Jason C Leppi1,2, Daniel J Rinella3, Mark S Wipfli4, Matthew S Whitman5. 1. Alaska Cooperative Fish and Wildlife Research Unit, College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, Fairbanks, Alaska, United States of America. 2. Research Department, The Wilderness Society, Anchorage, Alaska, United States of America. 3. Anchorage Fish and Wildlife Conservation Office, U.S. Fish and Wildlife Service, Anchorage, Alaska, United States of America. 4. U.S. Geological Survey, Alaska Cooperative Fish and Wildlife Research Unit, Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, Alaska, United States of America. 5. Arctic District Office, Bureau of Land Management, Fairbanks, Alaska, United States of America.
Abstract
Understanding the ecological niche of some fishes is complicated by their frequent use of a broad range of food resources and habitats across space and time. Little is known about Broad Whitefish (Coregonus nasus) ecological niches in Arctic landscapes even though they are an important subsistence species for Alaska's Indigenous communities. We investigated the foraging ecology and habitat use of Broad Whitefish via stable isotope analyses of muscle and liver tissue and otoliths from mature fish migrating in the Colville River within Arctic Alaska. The range of δ13C (-31.8- -21.9‰) and δ15N (6.6-13.1‰) across tissue types and among individuals overlapped with isotope values previously observed in Arctic lakes and rivers, estuaries, and nearshore marine habitat. The large range of δ18O (4.5-10.9‰) and δD (-237.6- -158.9‰) suggests fish utilized a broad spectrum of habitats across elevational and latitudinal gradients. Cluster analysis of muscle δ13C', δ15N, δ18O, and δD indicated that Broad Whitefish occupied four different foraging niches that relied on marine and land-based (i.e., freshwater and terrestrial) food sources to varying degrees. Most individuals had isotopic signatures representative of coastal freshwater habitat (Group 3; 25%) or coastal lagoon and delta habitat (Group 1; 57%), while individuals that mainly utilized inland freshwater (Group 4; 4%) and nearshore marine habitats (Group 2; 14%) represented smaller proportions. Otolith microchemistry confirmed that individuals with more enriched muscle tissue δ13C', δD, and δ18O tended to use marine habitats, while individuals that mainly used freshwater habitats had values that were less enriched. The isotopic niches identified here represent important foraging habitats utilized by Broad Whitefish. To preserve access to these diverse habitats it will be important to limit barriers along nearshore areas and reduce impacts like roads and climate change on natural flow regimes. Maintaining these diverse connected habitats will facilitate long-term population stability, buffering populations from future environmental and anthropogenic perturbations.
Understanding the ecological niche of some fishes is complicated by their frequent use of a broad range of food resources and habitats across space and time. Little is known about Broad Whitefish (Coregonus nasus) ecological niches in Arctic landscapes even though they are an important subsistence species for Alaska's Indigenous communities. We investigated the foraging ecology and habitat use of Broad Whitefish via stable isotope analyses of muscle and liver tissue and otoliths from mature fish migrating in the Colville River within Arctic Alaska. The range of δ13C (-31.8- -21.9‰) and δ15N (6.6-13.1‰) across tissue types and among individuals overlapped with isotope values previously observed in Arctic lakes and rivers, estuaries, and nearshore marine habitat. The large range of δ18O (4.5-10.9‰) and δD (-237.6- -158.9‰) suggests fish utilized a broad spectrum of habitats across elevational and latitudinal gradients. Cluster analysis of muscle δ13C', δ15N, δ18O, and δD indicated that Broad Whitefish occupied four different foraging niches that relied on marine and land-based (i.e., freshwater and terrestrial) food sources to varying degrees. Most individuals had isotopic signatures representative of coastal freshwater habitat (Group 3; 25%) or coastal lagoon and delta habitat (Group 1; 57%), while individuals that mainly utilized inland freshwater (Group 4; 4%) and nearshore marine habitats (Group 2; 14%) represented smaller proportions. Otolith microchemistry confirmed that individuals with more enriched muscle tissue δ13C', δD, and δ18O tended to use marine habitats, while individuals that mainly used freshwater habitats had values that were less enriched. The isotopic niches identified here represent important foraging habitats utilized by Broad Whitefish. To preserve access to these diverse habitats it will be important to limit barriers along nearshore areas and reduce impacts like roads and climate change on natural flow regimes. Maintaining these diverse connected habitats will facilitate long-term population stability, buffering populations from future environmental and anthropogenic perturbations.
