predictably with not only latitude but also elevation, with approximately a 1‰ to 4‰ decrease of δ2H in precipitation with every 100 m increase in elevation [29]. Depletion of H with altitude results from Rayleigh distillation and depletion of precipitation as an air mass rises over a mountain range and loses moisture to rainfall and decreasing temperatures [29, 30]. Patterns of δ2H in precipitation are correlated with animal tissues as a result of biochemical processes [23], and thus animal tissues are expected to reflect the isotopic signatures of the elevation of feeding where the tissue was grown.

Stable carbon isotopes (δ13C) can also be used to understand elevational movement, although the gradient of change across elevations is much smaller, and thus, δ13C are often not as informative as δ2H for small elevational gradients. For example, the rate of increase in δ13C values of bird feathers was only ~1.3 to 1.5‰ per 1,000 m for adult male black-throated blue warblers (Setophaga caerulescens) and multiple hummingbird species collected across elevational gradients in the Appalachian and Andean mountains, respectively [24, 31]. Therefore, in areas with small elevational gradients, δ13C, along with stable nitrogen isotopes (δ15N), are better for providing an understanding of the diet niche of a species than movement [23].

Animal tissues incorporate local isotopic signatures over different time periods, from days to years [3234], and thus at a single point in time different tissues can provide different time frames associated with the movement of animals. For example, feathers are metabolically inert after formation, and reflect the diet and water inputs of the bird only during the discrete period of feather growth (but see [35]). In contrast, metabolically active tissues like blood, liver, and muscle continuously incorporate the isotopic signature of their environment at varying rates. Blood plasma quickly incorporates isotopic signatures of the local environment with an average residency time of only ~3 to 5 days, while red blood cells (RBCs) and muscle have slower isotopic incorporation rates and integrate local isotopic signatures over longer timescales ranging from 1 to 2 months [32, 33, 36, 37]. However, inter-tissue differences in stable isotope values can not only be a function of differences in the residency time of isotopes, but also physiological mechanisms that control isotopic discrimination among different tissues resulting in tissue-specific discrimination [34]. Field and laboratory studies of birds have shown that feathers are more enriched in 2H than other tissues (e.g., plasma, RBCs, muscle), while isotopic discrimination of 2H between RBCs and blood plasma was not shown to differ [32, 33, 38, 39]. While controlled laboratory studies are beginning to shed light on the patterns of tissue-specific discrimination of stable isotopes, the processes that determine these patterns (e.g., differences in protein synthesis and nutrient routing between tissues) are still not completely understood [32]. Thus, comparisons of multiple tissues collected from the same individual at one point of time can provide insights into shifts in elevational movement and diet for different time periods of the annual cycle, as long as comparisons are made while also incorporating tissue-specific discrimination factors.

We tested the elevational-migration hypothesis in nectarivorous birds on the east side of Hawaiʻi Island in a wet tropical forest to determine if present day populations undergo elevational movements to access ʻōhiʻa flower blooms that form significant food resources. We captured birds at high elevation sites near the upper limits of the forest that had heavy ʻōhiʻa bloom. Birds were captured in the fall after peak molt (i.e., summer) and peak breeding (i.e., January to May) seasons were complete. To assess the propensity of movement, we compared δ2H of metabolically inert (feathers) and active (blood plasma, RBC) tissues collected from the same individual. Based on the elevational-migration hypothesis, we predicted that birds making elevational migrations upslope to high bloom areas would have lower blood plasma δ2H values, representative of the high elevation capture location, compared to their feathers that were grown at lower elevation breeding and molting sites. In contrast, if birds captured at high elevation, high bloom areas were resident breeders, we would expect similar stable isotope values among all tissue types, after accounting for differences in tissue-specific discrimination. We tested these predictions for two Hawaiian honeycreeper species, ‘apapane (Himatione sanguinea) and Hawaiʻi ʻamakihi (Chlorodrepanis virens), that vary in their degree of nectarivory and hypothesized propensity for movement. ‘Apapane are nectarivores, primarily feeding from ʻōhiʻa flowers, but are also known to consume foliage arthropods during the breeding season [13, 40]. In contrast, Hawaiʻi ‘amakihi are generalists that eat foliage arthropods but also consume large quantities of nectar when available [41]. Hawaiʻi ‘amakihi are thought to be more sedentary than ‘apapane given differences in their foraging strategies and greater genetic structure [42], and thus we predicted that a greater proportion of ‘apapane captured at high elevation, high bloom areas would be elevational migrants making long-distance movements in search of ʻōhiʻa nectar. To examine potential changes in diet between time periods of the annual cycle we also measured δ13C and δ15N from feathers and RBCs of target birds. We predicted that Hawaiʻi ‘amakihi would have greater inter-tissue variation for both δ13C and δ15N given their more generalist diet compared to ʻapapane. However, we did not predict large differences in δ13C associated with elevational movements given the small elevational range (~500 to 1500 m) of movements expected by ‘apapane and Hawaiʻi ‘amakihi.

Methods

Ethics statement

The research conducted for this study was carried out in accordance with the Ornithological Council’s guidelines for the use of wild birds in research and was approved by The University of Hawaiʻi at Hilo’s Institutional Animal Care and Use Committee (protocol # UH 12–1315). Other permits were from the United States Department of the Interior bird banding laboratory (permit # 23064), Hawaii State Protected Wildlife Research Permit (WL 13–07), and National Park Service Research Permit (HAVO-2012-SCI-0041).

Study species and area

We sampled ʻapapane and Hawaiʻi ʻamakihi at Hawaiʻi Volcanoes National Park in the upper Kaʻū Forest at three sites ranging in elevation from 1615 to 2191 m (Fig 1). Both species are Hawaiian honeycreepers (Fringillidea) that are locally abundant and widely distributed within the Kaʻū Forest and have been detected through surveys during the breeding season at elevations ranging from tree line (~2200m) to 700 m, with moderately high densities below 1500 m where mosquitoes that vector avian malaria are present [43]. The Kaʻū Forest is one of the largest intact native tropical wet forests on Hawaiʻi Island located on the southeast windward slopes of Mauna Loa Volcano. The forest is comprised primarily of mature ‘ōhiʻa and varying amounts of koa (Acacia koa) with a predominantly native understory. Southern regions of the Kaʻū Forest have been used for cattle ranching over the last 150 years and consist of forested pastures with isolated patches of ʻōhiʻa-koa forests and understory grasses [43]. All three capture sites in this study were near tree line in low stature scrubby ‘ōhiʻa patches that had heavy ʻōhiʻa bloom, immediately above the high stature mixed ʻōhiʻa-koa forest. We also attempted to capture birds in the high stature mixed ʻōhiʻa-koa forest which had little to no ʻōhiʻa bloom, however, we did not catch any birds most likely because densities of birds were so low. The climate of the Kaʻū Forest is affected by Mauna Loa Volcano as winds are driven around and upward creating three rainfall patterns: trade wind and thermally driven sea breeze cycles dominate rainfall patterns from Pāhala to Nāʻālehu, a rain-shadow is present in the area southwest of Kīlauea summit, and high elevation areas that are above the trade wind inversion zone have rainfall only during storms [44].

Fig 1. Map of the Kaʻū Forest on Hawaiʻi Island displaying the capture sites at high elevations (depicted by contour lines).

Fig 1

Habitat layers were obtained from the Landfire program (https://www.landfire.gov).

Sample collection

We captured birds via passive mist netting at three high elevation sites that were experiencing high ʻōhiʻa bloom during the months of September and October in 2012. Upon capture, birds were banded with a U.S. Geological Survey (USGS) aluminum numerical band, weighed to nearest 0.1g with an electronic scale, aged and sexed based on plumage, breeding characteristics, and size (as described in [45]), and assessed for active molt. Additionally, we pulled the two outer most tail feathers and collected a blood sample via brachial vein for δ2H (plasma and RBCs) and δ13C and δ15N (RBCs only) analysis. For most birds, the amount of blood collected was enough for δ2H and δ13C and δ15N analysis. However, we prioritize blood for δ2H analysis when the blood volume was too low for both analyses to be conducted. We stored blood samples on ice until the plasma and RBCs could be seperated at the end of the day, and then placed on dry ice until they could be transfered to a -20°C freezer.

We used plasma samples to represent the isotopic signature of the capture location given the short residency time of blood plasma, while feather samples represented the location of molt. Molt typically occurs following the breeding season during primarily the summer and early fall, and is believed to occur largely on the breeding grounds [46, 47]. While Hawaiian honeycreepers can breed anytime between October to May, depending on weather conditions, their peak breeding season occurs between January to May [46]. RBCs represented the time period in between breeding and capture in the fall.