The ecological niche conceptualizes the physical environment and food resources used by a species [1]. First described by Grinnell (1917) [2], the “niche habitat” concept proposed that environmental conditions across geographic space limit, or at least influence, the habitat utilized by species. Elton’s “niche” concept further explored this idea but focused on resources consumed and the status of a species within a community, including trophic relationships between prey and predators [3]. Building from previous definitions, Hutchinson (1957) [4] described the “fundamental niche” as a set of points in multivariate space whose axes represent both physical and biological variables required by a species. Within the fundamental niche concept, the first axis represents the bioclimate variables or the habitat stage used by a species and the second axis represents the prey resources that the species consumes [4]. Inside the fundamental niche is the “realized niche,” which is constrained by predation and competition.Diverse foraging behaviors and anadromy help fishes maximize foraging efficiency by enabling them to exploit a suite of seasonally available habitats and food supplies [5, 6]. The evolutionary basis for anadromy in high-latitude fishes is linked to generally lower freshwater productivity compared to marine environments [7, 8]. In addition, extreme seasonal variation in climate and changing hydrologic conditions create a shifting and heterogeneous mosaic of food-resources and suitable habitats [9] that can be exploited by mobile generalists typical of Arctic and boreal fishes [10-13]. The benefits of diverse foraging behavior within Arctic fishes are also influenced by ontogenetic changes in diet that favor migration between habitats to maximize prey intake and minimize energetic costs [14-16]. Collectively, these factors complicate the task of characterizing the ecological niches of Arctic fishes.Many animals inhabit ecosystems that are difficult to monitor and frequently move in search of food (e.g., fishes), which makes it difficult to quantify niche space via conventional techniques. Such techniques require extensive sampling to accurately measure diet composition yet generally lack temporal integration and fail to account for variation in assimilation rates [17, 18]. Alternatively, stable isotope analysis offers an approach for characterizing ecological niches that can time-integrate multiple dimensions of information on both resources and habitat [19-21]. Stable isotopes change in systematic ways within and across ecosystems [22, 23] and are incorporated into animals’ tissue through food and environmental water. Stable isotope ecologists can gain new insights into what a species consumes and where it lives through the development of the “isotopic niche” [19], which uses multiple stable isotope ratios within tissues to characterize a species’ niche space and the location of individuals within that space [17, 19, 24, 25]. Stable isotope analyses of carbon (δ13C) and nitrogen (δ15N) from tissues with different turnover rates (e.g., muscle, liver) can be used to understand diet and trophic position over different time spans [26-28]. Oxygen (δ18O) and deuterium (δD) isotope ratios in animal tissues change in predictable ways across landscapes and, when used in combination with modeled isoscapes [29], can offer additional insights into habitat use [18, 30].Otolith microchemistry is another tool to help understand ecological niches of highly mobile fish species [31-37]. Otoliths, paired inner ear stones used for hearing and balance in all teleost fishes, are laid as concentric layers of metabolically inert biogenic minerals, primarily calcium carbonate. Elements are permanently incorporated into their organic matrix, and compositional changes across the layers reflect changes across an individual’s life [38]. Strontium (Sr), a naturally occurring element derived from geologic material, has four stable isotopes (88Sr, 87Sr, 86Sr, 84Sr), in which only 87Sr is radiogenic. The ratio of 87Sr to 86Sr (87Sr/86Sr) reflects Sr released into fresh water sources and is driven by differences in lithology, age, chemical composition [39-41], and weathering rates of surficial geology [42-44]. For diadromous fishes, the relative differences in 87Sr/86Sr between freshwater and isotopically uniform marine values help provide detailed information on the timing and duration of estuarine and marine habitat use [45, 46].Arctic Alaska is undergoing major landscape and ecosystem transformations from climate change [47-51] and oil and gas development [52-54]. Arctic surface air temperatures are warming at more than twice the rate of lower latitudes, which is exacerbated by Arctic amplification—the feedback between air temperature and surface albedo in polar regions [55]. The accelerated impacts of climate change at high latitudes [56, 57] are a major threat to Arctic freshwater ecosystems [58], altering streamflow patterns [59-62], warming [63, 64] and drying [65] aquatic habitats, causing eutrophication [66] and browning of lakes [67, 68], and allowing for northward range expansion of eurythermic species [69]. Warmer air and fewer cold days have led to numerous changes in the Arctic cryosphere [70], including degraded permafrost [71] and increased active layer depth [72], ground subsidence and alterations in the patterned ground features [54], and increasing retrogressive thaw slump activity [73, 74]. These changes in permafrost and seasonally frozen ground have resulted in increased riverine nutrient [75] and sediment loads [76, 77] in freshwater ecosystems.Broad Whitefish (Coregonus nasus) is a primary subsistence resource for Indigenous peoples in Alaska. Referred to as Aanaakliq in the Iñupiaq language, Broad Whitefish are valued due to their relatively large size (up to 4.5 kg) and abundance during migrations, and account for about half the total mass of fishes harvested across all Beaufort Sea communities [78, 79]. However, information on Broad Whitefish habitat use in Arctic landscapes is limited. Previous research supports the theory of a highly mobile species that utilizes a variety of aquatic habitats [80, 81]. To rapidly build energy reserves during the brief open water period, it is likely that Broad Whitefish move across the landscape and use a variety of habitats (e.g., lakes, rivers, streams, estuaries, lagoons, and nearshore marine areas) [80, 81] while feeding on a diversity of benthic and pelagic prey across a range of trophic levels [12]. Connectivity between a variety of habitats is, therefore, especially important for Broad Whitefish. Similar to other Arctic fishes, habitat use across time and space results in a variety of life histories [81] with varying amounts of time spent in freshwater, estuarine and marine habitats [80] to maximize growth, survival, and reproduction. As such, Broad Whitefish can be considered a model species, which can help us understand habitat use of other similar Arctic fish species (e.g., Humpback Whitefish Coregonus pidschian).Broad Whitefish populations use the Colville River watershed for foraging, rearing [82, 83] and spawning [82]. With headwaters in the rugged Brooks Range, the Colville River is one of the few rivers in the region that contains abundant gravel substrate and deep channels, which are both likely essential for egg survival [84]. Due in part to its watershed size, the Colville River also has the largest delta on the Alaskan Beaufort Sea coast, which provides abundant rearing habitat for larval and juvenile fishes [80, 83]. Broad Whitefish can live for 30+ years and return to the Colville River ecosystem regularly to reproduce [85], likely migrating from a variety of productive foraging areas in rivers across the Beaufort Coastal Plain. Thus, by sampling the Colville River’s spawning run, we were able to infer patterns of foraging behavior and habitat use for Broad Whitefish at the regional scale.Food resources are dispersed across space and time within high-latitude aquatic ecosystems, which should favor fishes with generalist foraging strategies and the ability to exploit a variety of habitat types [11, 12]. Extreme seasonal variation in climate and changing hydrologic conditions, across a spectrum of freshwater to marine habitats, likely creates a variety of seasonally productive habitats and a diversity of ecological niches for Broad Whitefish and other Arctic fishes. We investigated the ecological niches utilized by Broad Whitefish—a highly mobile, generalist fish species—in the Alaska Arctic. Our specific objectives were to (1) explore how variation in δ13C and δ15N in Broad Whitefish muscle relates to Arctic freshwater and marine foraging niches (2) investigate whether diet changes across the summer by comparing tissues with different isotopic turnover rates, (3) determine how variation in muscle δ18O and δD relates to Arctic freshwater and marine niches (4) characterize isotopic niches using cluster analysis of stable isotope ratios (δ13C, δ15N, δ18O, and δD) from muscle tissue and investigate the relationship between the resulting isotopic cluster groups and potential niches utilized, and (5) determine if stable isotope values from muscle tissue are predictive of life history strategy by comparing to Sr isotopes in otoliths. Our research revealed new insights into Broad Whitefish isotopic niches and provided new information on important habitat and food resource use by Broad Whitefish within the Beaufort Sea region. This information expands our understanding of the mosaic of feeding habitats used and will better inform management and conservation decisions to protect this vital subsistence resource.
Materials and methods
Study area
The central Beaufort Sea region study area (Fig 1) contains a diversity of foraging habitats for Arctic fishes. Situated between the Ikpikpuk and Canning rivers, the coastline is a spectrum of deep bays and inlets, tapped lake basins (lake basins that are breached by the sea due to erosion), lagoons with barrier islands, and exposed bluffs [86]. River deltas of varying size are frequent along the coast [87]. Thermokarst and riverine lakes that vary in size, depth, and connectivity [87, 88] account for 30% of the region’s surface area [89]. Stream habitats vary by watershed and geomorphic setting [90, 91], generally resulting in colluvial channels in foothill and mountainous headwaters, beaded headwater streams in low-gradient coastal plains, and meandering alluvial streams and rivers lower in watersheds [88].
Fig 1
Study area.