Stable isotope analysis

Feather and blood samples were prepared for stable isotope analysis at the University of Oklahoma using the protocols outlined in [48]. Briefly, feather samples were cleaned with a 2:1 chloroform methanol solution as well as a phosphate-free detergent and rinsed in deionized water before drying for 24–36 hours under a fume hood. Plasma and RBCs were freeze-dried and powdered. Lipids were not extracted from blood samples prior to freeze drying given the low concentration of lipids in bird blood [49]. Feather material from the distal end of the sample, powdered RBC samples, and powdered plasma samples were weighed (δ2H: 140 to 160 μg, δ13C and δ15N: 350 μg) and wrapped in a silver (δ2H) or tin (δ13C and δ15N) capsule.

Samples were analyzed for stable hydrogen isotope ratios at the Colorado Plateau Stable Isotope laboratory (CPSIL; Flagstaff, Arizona, USA) using a comparative equilibrium approach with calibrated keratin standards to correct for uncontrolled isotope exchange between non-carbon-bound hydrogen in feathers and ambient water vapor [50]. The three calibrated isotope keratin standards analyzed with feather samples included: Cow Hoof (CBS; δ2H = -197‰); Kudi Horn (KHS; δ2H = -54.1‰); Spectrum Keratin Powder Lot SJ (SKP; δ2H = -121.6‰). Stable hydrogen isotope ratios were determined with a Thermo Scientific Delta Plus isotope ratio mass spectrometer connected to a Thermo Scientific TC/EA elemental analyzer and configure through a Thermo Scientific CONFLO IV for automated continuous-flow analysis. Samples were analyzed for stable carbon and nitrogen isotope ratios at the University of Arkansas using a Thermo-Finnigan DeltaPlus isotope ratio mass spectrometer connected to an Carlo Erba elemental analyzer. Two standards analyzed with feather and RBC samples included USGS40 and BHCO (powdered brown-headed cowbird (Molothrus ater) feather) used extensively as a lab standard as documented by Kelly et al. [51]. Stable isotope ratios are expressed in standard notation, where δ2H, δ13C, and δ15N = [(isotope ratiosample/isotope ratiostandard)– 1] x 1000. Consequently, δ2H, δ13C, and δ15N are expressed in parts per thousand (‰) deviation from a standard (δ2H: Vienna Standard Mean Ocean Water, δ13C: Vienna Pee Dee Belemnite, δ15N:Air). Measurement of the three keratin reference materials corrected for linear instrumental drift were both accurate and precise with mean δ2H ± standard deviation of -198.0 ± 0.4‰ (CBS), -55.8 ± 0.7‰ (KHS), and -120 ± 1.8‰ (SKP). Likewise, repeated analysis of δ13C and δ15N standards were -26.2 ± 0.3‰ (δ13C USGS40), -4.2 ± 0.3‰ (δ15N USGS40), -15.7 ± 0.1‰ (δ13C BHCO), and 7.6 ± 0.1‰ (δ15N BHCO). We ran standards and a replicate sample every 10th sample and flagged any replicate sample that differed by > 6‰.

Statistical analysis

We conducted all statistical analyses in R version 3.6.0 (R Core Team 2019) using the packages lme4 [52], lmerTest [53], and lsmeans [54]. We used general linear mixed models (GLMM) to separately examine differences in δ2H, δ13C, and δ15N values among tissue types (δ2H: feathers, RBC, plasma; δ13C, δ15N: feathers, RBC) and species (‘apapane, Hawaiʻi ‘amakihi). Individual was included as a random effect in each model to account for multiple tissues collected from the same individual. We assumed statistical significance at alpha ≤ 0.05, but with multiple comparisons we conducted a Tukey’s post-hoc analysis of least squared means to determine differences among significant factors. Prior to running GLMMs we adjusted δ2H feather values by -19.8‰ to account for tissue-specific discrimination between feathers and blood [34]. We adjusted δ2H feather values based on the average difference in tissue discrimination factors of feathers and blood plasma (-18.6‰±4.4‰) and feathers and RBCs (-21‰±1.5‰) calculated from an experiment with house sparrows (Passer domesticus), the species most closely related to Hawaiian honeycreepers with tissue-specific discrimination values [38]. RBCs and blood plasma do not differ in isotopic discrimination of 2H; therefore, we did not adjust these tissue types [32, 33, 38, 39]. We did not adjust δ13C and δ15N feather values prior to analysis because tissue-specific discrimination factors for δ13C and δ15N are highly sensitive to diet [36, 55] and discrimination factors have not been established for a nectarivore. In addition, published discrimination factors have primarily been calculated for feathers and whole blood, but not RBCs [36, 55, 56]. Instead, similar to the approach of Podlesak et al. [36] we examined only general changes in diet by considering differences in δ13C and δ15N values between feathers and RBCs greater than 2‰ to be indicative of a change in diet.

We estimated the elevation of feather growth for feather samples collected at our study sites based on the relation between elevation and stable hydrogen isotopes in precipitation (δ2Hp) for wet tropical forests on the east side of Hawaiʻi Island, δ2Hp = -0.018(elevation) -11.25. We derived the relationship between δ2Hp and elevation using published volume-weighted average δ2Hp values collected from 50 locations sampled across east Hawaiʻi Island, including sample locations within the Kaʻū Forest, and ranging in elevation from 6 to 4000 meters ([57] Appendix 1). Scholl et al. [57] calculated volume-weighted average δ2Hp values for each location based on rainfall samples collected at 6-month intervals between August 1991 to August 1994. Because all three rain patterns (i.e., trade winds, rain shadow, high elevation) are present in the Kaʻū Forest we used all sampling locations representing these rainfall patterns to establish the relationship between δ2Hp and elevation for the Kaʻū Forest. Prior to estimating elevation, we adjusted stable hydrogen isotopes in feathers (δ2Hf) to reflect δ2Hp utilizing a conversion equation from a species in the same foraging guild as our study species, Rufous hummingbird (Selasphorus rufus). As nectarivores, hummingbirds and Hawaiian honeycreepers receive most of their hydrogen from plant-derived water and plant-derived carbohydrates through consumption of large quantities of nectar. Thus, in the absence of a species-specific conversion equation for our species [58], hummingbirds likely provide the best approximation of the relation between feather and precipitation δ2H values for Hawaiian honeycreepers. The equation, δ2Hp = 1.15(δ2Hf) + 29.01, was calculated based on Rufous hummingbird feathers grown at known locations across North America [59]. The same relation between δ2Hf and δ2Hp was also found for Ruby-throated hummingbirds (Archilochus colubris) [60], indicating a consistent relation between δ2Hf and δ2Hp for nectarivorous birds.

Results

We captured a total of 102 birds during the 2-month time period (δ2H analysis: ‘apapane = 60, ‘amakihi = 42; δ13C and δ15N analysis: ‘apapane = 51, ‘amakihi = 36). We found significant differences in δ2H values among tissues taking into account individual variability (F2,118.3 = 172.5, p<0.001) with patterns not differing between species (F1,99.7 = 1.6, p = 0.21). Feathers had the highest mean δ2H values followed by RBCs, and then blood plasma (Fig 2). The average difference in δ2H values between feathers and blood plasma collected from the same individual was 40.7‰ (range 24.0–62.5‰), suggesting feathers were grown at lower elevations than the capture location represented by the blood plasma sample. The average difference in δ2H values between RBCs and blood plasma of the same individual was 32.3‰ (range 23.9–41.4‰).

Fig 2. Stable hydrogen isotope (δ2H) values (± SE) for plasma, red blood cells (RBC), and feathers adjusted for tissue discrimination collected from ‘apapane and Hawaiʻi ‘amakihi in the upper Kaʻū Forest.

Fig 2

Letters above bars indicate tissue types that are significantly different from one another based on a Tukey’s post-hoc analysis.

Based on the relationship between δ2Hp and elevation on the east side of Hawaiʻi Island we found the average estimated elevation of feather growth (1501 m, range 505 to 2528 m) was lower than the elevation of all three capture locations (1615 m, 1968 m, 2191 m) (Fig 3). The average distance between the elevation of a birdʻs capture location and estimated elevation of feather growth was 562 m (range 5–1686 m) with the distance between capture and molt elevation increasing with increasing elevation of the capture location (Table 1). All of the honeycreepers captured at our highest elevation site were estimated to have grown their feathers at lower elevations with on average 1008 m (range 193–1686 m) between the capture site and the estimated molt location. In contrast, 83% and 45% of honeycreepers captured at the other two sites (1968 m, 1615 m) had an estimated molt location lower than their capture location.