The central Beaufort Sea region in Arctic Alaska, situated between the Ikpikpuk River and the Canning River, contains a diversity of aquatic habitat. The large Colville River, AK, USA (ca. watershed area 60,000 km2), located in the middle of the central Beaufort Sea coast, contains minor tributaries that drain from the Brooks Range (thin grey lines) and main tributaries (thick dark grey lines) that flow toward a large delta on the edge of the Beaufort Sea, near the community of Nuiqsut, AK. Fish were collected at three sites (black triangles) within the Colville River (site 1 = Itkillik, site 2 = Puviksuk, site 3 = Umiat). Data sources: USGS National Map Viewer (http://viewer.nationalmap.gov/viewer/), Natural Earth (http://www.naturalearthdata.com/), National Hydrography Dataset (https://www.usgs.gov/national-hydrography/national-hydrography-dataset).
Study area.
The central Beaufort Sea region in Arctic Alaska, situated between the Ikpikpuk River and the Canning River, contains a diversity of aquatic habitat. The large Colville River, AK, USA (ca. watershed area 60,000 km2), located in the middle of the central Beaufort Sea coast, contains minor tributaries that drain from the Brooks Range (thin grey lines) and main tributaries (thick dark grey lines) that flow toward a large delta on the edge of the Beaufort Sea, near the community of Nuiqsut, AK. Fish were collected at three sites (black triangles) within the Colville River (site 1 = Itkillik, site 2 = Puviksuk, site 3 = Umiat). Data sources: USGS National Map Viewer (http://viewer.nationalmap.gov/viewer/), Natural Earth (http://www.naturalearthdata.com/), National Hydrography Dataset (https://www.usgs.gov/national-hydrography/national-hydrography-dataset).The region, within the Arctic tundra biome, is characterized by permafrost, extreme climate, low-growing plants, and large variations in day length. The region’s stark seasonality can be divided into a long cold season and a short warm season, but the former controls many of the physical and biological processes. Cold season air temperatures are consistently well below freezing, creating a landscape dominated by snow and ice for about eight months [92]. The warm season is brief, but with 24 hours of daylight and moderate air temperatures [92], the area becomes productive foraging and rearing habitat for many resident and migratory fishes, mammals, and birds. Annual precipitation is generally low, with more falling in the foothills than along the coast (30 and 20 cm, respectively) and about half falling as snow [92].
Fish sampling
We collected otoliths and tissue from adult Broad Whitefish migrating up the Colville River during 2015. The Colville, the largest river in Arctic Alaska, flows about 560 km northward from its headwaters in the partially glaciated Brooks Range to a large delta on the edge of the central Beaufort Sea coast, near the Alaska Native village of Nuiqsut (Fig 1). We set gill nets ca. 30 m in length, composed of braided nylon and monofilament with 10-cm and 12-cm stretched mesh, to target adult fish large enough to spawn (> 35 cm) [93]. We positioned nets at gravel point bars, along eddy lines, and perpendicular to flow in low-gradient reaches at three separate sites (Sites 1–3; Fig 1). We sampled at Puviksuk on July 23–27, at Umiat on August 21–26, and at Itkillik on October 10–11. We euthanized captured Broad Whitefish with a single sharp blow to the cranium and recorded fork length (n = 98, all of which were adults ≥ 42 cm; [84], total weight, gonad weight, and sex (44 males, 47 females, 7 undetermined; S1 Table). We also collected liver and epaxial muscle samples with sterile 5-mm biopsy punches (preserved with clay desiccant beads) from all individuals, except in cases where fish organs were consumed by birds while caught in gillnets (n = 5). Liver and muscle tissue likely represent the integration of consumed food resources for ca. 37 and 88 days prior to capture [26], respectively, providing records of fish foraging niches for differing periods during the growing season. Adult Broad Whitefish are slow-growing fish and it is likely that integration of isotopes into tissues is primarily through anabolism, which could mean that integration of food resources is much longer [27]. Sagittal otoliths were collected from each individual using the Guillotine method [94], rinsed in water, and stored in paper envelopes. The planned sample size of 50 individuals per site was lower than anticipated at Umiat (n = 23) and Itkillik (n = 17), as opposed to Puviksuk (n = 57), due to unexpectedly high streamflow at the former and an early freeze-up at the latter that inhibited our ability to capture fish. Research was conducted under Bureau of Land Management NPR-A permit #FF097006 and the Alaska Department of Fish and Game, Fish Resource permit #SF2015-200. All collections were performed using methods in line with guidelines to minimize suffering.
Tissue stable isotope analyses and data analysis
We selected stable isotopes δ13C, δ15N, δ18O, and δD due to their combined ability to discern Broad Whitefish diet, trophic position, and habitat use [22–25, 30, 95, 96]. We analyzed tissues with different turnover rates (e.g., muscle, liver) to understand change in stable isotopes over different time spans [26-28]. Both δ13C and δ15N have remained important stable isotopes for reconstructing foraging ecology patterns due to their exclusive association with diet, limited fractionation, and ability to reflect sources of primary production and trophic position [22, 97].While relatively new to food web studies, tissue δ18O and δD, when used in combination with modeled isoscapes, can offer additional insights into diet and habitat use [18, 30, 95, 97].We analyzed liver and muscle tissue at the University of Alaska Anchorage’s Environment and Natural Resources Institute (ENRI) Stable Isotope Facility. Samples were dried, ground to a fine powder, and weighed to 0.001 g prior to analysis. Liver and muscle samples were analyzed for δ13C and δ15N using a Costech ECS 4010 elemental analyzer (Costech, Valencia CA) in line with a Thermo Finnigan™ Delta V continuous-flow isotope ratio mass spectrometer (Thermo Scientific™, Bremen, Germany). Muscle samples were analyzed for δD and δ18O using a Thermo Finnigan TC/EA in line with a Thermo Finnigan™ Delta Plus™ XP continuous-flow isotope ratio mass spectrometer (Thermo Scientific™, Bremen, Germany). Due to the reduced size of dried liver samples, we were unable to analyze liver tissue for δD and δ18O. Instruments were calibrated against international reference standards from the International Atomic Energy Agency and the United States Geological Survey. Stable isotope compositions were referenced relative to international standards; atmospheric N for nitrogen, Vienna Pee Dee Belemnite (VPDB) for carbon and Vienna standard mean ocean water (VSMOW) for oxygen and deuterium. Stable isotope ratios were expressed in δ notation in units of per mil (‰) relative to international standards where: δX = [(Rsample—Rstandard)/Rstandard]*1000‰, where R is the ratio between the isotopes (i.e., 13C/12C, 15N/14N, 18O/17O, 2H/1H). Long-term records of internal standards yield an analytical precision of 0.11 ‰ for δ15N, 0.12 ‰ for δ13C, 0.2 ‰ for δ18O, and 1.8 ‰ for δD.To account for a subset of values with carbon to nitrogen ratios (C:N) greater than 3.5, we lipid-normalized δ13C samples following an approach outlined in Skinner et al. (2016) [98]. Using their approach, we adjusted δ13C using the Kiljunen et al. (2006) [99] mathematical normalization model (δ13Cˈ(normalized δ13C) = δ13C + D (I + (3.90)/(1 + 278/L)) with difference in carbon isotopic composition between protein and lipid (D) equal to 7.018 and the constant (I) equal to 0.048. We calculated percent lipid (L) using the Post et al. (2007) [100] equation (L = -20.54 + 7.34 × C:N). We statistically analyzed the stable isotope ratios from Broad Whitefish tissue samples through a hierarchal clustering approach to characterize ecological niches [101]. Hierarchal clustering builds a hierarchy of clusters more similar to each other and, in this instance, our approach clustered individuals into groups with similar isotopic ratios, which represented an individual’s habitat and food resources in multivariate space. Assigning clusters is complicated due to the high-dimensional nature of biological data, which makes it difficult to visualize, but overall, clustering can help gain insights [101]. We conducted a hierarchal agglomerative clustering analysis on normalized-rescaled values following methods outlined by Charrad et al. (2014) [102] within R statistical program using the NbClust package, average link method, and Euclidian distance. Next, we generated 30 cluster validity indices available within the NbClust package to assess the optimal number of clusters (groups) and used the majority rule to determine the best number of clusters [102].To determine if an individual’s diet remained stable or changed over the summer period, we visually and quantitatively compared the difference between muscle and liver tissues (i.e., muscle minus liver) for both δ15N and δ13C. We also conducted a statistical correlation analysis in R statistical program using the ggpubr package. To assess the data for normality we used quantile-quantile plots and the Shapiro-Wilk’s test. Then, we conducted a Pearson correlation analysis between muscle and liver δ15N and δ13C to determine the linear correlation between the muscle and liver tissues. Last, we conducted a linear regression analysis for the muscle and liver δ15N and δ13C to determine the slope and statistical significance of the best-fit line.