Fig 3. Estimated elevation of feather growth for Hawaiʻi ‘amakihi and ‘apapane captured during the fall in upper Kaʻū Forest.

Fig 3

Dashed lines represent the elevations of the three capture sites.

Table 1. For each capture location, the sample size (n) and mean, minimum, and maximum difference in elevation between a birdʻs capture location and their estimated molt location.

Site numbers refer to the locations indicated in Fig 1.

      Difference in elevation of capture and estimated molt location
Site Elevation (m) n Mean (m) Minimum (m) Maximum (m)
1 1615 33 231 9 913
2 1968 35 442 5 1248
3 2191 34 1008 193 1686

We found significantly higher δ13C and δ15N values of feathers compared to RBC values (δ13C: F1,86 = 161.4, p<0.001, δ15N: F1,86 = 30.3, p<0.001) with overall higher δ13C and δ15N values for Hawaiʻi ‘amakihi compared to ‘apapane (δ13C: F1,85 = 36.5, p<0.001, δ15N: F1,85 = 4.2, p = 0.04) (Fig 4). However, for ʻapapane the average difference in isotope values between feathers and RBCs collected from the same individual was less than 2‰ (δ13C: 0.9‰, range -0.3 to 2.6‰, δ15N: 1.3‰, range -3.0 to 4.0‰) (Fig 5). In contrast, for Hawaiʻi ʻamakihi almost half (δ13C: 42%, δ15N: 44%) of the individuals captured had differences in isotope values between feathers and RBCs greater than 2‰ (δ13C: 2.0‰, range -1.9 to 3.6‰, δ15N: 2.6‰, range -3.2 to 8.2‰) (Fig 5).

Fig 4.

Fig 4

(A) Stable carbon isotope (δ13C) and (B) stable nitrogen isotope (δ15N) values (± SE) for red blood cells (RBC) and feathers collected for ‘apapane and Hawaiʻi ‘amakihi in the upper Kaʻū Forest.

Fig 5.

Fig 5

Boxplots showing the difference in (A) stable carbon isotope (δ13C) and (B) stable nitrogen isotope (δ15N) values between feathers and red blood cells collected from ‘apapane and Hawaiʻi ‘amakihi in the upper Kaʻū Forest. Box plot whiskers depict the 10th and 90th percentiles and boxes show the 25th and 75th percentiles with the median value indicated; circles represent outliers.

Discussion

We demonstrate that collecting multiple tissue samples, which grow at different rates or time periods, from a single individual can provide insights into elevational movements over an extended time period. By examining stable hydrogen isotope values from a feather, RBCs, and blood plasma collected from the same individual during the fall, we documented elevational movements for ‘apapane and Hawaiʻi ‘amakihi between the summer, the period of peak feather molt following breeding, and the time around capture in the fall, represented by the blood plasma sample. RBCs provide information on movement between the two periods given the longer residency time of isotopes in RBCs (6 to 8 weeks) compared to plasma (~3 to 5 days) [32, 33, 37].

Consistent with our predictions based on the elevational-migration hypothesis we found that the majority of ‘apapane and Hawaiʻi ‘amakihi captured at high elevation sites in the fall where not year-round residents at the capture locations, but had molted their feathers at lower elevations presumably in the summer after breeding. δ2H values of feathers adjusted for tissue-specific discrimination for all ‘apapane and Hawaiʻi ‘amakihi sampled were higher than blood plasma isotope values, and the direction and magnitude of difference between δ2H values of feathers and blood plasma indicates that feathers were grown at lower elevations than their capture location. Likewise, estimations of the elevation of feather growth based on the relationship between δ2Hp and elevation on the east side of Hawaiʻi Island indicated that the average elevation of feather growth was around 1500m, which is below all three capture locations. Seventy-five percent of the birds captured had an estimated elevation of feather growth below their capture location, with primarily only birds captured at the lowest elevation capture site deviating from this pattern. The molting of feathers at lower elevations than the high elevation capture sites is also consistent with survey data during the breeding season showing the highest densities of ‘apapane and Hawaiʻi ‘amakihi in the Kaʻū Forest around 1500m [43]. Moreover, the closer proximity of δ2H values of RBCs to adjusted δ2H of feathers (average difference = 10.1‰) compared to plasma (average difference 32.3‰), indicates that birds may have 1) recently migrated to higher elevations, and still retain isotopes from lower elevations among their RBCs, 2) that birds are making daily long-distance movements to forage within both high and low elevation areas, and the isotope signature of RBCs represents an integration of both locations, or 3) some combination of the two scenarios. Visual observations of large numbers of birds making morning flights above the canopy from lower elevations forests, that were not in bloom, to flowering ʻōhiʻa trees at the high elevation capture sites in the fall (E. Paxton personal observations) is consistent with the second scenario. Collectively, the isotope results from multiple tissues provides empirical evidence for seasonal elevational migrations of both ‘apapane and Hawaiʻi ‘amakihi after the breeding season to high elevation sites within the Kaʻū Forest that have heavy ʻōhiʻa bloom.

Surprisingly, we did not find a difference in the propensity of elevational movement between ‘apapane and Hawaiʻi ‘amakihi. Given differences in the foraging strategies of ‘apapane, a nectivore, and Hawaiʻi ‘amakihi, a generalist, we predicted that ‘apapane would be more likely to make elevational movements in search of seasonally variable nectar resources while Hawaiʻi ʻamakihi would be more likely to switch diets when ʻōhiʻa bloom is scarce. However, our results, along with other studies [9, 61, 62] indicate that there may be more overlap in the foraging strategies of these two species, particularly at times when resources are highly concentrated. ʻŌhiʻa accounts for 90% of the trees and shrubs producing nectar in Hawaiian wet forests from sea level to tree line [12, 17], but the bloom of ʻōhiʻa is not uniform in space and time and the timing of peak flowering varies depending on a siteʻs elevation, substrate age, and genetic variation of ʻōhiʻa varieties present [14, 15, 17]. High elevation ʻōhiʻa varieties polymorpha and incana bloom in fall and winter, whereas lower elevation varieties such as glaberrima have peak bloom primarily in spring [15, 17, 46]. Differences in the timing of bloom by variety and elevation creates spatially and temporaly variable distributions of bloom that may drive elevational migration. Indeed, the mature stature ʻōhiʻa forest below our capture sites had virtually no bloom and the forest was quiet with little bird activity detected. In contrast, the low stature ʻōhiʻa patches where we captured birds in the fall had heavy bloom and high densities of birds, which were evident by both sight and auditory detection (E. Paxton personal observations). The high energy content of nectar compared to arthropods [63], may make long distant flights to track nectar resources across the landscape beneficial from an energetic consideration (e.g., [11]) for not only true nectivores like ʻapapane and ʻiʻiwi (Drepanis coccinea), but also Hawaiʻi ʻamakihi, especially when high volumes of nectar are concentrated in a particular area like the high elevation capture sites in this study. ‘Apapane are conspicous when moving long distances, flying above the canopy, whereas Hawaiʻi ‘amakihi are rarely seen flying above the canopy and likely move within or below the forest canopies (E. Paxton personal observations). Differences in the conspicuousness of the two speciesʻ flight patterns potentially associated with different foraging strategies may account for the perception that Hawaiʻi ‘amakihi do not move as much as ‘apapane. A better understanding of the consistency of bloom patterns across time within the Kaʻū Forest and other forests in Hawaiʻi would help to shed light on the mechanisms underlying the patterns found in this study.

The incorporation of carbon and nitrogen stable isotopes provides further evidence for the use of nectar resources by Hawaiʻi ʻamakihi at the high elevation capture sites in the fall. Hawaiʻi ʻamakihi and ‘apapane both had significant differences between δ13C and δ15N values of feathers and RBCs. However, the average difference between tissue types for ‘apapane was less than 2‰, indicating that for the majority of ‘apapane the change in isotope values between feathers and RBCs most likely represents only differences in tissue discrimination of isotopes [36, 55, 56], and not a shift in diet between seasons. In contrast, the majority of Hawaiʻi ʻamakihi had differences in isotope values between feathers and RBCs greater than 2‰, suggesting differences in isotope values between feathers and RBCs most likely represents a shift in diet between seasons. The high variability in δ13C and δ15N values of Hawaiʻi ʻamakihi also indicated that they had a more diverse diet across trophic levels than ʻapapane, particularly during the post-breeding period of feather molt. However, the greater depletion of N in RBC samples compared to feather samples of Hawaiʻi ʻamakihi indicated a greater reliance in the fall on nectar which is more depleted in N [34, 64]. The incorporation of δ13C and δ15N from plasma or breath samples in future studies would help to elicudate the role of nectar in the diet at the time of capture. In addition, tissue-specific discrimination factors for our study species or a comparable nectarivore species would allow for a more precise understanding of changes in diet between seasons.

The Hawaiian Archipelago, and particularly Hawaiʻi Island, is ideal for studying elevational movements with δ2H because of large elevational gradients (e.g., 0–4000 m) that occur across small geographic areas, resulting in a strong gradient of δ2Hp values that are driven by changes in elevation and not latitude. The rate of change in δ2Hp across elevations in Hawaiʻi (~1.8‰ per 100m) is consistent with other mountainous systems (e.g. Appalachian and Ecuadorian Andes Mountains) [24, 28, 31] and global patterns of precipitation (e.g., IAEA value for Hilo; [57]). However, unlike other tropical systems that have large seasonality in rainfall patterns (e.g., wet and dry seasons), which can result in different isotopic values between seasons [27], rainfall patterns on the Hawaiian Islands are largely driven by trade-winds resulting in consistent annual and seasonal δ2H values across elevations [44, 65]. While storm systems during the winter months, when trade-winds are less frequent, can sometimes result in lower δ2Hp values than expected, there was not an increase in storm events (>50mm rainfall in one event; definition given by [57]) during the time period of the study (NOAA National Climate Data Center for Hilo, Hawaiʻi, Network ID: GHCND:USW00021504).

Mobile animals such as birds can move across the landscape irespective of jurisdictional boundaries, which creates unique managment and conservation problems. Much of Ka’ū Forest is managed by Hawaiʻi Division of Forestry and Wildlife; however, the upper portion of the forest, where our study sites were located, is within the boundaries of Hawaiʻi Volcanoes National Park. Our study indicates that birds in the Ka’ū Forest move between the two reserves, and may be dependent on two different management entities, highlighting the importance of understaning movement of birds across the landscape, and how that movement connects different spatial areas over time. Ultimately, conservation of Hawaiian forest birds such as the ‘apapane and Hawaiʻi ‘amakihi may depend on the joint-management of lands under different owerships to ensure that habitat quality and protection is sufficient for the birds across the annual cycle.

Acknowledgments

Darcy Hu (National Park Service) was a key supporter of the project, and helped shape study design. Field work was conducted by Nolan Lancaster, Sonia Levitz, and Keith Burnett. We thank Hawaiʻi Volcanoes National Park for land access.

Data Availability

All data is available at a USGS data repository called ScienceBase-Catalog with the following citation and url: Paxton KL, Kelly JF, Pletchet SM, Paxton EH. 2020. Hawaii Volcanoes National Park stable isotope values from Hawaii forest birds 2012. U.S. Geological Survey data release: https://doi.org/10.5066/P98I4EP7.