Otolith microchemistry and life history classification
We measured Sr isotope concentrations (88Sr, 87Sr, 86Sr, 84Sr) across a subset of the otoliths (69 of 98 individuals sampled). In preparation for isotope analysis, we mounted otoliths prepared in the transverse plane on petrographic slides following methods outlines in Leppi 2021 [82]. We used an Analyte G2 Excimer 193-nm Laser Ablation System (LA; Teledyne Photon Machines, Bozeman, USA) with a Helex cell coupled to a Neptune Plus™ multi-collector inductively coupled plasma mass spectrometer (MC-ICP-MS; Thermo Scientific™, Bremen, Germany) for strontium isotope analyses at the University of Alaska Fairbanks, Alaska Stable Isotope Facility following methods outlined in Leppi 2021 [82]. Briefly, we selected samples to prioritize for laser ablation with the goal of analyzing otoliths across a gradient of δ13Cˈ, δD, and δ18O, which was expected to represent time spent in different habitat types (e.g., freshwater, estuarine, marine) over the three months prior to capture [82]. Subsampled otoliths were roughly proportional to the number of samples collected at each field site [82]. Compared to freshwater habitats, 87Sr/86Sr in marine habitats is generally lower, homogenous, and constant due to the long residence time and mixing of oceans [45, 46].We calculated Sr concentrations (Sr mg/kg) by dividing the concentration of Sr in the FEBS-1 standard (i.e., 2055 mg/kg) by the average 88Ca FEBS-1 standard value during ablation and multiplying by otolith 88Ca at individual points across the ablation path. We considered otolith 88Sr below 6.13 voltage V (ca. 850 mg/kg) to be time spent in freshwater, greater than 12.26 V (ca.1700 mg/kg) to be marine habitat use [45, 46], and intermediate values to reflect time spent in estuarine habitat. The 88Sr concentrations systematically increase with water salinity, with lower values found in freshwater compared to marine habitats. For diadromous fishes, these relative differences in Sr isotopes between distinctive freshwater, estuarine, and marine values can be used to indicate the timing and duration of habitat use [45, 46]. If Sr data were highly variable or contained unreliable values due to cracks, otoliths were removed from the dataset (n = 6).We visually compared the 88Sr and 87Sr/86Sr across each otolith core-to-edge chronology and used a supervised classification approach to group otoliths into three life history groups. Life history types included anadromous, semi-anadromous, and nonanadromous. We considered individuals with maximum 88Sr above 12.26 V and 87Sr/86Sr near the global mean oceanic value (GMV = 0.70918 ± 0.00006 2 standard deviations (SD)) anadromous. We classified individuals as semi-anadromous if 87Sr/86Sr at the natal region was near GMV. Semi-anadromous individuals had no detectable age-0 freshwater otolith signature, likely spending limited time in freshwater as larvae and frequently moving between freshwater, estuarine, and marine habitats [82]. Nonanadromous individuals had 88Sr concentrations lower than 12.26 V and 87Sr/86Sr consistently below global marine 87Sr/86Sr, indicating that they did not enter marine habitats.
Results
δ13Cˈ and δ15N in isotope space
Stable isotope ratios measured in Broad Whitefish muscle tissue overlapped with those previously observed from a variety of Arctic plants, invertebrates, and fish species (Fig 2). Previous research has shown that species that inhabited inland lakes and rivers had more depleted δ13C, compared to marine species (See S2 Table). Broad Whitefish normalized muscle values (δ13Cˈ) ranged from -31.8 to -21.9‰ and overlapped with δ13C observed in Arctic lakes and rivers, estuaries, and nearshore marine habitats (Fig 2) [103-105]. The mean δ13Cˈ of -25.8‰ was roughly between values observed in several riverine and estuarine species (Fig 2; S2, S3 Tables). Muscle δ15N was less variable than observed δ13Cˈ (δ15N range = 6–13.1‰; Fig 4) and was generally higher than that of invertebrates and lower than other fishes (Fig 2) [103-105].
Fig 2
Arctic isoscape.
Cross-section of Arctic aquatic ecosystems. Circles with error bars represent the mean and standard deviation of the organism from each type of ecosystem (Dark blue = marine, light blue = estuarine, green = riverine, gold = lacustrine). Error bars on estuarine species and benthic particulate organic matter values represent the standard error. Circles without error bars represent a single sample. For comparison, data from outside the study area is shown: marine samples are from Admiralty Inlet in the Northwest Territories, CA; lagoon samples are from sites along the eastern Beaufort Sea coast, Alaska, USA; riverine samples are from the lower MacKenzie River, Yukon, CA, and Lacustrine samples are from Toolik Lake, Alaska, USA. Additional isotope sources: See S2, S3 Tables.
Fig 4
The scatterplot shows stable isotopes δ18O versus δD along with the associated boxplot for each isotope measured in muscle of Broad Whitefish (Coregonus nasus) from the Colville River, AK, USA.