Funding Statement

Funding for this study was provided to EHP through a U.S. Geological Survey Natural Resource Preservation Project grant. KLP was supported by a National Science Foundation (NSF) Centers for Research Excellence in Science and Technology (CREST) grant (0833211). JFK was supported by NSF grant EF-1840230. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Alerstam T, Hedenström A, Åkesson S. Long distance migration: evolution and determinants. Oikos. 2003;103(2):247–60. [Google Scholar]
  • 2.Dingle H, Drake VA. What is migration? Bioscience. 2007;57(2):113–21. [Google Scholar]
  • 3.Boyle WA. Altitudinal bird migration in North America. The Auk. 2017;134(2):443–65. 10.1642/auk-16-228.1 [DOI] [Google Scholar]
  • 4.Hsiung AC, Boyle WA, Cooper RJ, Chandler RB. Altitudinal migration: ecological drivers, knowledge gaps, and conservation implications. Biol Rev Camb Philos Soc. 2018;93(4):2049–70. 10.1111/brv.12435 [DOI] [PubMed] [Google Scholar]
  • 5.Loiselle BA, Blake JG. Temporal variation in birds and fruits along an elevational gradient in Costa Rica. Ecology. 1991;72(1):180–93. [Google Scholar]
  • 6.Levey DJ, Stiles FG. Evolutionary precursors of long-distance migration: resource availability and movement patterns in Neotropical landbirds. The American Naturalist. 1992;140(3):447–76. [Google Scholar]
  • 7.Boyle WA, Norris DR, Guglielmo CG. Storms drive altitudinal migration in a tropical bird. Proceedings of Royal Society B. 2010;277(1693):2511–9. 10.1098/rspb.2010.0344 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Perkins RCL. Vertebrata In: Sharp D, editor. Fauna Hawaiiensis. 1 Cambridge, United Kingdom: University Press; 1903. p. 365–466. [Google Scholar]
  • 9.Baldwin PH. Annual cycle, environment and evolution in the Hawaiian honeycreepers (Aves: Drepaniidae). Univ Calif Publ Zool; 1953;52:285–398. [Google Scholar]
  • 10.Warner RE. The role of introduced diseases in the extinction of the endemic Hawaiian avifauna. The Condor. 1968;70(2):101–20. [Google Scholar]
  • 11.MacMillen RE, Carpenter FL. Evening roosting flights of the honeycreepers Himatione sanguinea and Vestiaria coccinea on Hawaii. The Auk. 1980;97(1):28–37. [Google Scholar]
  • 12.Mueller-Dombois D, Fosberg FR. Vegetation of the tropical Pacific islands: Springer Science & Business Media; 2013. [Google Scholar]
  • 13.van Dyk KN, Paxton KL, Hart PJ, Paxton EH. Seasonality and prevalence of pollen collected from Hawaiian nectarivorous birds. Pacific Science. 2019;73(2):187–97. [Google Scholar]
  • 14.Cordell S, Goldstein G, Meinzer FC, Handley LL. Allocation of nitrogen and carbon in leaves of Metrosideros polymorpha regulates carboxylation capacity and δ13C along an altitudinal gradient. Functional Ecology. 1999;13(6):811–8. [Google Scholar]
  • 15.Berlin KE, Simon JC, Pratt TK, Kowalsky JR, Hatfield JS. Akohekohe response to flower availability: seasonal abundance, foraging, breeding, and molt. Stud Avian Biol. 2001;22:202–12. [Google Scholar]
  • 16.Guillaumet A, Kuntz WA, Samuel MD, Paxton EH. Altitudinal migration and the future of an iconic Hawaiian honeycreeper in response to climate change and management. Ecological Monographs. 2017;87(3):410–28. [Google Scholar]
  • 17.Hart PJ, Woodworth BL, Camp RJ, Turner K, McClure K, Goodall K, et al. Temporal variation in bird and resource abundance across an elevational gradient in Hawaii. The Auk. 2011;128(1):113–26. [Google Scholar]
  • 18.Ralph CJ, Fancy SG. Demography and movements of Apapane and Iiwi in Hawaii. The Condor. 1995;97(3):729–42. [Google Scholar]
  • 19.Pratt LW, Jacobi JD. Loss, degradation, and persistence of habitats In: Pratt TK, Atkinson CT, Banko PC, J.D. J, Woodworth BL, editors. Conservation Biology of Hawaiian Forest Birds New Haven, CT: Yale University Press; 2009. p. 137–58. [Google Scholar]
  • 20.Banko WE, Banko PC. Historic decline and extinction In: Pratt TK, Atkinson CT, Banko PC, J.D. J, Woodworth BL, editors. Conservation Biology of Hawaiian Forest Birds. New Haven, CT: Yale University Press; 2009. p. 25–58. [Google Scholar]
  • 21.Atkinson CT, LaPointe DA. Introduced avian diseases, climate change, and the future of Hawaiian honeycreepers. J Avian Med Surg. 2009;23(1):53–63. 10.1647/2008-059.1 [DOI] [PubMed] [Google Scholar]
  • 22.Bridge ES, Thorup K, Bowlin MS, Chilson PB, Diehl RH, Fléron RW, et al. Technology on the move: recent and forthcoming innovations for tracking migratory birds. Bioscience. 2011;61(9):689–98. [Google Scholar]
  • 23.Hobson KA. Application of isotopic methods to tracking animal movements In: Hobson KA, Wassenaar LI, editors. Tracking Animal Migration with Stable Isotopes: Elsevier; 2019. p. 85–115. [Google Scholar]
  • 24.Hobson KA, Wassenaar LI, Mila B, Lovette I, Dingle C, Smith TB. Stable isotopes as indicators of altitudinal distributions and movements in an Ecuadorean hummingbird community. Oecologia. 2003;136(2):302–8. 10.1007/s00442-003-1271-y [DOI] [PubMed] [Google Scholar]
  • 25.Boyle WA, Guglielmo CG, Hobson KA, Norris DR. Lekking birds in a tropical forest forego sex for migration. Biol Lett. 2011;7(5):661–3. 10.1098/rsbl.2011.0115 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Newsome SD, Sabat P, Wolf N, Rader JA, Martinez Del Rio C. Multi-tissue d2H analysis reveals altitudinal migration and tissue-specific discrimination patterns in Cinclodes. Ecosphere. 2015;6(11). [Google Scholar]
  • 27.Villega M, Newsome SD, Blake JG. Seasonal patterns in δ2H values of multiple tissues from Andean birds provide insights into elevational migration. Ecological Applications. 2016;26(8):2381–7. 10.1002/eap.1456 [DOI] [PubMed] [Google Scholar]
  • 28.Hardesty JL, Fraser KC. Using deuterium to examine altitudinal migration by Andean birds. Journal of Field Ornithology. 2010;81(1):83–91. 10.1111/j.1557-9263.2009.00264.x [DOI] [Google Scholar]
  • 29.Poage MA, Chamberlain CP. Empirical relationships between elevation and the stable isotope composition of precipitation and surface waters: considerations for studies of paleoelevation change. American Journal of Science. 2001;301(1):1–15. [Google Scholar]
  • 30.Bowen G, Wilkinson B. Spatial distribution of d18O in meteoric precipitation. Geology 30, 315e318 2002. [Google Scholar]
  • 31.Graves GR, Romanek CS, Navarro AR. Stable isotope signature of philopatry and dispersal in a migratory songbird. Proceedings of the National Academy of Sciences. 2002;99(12):8096–100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Wolf N, Newsome SD, Fogel ML, Martinez Del Rio C. An experimental exploration of the incorporation of hydrogen isotopes from dietary sources into avian tissues. J Exp Biol. 2012;215(11):1915–22. 10.1242/jeb.065219 [DOI] [PubMed] [Google Scholar]
  • 33.Storm-Suke A, Norris DR, Wassenaar LI, Chin E, Nol E. Factors influencing the turnover and net isotopic discrimination of hydrogen isotopes in proteinaceous tissue: experimental results using Japanese quail. Physiol Biochem Zool. 2012;85(4):376–84. 10.1086/666476 [DOI] [PubMed] [Google Scholar]
  • 34.Martínez del Rio C, Wolf N, Carleton SA, Gannes LZ. Isotopic ecology ten years after a call for more laboratory experiments. Biological Reviews. 2009;84(1):91–111. 10.1111/j.1469-185X.2008.00064.x [DOI] [PubMed] [Google Scholar]
  • 35.Chamberlain C, Blum J, Holmes RT, Feng X, Sherry T, Graves GR. The use of isotope tracers for identifying populations of migratory birds. Oecologia. 1997;109(1):132–41. [DOI] [PubMed] [Google Scholar]
  • 36.Podlesak DW, McWilliams SR, Hatch KA. Stable isotopes in breath, blood, feces and feathers can indicate intra-individual changes in the diet of migratory songbirds. Oecologia. 2005;142(4):501–10. 10.1007/s00442-004-1737-6 [DOI] [PubMed] [Google Scholar]
  • 37.McKinnon EA, Fraser KC, Diamond AW, Rimmer CC, Townsend JM. Stable-hydrogen isotope turnover in red blood cells of two migratory thrushes: application to studies of connectivity and carry-over effects. Journal of Field Ornithology. 2012;83(3):306–14. 10.1111/j.1557-9263.2012.00380.x [DOI] [Google Scholar]
  • 38.Wolf N, Bowen GJ, Del Rio CM. The influence of drinking water on the dD and d18O values of house sparrow plasma, blood and feathers. J Exp Biol. 2011;214(Pt 1):98–103. 10.1242/jeb.050211 [DOI] [PubMed] [Google Scholar]
  • 39.Wolf N, Newsome SD, Fogel ML, Del Rio MC. The relationship between drinking water and the hydrogen and oxygen stable isotope values of tissues in Japanese quail (Cortunix japonica). The Auk. 2013;130(2):323–30. [Google Scholar]
  • 40.Fancy SG, Ralph CJ. Apapane (Himatione sanguinea) In: Poole A, Gill F, editors. In The Birds of North America, No 296 Ithaca, NY: Cornell Lab of Ornithology; 1997. [Google Scholar]
  • 41.Lindsey GD, VanderWerf EA, Baker H, P.E. B. Hawaii Amakihi (Chlorodrepanis virens) In: Poole A, editor. The Birds of North America. Ithaca, NY: Cornell Lab of Ornithology; 1998. [Google Scholar]
  • 42.Eggert LS, Terwilliger LA, Woodworth BL, Hart PJ, Palmer D, Fleischer RC. Genetic structure along an elevational gradient in Hawaiian honeycreepers reveals contrasting evolutionary responses to avian malaria. BMC Evol Biol. 2008;8:315 10.1186/1471-2148-8-315 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Gorresen PM, Camp RJ, Pratt TK. Forest bird distribution, density and trends in the Ka`ū region of Hawai`i Island. 2007. US Geological Survey Open-File Report. [Google Scholar]
  • 44.Scholl MA, Ingebritsen SE, Janik CJ, Kauahikaua JP. Use of precipitation and groundwater isotopes to interpret regional hydrologyon a tropical volcanic island: Kilauea volcano area, Hawaii. Water Resources Research 1996;32(12):3525–37. [Google Scholar]
  • 45.Paxton EH, McLaughlin R, Levins S, Vanderwerf E, Lancaster N. Aging and sexing guide to the forest birds of Hawai ‘i Island. Hilo, HI: University of Hawai'i at Hilo, 2016. [Google Scholar]
  • 46.Ralph CJ, Fancy SG. Timing of breeding and molting in six species of Hawaiian honeycreepers. Condor. 1994;96:151–61. [Google Scholar]
  • 47.Freed LA, Cann RL. Changes in timing, duration, and symmetry of molt of Hawaiian forest birds. PLoS ONE. 2012;7(1):e29834 10.1371/journal.pone.0029834 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Chew B, Kelly J, Contina A. Stable isotopes in avian research: a step by step protocol to feather sample preparation for stable isotope analysis of carbon (δ13C), nitrogen (δ15N), and hydrogen (δ2H). Version 1.1. protocolsio. 2019. dx.doi.org/10.17504/protocols.io.z2uf8ew. [Google Scholar]
  • 49.Bearhop S, Waldron S, Votier SC, Furness RW. Factors that influence assimilation rates and fractionation of nitrogen and carbon stable isotopes in avian blood and feathers. Physiological and Biochemical Zoology. 2002;75(5):451–8. 10.1086/342800 [DOI] [PubMed] [Google Scholar]
  • 50.Wassenaar L, Hobson K. Comparative equilibration and online technique for determination of non-exchangeable hydrogen of keratins for use in animal migration studies. Isotopes in Environmental and Health Studies. 2003;39(3):211–7. 10.1080/1025601031000096781 [DOI] [PubMed] [Google Scholar]
  • 51.Kelly JF, Bridge ES, Fudickar AM, Wassenaar LI. A test of comparative equilibration for determining non-exchangeable stable hydrogen isotope values in complex organic materials. Rapid Communications in Mass Spectrometry. 2009;23(15):2316–20. 10.1002/rcm.4150 [DOI] [PubMed] [Google Scholar]
  • 52.Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. Journal of Statistical Software. 2015;67:1–48. 10.18637/jss.v067.i01 [DOI] [Google Scholar]
  • 53.Kuznetsova A, Brockhoff PB, Christensen RHB. lmerTest package: tests in linear mixed effects models. Journal of Statistical Software. 2017;82(13):1–26. 10.18637/jss.v082.i13. [DOI] [Google Scholar]
  • 54.Lenth R, Lenth MR. Package ‘lsmeans’. The American Statistician. 2018;34(4):216–21. [Google Scholar]
  • 55.Pearson SF, Levey DJ, Greenberg CH, Martinez Del Rio C. Effects of elemental composition on the incorporation of dietary nitrogen and carbon isotopic signatures in an omnivorous songbird. Oecologia. 2003;135(4):516–23. 10.1007/s00442-003-1221-8 [DOI] [PubMed] [Google Scholar]
  • 56.Hobson KA, Bairlein F. Isotopic fractionation and turnover in captive Garden Warblers (Sylvia borin): implications for delineating dietary and migratory associations in wild passerines. Can J Zool. 2003;81(9):1630–5. 10.1139/z03-140. [Google Scholar]
  • 57.Scholl MA, Ingebritsen SE, Janik CJ, Kauahikaua JP. An Isotope hydrology study of the Kilauea volcano area, Hawaii U.S. Geological Survey, 1995. [Google Scholar]
  • 58.Nordell CJ, Hache S, Bayne EM, Solymos P, Foster KR, Godwin CM, et al. Within-Site Variation in Feather Stable Hydrogen Isotope (delta2Hf) Values of Boreal Songbirds: Implications for Assignment to Molt Origin. PLoS ONE. 2016;11(11):e0163957 10.1371/journal.pone.0163957 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Moran JA, Wassenaar LI, Finlay JC, Hutcheson C, Isaac LA, Wethington SM. An exploration of migratory connectivity of the Rufous Hummingbird (Selasphorus rufus), using feather deuterium. J Ornithol. 2012;154(2):423–30. 10.1007/s10336-012-0906-3 [DOI] [Google Scholar]
  • 60.Hutcheson CA, Hendrix L, Moran JA. An isotopic analysis of migratory connectivity in Ruby-throated Hummingbirds. N Am Bird Bander. 2010;35:5–11. [Google Scholar]
  • 61.Carpenter FL. Food abundance and territoriality: to defend or not to defend? American Zoologist. 1987;27(2):387–99. [Google Scholar]
  • 62.Pimm SL, Pimm JW. Resource use, competition, and resource availability in Hawaiian honeycreepers. Ecology. 1982;63(5):1468–80. [Google Scholar]
  • 63.Ford HA, Paton DC. The value of insects and nectar to honeyeaters. Emu. 1976;76(2):83–4. [Google Scholar]
  • 64.Symes CT, McKechnie AE, Nicolson SW, Woodborne SM. The nutritional significance of a winterterrs. Ecology. 1982;63(5):1468-80.tic avian nectarivores. Ibis. 2011;153(1):110–21. [Google Scholar]
  • 65.Scholl MA, Gingerich SB, Tribble GW. The influence of microclimates and fog on stable isotope signatures used in interpretation of regional hydrology: East Maui, Hawaii. Journal of Hydrology. 2002;264:1–4. [Google Scholar]

Decision Letter 0

David P Gillikin

23 Mar 2020

PONE-D-19-34295

Stable isotope analysis of multiple tissues from Hawaiian honeycreepers indicates elevational movement

PLOS ONE

Dear Dr. Paxton,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

The main points that both reviewers make is that you need to find discrimination factors between blood and feathers for these species. They also include many other useful comments. Please be sure to look at Reviewer 1 comments in the attached word file. 

We would appreciate receiving your revised manuscript by May 07 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

David P. Gillikin, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I enjoyed reading this manuscript very much. The grammar and clarity made it easy to review. The authors have used tissue stable isotopes in a fascinating, appropriate, and somewhat novel way. My primary concern is with the application of a conversion equation for hummingbirds that may not be appropriate here and, specifically, may have artificially inflated the support for the elevation-migrant hypothesis. When this problem is dealt with the manuscript is otherwise a worthy contribution to its field.

Reviewer #2: This paper uses stable isotopes of mainly hydrogen to explore the use of different elevations of two species of Hawaiian birds within a montane environment. The paper is well written and well thought out. Although the use of stable isotopes of hydrogen has been used in this context previously, and the authors present interesting results, they do not account for the discrimination factors between tissues and therefore the results are not interpreted correctly. The authors need to find discrimination factors between blood and feathers for these species they are interested in, or in a species that is somewhat similar to approximate it. After accounting for the discrimination factors between tissues (for each stable isotope separately, it will differ for carbon, hydrogen and nitrogen) then the authors can proceed with the analyses as they had. This may change their results of elevation pattern use for the two species and also differences in dietary niche. The authors mention discrimination factors in the discussion (lines 288-292), so they are clearly aware of this, however I think it is crucial that these are incorporated in their analyses and adding this as a discussion point is insufficient.

Below I make other recommendations with which to improve this manuscript.

Line 64: define the two terms frugivorous and nectivorous. Within the discussion also include some approximation of how these two diets may differ isotopically.

Line 72: which other feeding guilds are you referring to? Please provide an example or two.

Line 78: Do you mean that the birds “tracked the timing of the flowering ‘ōhi’a” ? If so, please change wording accordingly. I think this introduction would benefit from a sentence detailing when this tree flowers at which elevation and if there are other trees that flower in this area and when. It is a bit unclear to those that might not be familiar with this landscape.

Line 102: Define the term “orographically” or better yet write this sentence without such jargon. This paper will primarily be read by bird researchers who are unlikely to know such climatic terms.

Line 103-105: Stable isotopes of nitrogen is correlated with trophic level (becoming more and more enriched with the increase of trophic level) not hydrogen. Hydrogen is fairly insensitive to trophic level. There are a lot of papers out there outlining this, but these two are also.

G. Bowen et al 2005 Global application of stable hydrogen and oxygen isotopes to wildlife forensics. Oecologia 143: 337–348

K. Hobson et al 1994 Using stable isotopes to determine seabird trophic relationships. J. Animal Ecol. 63(4):786-798

Line 131-134: Here the authors even explicitly state that discrimination factors are important to consider, but then they’re not included in the analyses. Would suggest rewording this sentence to end with “as long as comparisons are made while also incorporating tissue-specific discrimination factors”. It is necessary to account for discrimination factors in your analyses. In line 146 you again write about discrimination values, yet don’t actually account for them as far as I can tell. Without accounting for discrimination between tissues you cannot be certain that any differences you see are due to elevation.

Line 135: why the windward side? Please explain. This could also be a good space to include details about the flowering cycle of the primary source of nectar.

Line 137: A sentence detailing the annual-cycle and timing of each stage is necessary here. When do the birds molt? Migrate to where? Breed?

Line 172: How come birds weren’t also sampled at lower elevations? Or are there no birds present at lower elevations at all?

Line 196: Could be helpful to include a figure outlining tissues and what time period they would reflect.

Line 201: Were plasma and RBC not lipid extracted? Why not? For stable isotopes of hydrogen it doesn’t really matter, but plasma is highly enriched in lipids, and therefore not lipid extracting can influence your stable isotopes of carbon values.

Line 208: Are you sure this is caribou and not cow? Should include references for these standards, and also the variation throughout your analyses of the standards (which is the whole reason they are included anyway, to ensure the stable isotope analysis is accurate throughout the analyses and doesn’t trend in one direction or the other indicating that the Mass Spec isn’t working). You should include average value +/- standard deviation for each standard and how often you analysed the standards throughout the analyses (often its every 5th or 10th sample). There should have also been duplicates of at least each 10th sample you analysed to ensure that the samples were homogenous.

Line 242: How come there are so many fewer samples for C/N? (guessing that the numbers for C are the same as for N, but you should also include that explicitly in your sample size here).

All of the analyses in the results sections need to be redone after accounting for discrimination factors between tissues. I’m sorry, this is always difficult to hear, but I think your paper will be much better after accounting for this. Otherwise you cannot be confident that the differences you see are actually because of elevational differences between different stages during the annual cycle. Other than this oversight, the statistical analyses are quite well done, and easy to follow.

Lin 289-292: Its obvious you are aware of these differences. You can pretty much remove this section once the analyses are re-done. Over half of the differences you saw in elevation are actually due to discrimination factors. Which means that the calculations you made for use of different elevations is actually incorrect, likely half of what you calculated.

Line 298-305: Not that I’m recommending this for this paper, but one alternative method you could consider for future exploration of use of different elevations is using VHF tags and a motus type network (widely used in eastern Canada/US). They are generally quite light weight and are a good alternative to GPS tags. Just a thought!

Line 332: Could these flight patterns also be due to differences in foraging strategies?

Line 343-345: You didn’t look at this in plasma? How come? (possible I missed this explanation in the methods).

Line 368: typo. “different” not “differnt”

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Cameron Nordell

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachment

Submitted filename: Comments.docx

PLoS One. 2020 Jul 15;15(7):e0235752. doi: 10.1371/journal.pone.0235752.r002

Author response to Decision Letter 0


19 May 2020

Dear Dr. Gillikin,

Please accept the revised manuscript (PONE-D-19-34295) titled: “Stable isotope analysis of multiple tissues from Hawaiian honeycreepers indicates elevational movement” for publication in PLOS ONE. We thank the two reviewers for their thorough and insightful comments. We have responded to the requested revisions, which have improved the manuscript. Please see below for more detailed responses (in blue) to comments made by the reviewers (in black). The page and line numbers indicated in our responses refer to line numbers in the revised manuscript with track changes. We hope you will find that we have addressed the comments of the reviewers and thank you for your consideration of the revised manuscript for publication in PLOS ONE.