Boxplots show median values (horizontal black line), interquartile range (IQR) (box with blue outline), the maximum value within 1.5 times the IQR (vertical black line), and outside values are greater than 1.5 times the IQR (black dots).
Arctic isoscape.
Cross-section of Arctic aquatic ecosystems. Circles with error bars represent the mean and standard deviation of the organism from each type of ecosystem (Dark blue = marine, light blue = estuarine, green = riverine, gold = lacustrine). Error bars on estuarine species and benthic particulate organic matter values represent the standard error. Circles without error bars represent a single sample. For comparison, data from outside the study area is shown: marine samples are from Admiralty Inlet in the Northwest Territories, CA; lagoon samples are from sites along the eastern Beaufort Sea coast, Alaska, USA; riverine samples are from the lower MacKenzie River, Yukon, CA, and Lacustrine samples are from Toolik Lake, Alaska, USA. Additional isotope sources: See S2, S3 Tables.
Tissue comparison
The difference between muscle and liver tissues (i.e., muscle minus liver) was generally minor, with most individuals having a disparity of < 2.0‰ for both δ13Cˈ and δ15N. Differences for δ 13Cˈ ranged from -6.75 to 2.29‰ (mean -0.13‰; S.D. = 1.24‰; Fig 3) while differences for δ15N ranged from -1.50 to 3.97‰ (mean 0.29‰; S.D. = 0.81‰; Fig 3). Delta13Cˈand δ15N were significantly correlated (p-value < 0.05, R = 0.85 and 0.82, respectively) and indicated a moderately strong positive relationship between muscle and liver isotope ratios (δ 13Cˈ = p-value < 0.001, β = 0.9, R2 = 0.73; δ15N = p-value < 0.001, β = 0.85, R2 = 0.66). However, the disparity between muscle and liver isotope ratios suggests that the diet of two individuals shifted toward prey items more depleted in δ13C, while that of two others shifted toward items more enriched in δ15N (Fig 3).
Fig 3
Isotope tissue differences.
The difference in δ15N and δ13Cˈ (muscle minus liver) for each Broad Whitefish (Coregonus nasus) sampled in the Colville River, AK, USA. Scatter plot shapes represent the collection site locations (Itkillik = circle, Puviksuk = triangle, Umiat = square) and the color represents the individual fish’s length (blue ≤ 40 cm, purple = 50 cm, red ≥ 60 cm). For both isotope ratios, positive values indicate a shift from foraging food sources from more enriched (e.g., marine gastropod) to a food source with more depleted values (e.g., lacustrine amphipod), while negative values indicate the opposite.
Isotope tissue differences.
The difference in δ15N and δ13Cˈ (muscle minus liver) for each Broad Whitefish (Coregonus nasus) sampled in the Colville River, AK, USA. Scatter plot shapes represent the collection site locations (Itkillik = circle, Puviksuk = triangle, Umiat = square) and the color represents the individual fish’s length (blue ≤ 40 cm, purple = 50 cm, red ≥ 60 cm). For both isotope ratios, positive values indicate a shift from foraging food sources from more enriched (e.g., marine gastropod) to a food source with more depleted values (e.g., lacustrine amphipod), while negative values indicate the opposite.
δ18O and δD
Muscle δ18O ranged from 4.5 to 10.9‰ with a mean of 7.5‰ (S.D. = 1.33‰; Fig 4) and fit within the range of modeled isotopic values for nearshore marine to inland Arctic regions [29]. Muscle δD was much more variable, ranging from -237.6 to -158.9‰ with a mean of -191.0‰ (S.D. = 12.89‰; Fig 4).
The scatterplot shows stable isotopes δ18O versus δD along with the associated boxplot for each isotope measured in muscle of Broad Whitefish (Coregonus nasus) from the Colville River, AK, USA.
Boxplots show median values (horizontal black line), interquartile range (IQR) (box with blue outline), the maximum value within 1.5 times the IQR (vertical black line), and outside values are greater than 1.5 times the IQR (black dots).
Isotopic niche identification
Cluster analysis of muscle δ13Cˈ, δ15N, δ18O, and δD indicated that grouping samples into four levels was best supported by the data (Fig 5A), explained 76.7% of the information on the first two dimensions, and provided good separation of clusters on dimension one (Fig 5B). Fish within cluster group one (n = 55) contained a broad range of δ13Cˈ that were all greater than -27‰, had δ15N between 7 and 10‰, and had δ18O and δD that overlapped with other groups (Fig 6; S4 Table). Individuals within cluster group two (n = 14) contained the most enriched δ13Cˈ, δ18O, and δD relative to the other groups (Fig 6; S4 Table). Cluster group three (n = 24) contained a broad range of δ13Cˈ that were all less than -26.3‰, mean δ18O that was lower than group 2 and higher than group 1, mean δ15N that was similar to group 2, and mean δD were similar to group 1 (Fig 6; S4 Table). Cluster group four (n = 4) were the most depleted in δ13Cˈ, δ18O, and δD but had δ15N similar to group 1 (Fig 6; S4 Table).