Sincerely,

Kristina Paxton, PhD

University of Hawai‘i at Hilo

Response to Reviewers

Reviewer #1: Cameron Nordell

I enjoyed reading this manuscript very much. The grammar and clarity made it easy to review. The authors have used tissue stable isotopes in a fascinating, appropriate, and somewhat novel way. My primary concern is with the application of a conversion equation for hummingbirds that may not be appropriate here and, specifically, may have artificially inflated the support for the elevation-migrant hypothesis. When this problem is dealt with the manuscript is otherwise a worthy contribution to its field.

Grammatical Comments:

Line 38: In the abstract I believe you use the word “where” instead of “were”

Lines 201-202: You used the word “powered” instead of “powdered” twice.

Response: All grammatical errors were corrected

Specific Comments

Line 95-96

I find it imprecise to say that isotopes are incorporated into animal tissues through trophic level interactions. You might more closely reflect the relationship of animal tissues to isotopes by stating that they are incorporated through biochemical processes

(e.g. Breathing is, in part, responsible for the isotope ratios in an organism’s tissues).

Line 103-104

As with my comment on Line 95, I suggest that the δ2H isotope ratios in animal tissues reflect their environment not singularly because of trophic interactions.

You might also reconsider the use of the word “highly” to describe the relationship between tissues and δ2H isotope ratios, given the many confounding factors that obscure this relationship (e.g. evapotranspiration of environmental or biological water differs among individuals and perhaps small-scale location). I think the theme of quantifying the factors that obscure δ2HP and δ2H in animal tissues, in particular, is common in recent papers.

You might also consider the addition “expected to reflect the isotopic signatures of the elevation of feeding when the tissue was grown”

Response: As suggested we updated the text in the introduction to better represent how stable isotopes are incorporated into animal tissues and replaced ‘trophic interactions’ with ‘biochemical processes’. [lines 104, 116]

Line 157

I’d suggest that “greater inter-tissue variation” might better capture your meaning here.

Response: As suggested text was changed from ‘greater inter-tissue differences’ to ‘greater inter-tissue variation’ [line 178]

Line 189

Were tail feather selected for any reason? The outer tail feathers are molted last in many species. Is there a possibility to mis-classify some lower-elevation migrants as higher-elevation locals by sampling feathers that were recently replaced (i.e. outer tail feathers, the last replaced) at higher elevations? If this went unaccounted for, you might actually find stronger support for your elevational-migrant hypothesis.

Further, were the tail feathers counted from the center to determine the feather taken was the true outer feather and not the outermost that is not actively being replaced? Failure to account for this could introduce additional unwanted noise into your data.

Response: We choose tail feathers because they are a standard feather used for stable isotope analysis. For each bird captured, we assessed for the presence of molt and did not include birds that were actively molting tail feathers. Because all birds were sampled the same, any bias would be the same for all individuals. [line 215]

Lines 266-267.

The cutoff of 2‰ used to assert that differences between ‘apapane tissues owe to differential discrimination while in differences between tissues amakihi’ are due to diet changes seems arbitrary. Without stronger apriori assertions about 2‰ it seems equally valid to conclude that amakihi’ demonstrated a greater seasonal shift in diet than ‘apapane. Or that the isotope discrimination between the two tissues was greater in ‘apapane than amakihi’. Further, I’d suggest this is best left for the discussion rather than the results section.

Response: As suggested we moved the discussion of the results to the discussion section. [443-451] In addition, in the methods section we provided text to support our use of 2‰ as a discrimination factor between RBCs and feathers to assess large-scale changes in diet. [lines 280-286]

Line 272-274

Does the larger variation in δ13C not also suggest a more diverse diet? Regardless, this sentence might be best positioned in your discussion section.

Response: We agree with the reviewer and removed the text from the results section. In the discussion section we included text discussing support for ’amakihi having a more diverse diet than ‘apapane based on both δ13C and δ15N. [line 450-453]

Lines 352-355

I think this is an important distinction for your study area. Good inclusion.

Response: Thank you

General Comments

A) I assume all birds used in your study were AHY individuals? Is this simple to determine using plumage differences between AHY and HY? Other studies have found significant isotope ratio differences between AHY and HY individuals at the same breeding site. (Hache et al. 2012 - Assigning birds to geographic origin using feather hydrogen isotope ratios (δ2H): importance of year, age, and habitat)

Response: Yes there are distinct plumage differences between HY and AHY birds. All birds were aged and sexed using plumage, breeding characteristics, and size as described in Paxton et al. 2016 – Aging and sexing guide to the forest birds of Hawai’i Island. Over 90% of the birds in our study were AHY. We did not have a large enough sample size to test for differences between AHY and HY birds. [lines 212-215]

B) The most important concern with the manuscript: I am suspicious of the application of a conversion equation that describes the relationship between δ2HP and δ2Hf in hummingbirds to your study species. Elsewhere, among closely related species breeding in the same area, species-specific equations to convert δ2HP to δ2Hf appear to be necessary (Nordell et al. 2016 - Within-Site Variation in Feather Stable Hydrogen Isotope (δ2 Hf) Values of Boreal Songbirds: Implications for Assignment to Molt Origin).

I am no biochemist, but the particularly extreme metabolism of hummingbirds might lead to biochemical isotope discrimination at significantly greater rates than perhaps any other species.

I am not sure whether the fast hummingbird metabolism would incorporate light hydrogen or deuterium (heavy hydrogen) preferentially in metabolic processes. The worst case scenario for your manuscript would be that deuterium is more concentrated in hummingbird tissues than in your study species, which would lead you to predict δ2H values in your species originated at lower elevations than they truly did. In that case, you might find considerably less support for your elevation-migrant hypothesis.

I suggest you explore the literature to determine whether the use of the conversion equation for hummingbirds is valid (I don’t think the fact that they are nectivores is justification enough) and, if necessary, utilize a conversion equation more representative of your species (e.g. other fringilidae).

Response: We agree with the reviewer that it would be best to use a species-specific conversion equation. However, we did not have a species-specific conversion equation for our study species or any closely related species, so we used the best approximation available. As nectarivores, hummingbirds and Hawaiian honeycreepers receive most of their hydrogen from plant-derived water and plant-derived carbohydrates through consumption of large quantities of nectar. Thus, hummingbirds likely provide the best approximation of the relationship between feather and precipitation �2H values for Hawaiian honeycreepers. In the text, we discuss the need for species-specific equations, particularly for Hawaiian nectarvores. [lines 297-306]

Reviewer #2:

This paper uses stable isotopes of mainly hydrogen to explore the use of different elevations of two species of Hawaiian birds within a montane environment. The paper is well written and well thought out. Although the use of stable isotopes of hydrogen has been used in this context previously, and the authors present interesting results, they do not account for the discrimination factors between tissues and therefore the results are not interpreted correctly. The authors need to find discrimination factors between blood and feathers for these species they are interested in, or in a species that is somewhat similar to approximate it. After accounting for the discrimination factors between tissues (for each stable isotope separately, it will differ for carbon, hydrogen and nitrogen) then the authors can proceed with the analyses as they had. This may change their results of elevation pattern use for the two species and also differences in dietary niche. The authors mention discrimination factors in the discussion (lines 288-292), so they are clearly aware of this, however I think it is crucial that these are incorporated in their analyses and adding this as a discussion point is insufficient.

Below I make other recommendations with which to improve this manuscript.

Line 64: define the two terms frugivorous and nectivorous. Within the discussion also include some approximation of how these two diets may differ isotopically.

Response: As suggested we defined frugivorous and nectivorous in the text. [line 68]

Line 72: which other feeding guilds are you referring to? Please provide an example or two.

Response: As suggested we provided examples of the alternative feeding guilds that we referred to in the introduction. [line 76]

Line 78: Do you mean that the birds “tracked the timing of the flowering ‘ōhi’a” ? If so, please change wording accordingly. I think this introduction would benefit from a sentence detailing when this tree flowers at which elevation and if there are other trees that flower in this area and when. It is a bit unclear to those that might not be familiar with this landscape.

Response: As suggested we have added text in the introduction that provides more details about the phenology of ‘ōhi‘a and its importance as a nectar resource to Hawaiian honeycreepers. [lines 81 – 87]

Line 102: Define the term “orographically” or better yet write this sentence without such jargon. This paper will primarily be read by bird researchers who are unlikely to know such climatic terms.