Fig 5
Hierarchal clustering.
Cluster dendrogram (A) shows the individual Broad Whitefish (Coregonus nasus) from the Colville River, AK, USA, clusters (coded by color; purple = cluster 1, blue = cluster 2, turquoise = cluster 3, yellow = cluster 4), and height of the dendrogram. Cluster plot (B) shows each cluster (purple circle = cluster 1, blue triangle = cluster 2, turquoise square = cluster 3, yellow plus = cluster 4) overlaid across two principal components.
Fig 6
Isotope values and hierarchal clustering groups.
Scatterplots (A, C, E) show stable isotopes δ18O, δ15N, and δD versus δ13Cˈ along with the associated cluster group (purple = cluster 1, blue = cluster 2, turquoise = cluster 3, yellow = cluster 4) of Broad Whitefish (Coregonus nasus) from the Colville River, AK, USA. Boxplots (B, D, F) show stable isotopes δ18O, δ15N, and δD by cluster group (purple = cluster 1, blue = cluster 2, turquoise = cluster 3, yellow = cluster 4) along with median (horizontal black line), interquartile range (IQR) (box with colored outline), and maximum value within 1.5 times the IQR (vertical colored line).
Hierarchal clustering.
Cluster dendrogram (A) shows the individual Broad Whitefish (Coregonus nasus) from the Colville River, AK, USA, clusters (coded by color; purple = cluster 1, blue = cluster 2, turquoise = cluster 3, yellow = cluster 4), and height of the dendrogram. Cluster plot (B) shows each cluster (purple circle = cluster 1, blue triangle = cluster 2, turquoise square = cluster 3, yellow plus = cluster 4) overlaid across two principal components.
Isotope values and hierarchal clustering groups.
Scatterplots (A, C, E) show stable isotopes δ18O, δ15N, and δD versus δ13Cˈ along with the associated cluster group (purple = cluster 1, blue = cluster 2, turquoise = cluster 3, yellow = cluster 4) of Broad Whitefish (Coregonus nasus) from the Colville River, AK, USA. Boxplots (B, D, F) show stable isotopes δ18O, δ15N, and δD by cluster group (purple = cluster 1, blue = cluster 2, turquoise = cluster 3, yellow = cluster 4) along with median (horizontal black line), interquartile range (IQR) (box with colored outline), and maximum value within 1.5 times the IQR (vertical colored line).
Variation in isotopic values within life history strategy
Stable isotope values (δ13Cˈ, δ15N, δ18O, δD) within otolith-derived life history groups (anadromous, semi-anadromous, and nonanadromous) show differences, but also considerable overlap. Nonanadromous individuals (n = 8) had mean δ13Cˈ, δ18O, and δD that were depleted compared to semi-anadromous (n = 17) and anadromous (n = 36) individuals (Fig 7; S5 Table). Mean δ15N was similar for the three life history groups and significant overlap was present (Fig 7B; S5 Table). Anadromous and semi-anadromous individuals had higher mean δD than nonanadromous individuals, but there was substantial overlap among groups (Fig 7C; S5 Table).
Fig 7
Isotope values and life history group.
Boxplots (A, B, C, D) showing δ13Cˈ, δ15N, δ18O, and δD by Broad Whitefish (Coregonus nasus) life history group (anadromous (black), semi-anadromous (purple), nonanadromous (pink), along with median (horizontal black line), interquartile range (IQR) (box with colored outline), and maximum value within 1.5 times the IQR (vertical colored line).
Isotope values and life history group.
Boxplots (A, B, C, D) showing δ13Cˈ, δ15N, δ18O, and δD by Broad Whitefish (Coregonus nasus) life history group (anadromous (black), semi-anadromous (purple), nonanadromous (pink), along with median (horizontal black line), interquartile range (IQR) (box with colored outline), and maximum value within 1.5 times the IQR (vertical colored line).
Discussion
Our research revealed that Broad Whitefish utilized numerous isotopic niches and suggests that various successful foraging strategies exist (e.g., residency, migration) to track seasonally available Arctic food resources. The use of a spectrum of freshwater to marine habitats suggests a generalist foraging strategy