Response: As suggested we have removed the word “orographically” and replaced the text with “over a mountain range” to make the text more understandable to a broad audience. [line 114]

Line 103-105: Stable isotopes of nitrogen is correlated with trophic level (becoming more and more enriched with the increase of trophic level) not hydrogen. Hydrogen is fairly insensitive to trophic level. There are a lot of papers out there outlining this, but these two are also.

G. Bowen et al 2005 Global application of stable hydrogen and oxygen isotopes to wildlife forensics. Oecologia 143: 337–348

K. Hobson et al 1994 Using stable isotopes to determine seabird trophic relationships. J. Animal Ecol. 63(4):786-798

Response: To clarify the text we have removed “trophic level interactions” and replaced it with “biochemical processes” to accurately reflect the relationship with between stable hydrogen isotopes in animal tissues and precipitation. [lines 115-117]

Line 131-134: Here the authors even explicitly state that discrimination factors are important to consider, but then they’re not included in the analyses. Would suggest rewording this sentence to end with “as long as comparisons are made while also incorporating tissue-specific discrimination factors”. It is necessary to account for discrimination factors in your analyses. In line 146 you again write about discrimination values, yet don’t actually account for them as far as I can tell. Without accounting for discrimination between tissues you cannot be certain that any differences you see are due to elevation.

Response: We have rewritten the text in the introduction as suggested.[lines 146-149]

Line 135: why the windward side? Please explain. This could also be a good space to include details about the flowering cycle of the primary source of nectar.

Response: In the text we replaced ‘windward’ with ‘east’ to clarify that this text is just referring to the location of the study area on Hawai‘i island. [lines 150-152] We added more text to the introduction, in an earlier paragraph, about the phenology of ‘ōhi‘a flowering to help readers not familiar with the study system. [lines 81-87]

Line 137: A sentence detailing the annual-cycle and timing of each stage is necessary here. When do the birds molt? Migrate to where? Breed?

Response: We provided more detailed information about the annual-cycle and timing of breeding and molt in the text of the introduction [line 153-155] and methods [lines 226-230].

Line 172: How come birds weren’t also sampled at lower elevations? Or are there no birds present at lower elevations at all?

Response: We added text to the methods section to indicate that birds were sampled at lower elevations, but no birds were captured most likely because densities of birds were so low. [lines 203-205]

Line 196: Could be helpful to include a figure outlining tissues and what time period they would reflect.

Response: We did not include a figure, but clearly outlined the time period that each tissue represents in the text. [lines 225-231]

Line 201: Were plasma and RBC not lipid extracted? Why not? For stable isotopes of hydrogen it doesn’t really matter, but plasma is highly enriched in lipids, and therefore not lipid extracting can influence your stable isotopes of carbon values.

Response: We did not extract lipids from plasma and RBCs due to the low proportion of lipids in bird blood. However, plasma samples were only included for stable hydrogen analysis and not carbon and nitrogen analysis. [lines 236-237]

Line 208: Are you sure this is caribou and not cow? Should include references for these standards, and also the variation throughout your analyses of the standards (which is the whole reason they are included anyway, to ensure the stable isotope analysis is accurate throughout the analyses and doesn’t trend in one direction or the other indicating that the Mass Spec isn’t working). You should include average value +/- standard deviation for each standard and how often you analysed the standards throughout the analyses (often its every 5th or 10th sample). There should have also been duplicates of at least each 10th sample you analysed to ensure that the samples were homogenous.

Response: We have added to the Methods section all information relating to the standards and their precision. [lines 255-258, lines 261-266]

Line 242: How come there are so many fewer samples for C/N? (guessing that the numbers for C are the same as for N, but you should also include that explicitly in your sample size here).

Response: Samples sizes differed between hydrogen and carbon/nitrogen analysis because of the differences in the amount of blood collected from each bird. We prioritized the stable hydrogen isotope analysis when blood volumes were too low for both analyses. We have included text in the methods section to clarify this point. [lines 215-222]

All of the analyses in the results sections need to be redone after accounting for discrimination factors between tissues. I’m sorry, this is always difficult to hear, but I think your paper will be much better after accounting for this. Otherwise you cannot be confident that the differences you see are actually because of elevational differences between different stages during the annual cycle. Other than this oversight, the statistical analyses are quite well done, and easy to follow.

Lin 289-292: Its obvious you are aware of these differences. You can pretty much remove this section once the analyses are re-done. Over half of the differences you saw in elevation are actually due to discrimination factors. Which means that the calculations you made for use of different elevations is actually incorrect, likely half of what you calculated.

Response: Given the lack of tissue-specific discrimination factors for our study species we originally choose to not adjust feather values prior to analysis, but to instead look at the magnitude of differences between tissues and assess whether the difference observed exceeded the offset expected based on general tissue discrimination values for hydrogen. However, in light of the reviewers comment we have re-run the general linear mixed model for stable hydrogen isotopes with feather values adjusted to account for tissue-specific discrimination between feathers and blood using the average tissue discrimination factor between feathers and blood calculated from an experiment with house sparrows, the species most closely related to Hawaiian honeycreepers with tissue-specific discrimination values.

[lines 273-280]

The new analysis does not change the overall conclusions of our study and still supports the elevational-migration hypothesis that the majority of birds captured at the high elevation sites where not year-round residents, but had molted their feathers at lower elevations. The average difference in adjusted �2H values of feathers to plasma is 32.3‰, while the average difference in adjusted �2H of feathers to RBCs is 10.1‰. [lines 317-321]

However, we did not adjust feather values for the carbon and nitrogen analysis because tissue discrimination factors for carbon and nitrogen are highly sensitive to diet (e.g. the amount of protein in the diet) and discrimination factors have not been established for a nectarivore. In addition, published discrimination factors have primarily been calculated for feathers and whole blood, but not RBCs. Instead, similar to the approach of Podlesak et al. 2005 we examined only general changes in diet by considered differences in �13C and �15N values between feathers and RBCs greater than 2‰ to be indicative of a change in diet. This approach allows us to make a general interpretation of whether diets may have changed between time periods. [lines 280-286] We have also acknowledged in the discussion that tissue discrimination factors are needed for our study species or nectivores in general to make this analysis more robust. [lines 456-458]

Line 298-305: Not that I’m recommending this for this paper, but one alternative method you could consider for future exploration of use of different elevations is using VHF tags and a motus type network (widely used in eastern Canada/US). They are generally quite light weight and are a good alternative to GPS tags. Just a thought!

Response: Good suggestion for future studies

Line 332: Could these flight patterns also be due to differences in foraging strategies?

Response: Yes, differences in flight patterns could be a result of differences in foraging strategies. [lines 433-435]

Line 343-345: You didn’t look at this in plasma? How come? (possible I missed this explanation in the methods).

Response: In the methods we indicate that only RBCs, not plasma was run for carbon and nitrogen analyses. We have added text in the methods to clarify that the volume of blood collected did not permit the analysis of plasma for both hydrogen and carbon/nitrogen analyses. [lines 215-222]

Line 368: typo. “different” not “differnt”

Response: We have fixed the typo [line 485]

Decision Letter 1

David P Gillikin

23 Jun 2020

Stable isotope analysis of multiple tissues from Hawaiian honeycreepers indicates elevational movement

PONE-D-19-34295R1

Dear Dr. Paxton,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Congratulations!

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

David P. Gillikin, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: (No Response)

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have fully addressed my comments and the manuscript is a worthy contribution to the field.

Reviewer #2: The authors have adequately addressed all comments included in the previous review process. The manuscript is well written, easy to follow and statistical analyses have been conducted in a sound manner. Re-running analyses after receiving a review is never an easy task, and the authors have made adequate efforts to address these comments and amended their manuscript appropriately.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Cameron J. Nordell

Reviewer #2: Yes: Rolanda J Steenweg

Acceptance letter

David P Gillikin

30 Jun 2020

PONE-D-19-34295R1

Stable isotope analysis of multiple tissues from Hawaiian honeycreepers indicates elevational movement

Dear Dr. Paxton:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr David P. Gillikin

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: Comments.docx

    Data Availability Statement

    All data is available at a USGS data repository called ScienceBase-Catalog with the following citation and url: Paxton KL, Kelly JF, Pletchet SM, Paxton EH. 2020. Hawaii Volcanoes National Park stable isotope values from Hawaii forest birds 2012. U.S. Geological Survey data release: https://doi.org/10.5066/P98I4EP7.


    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES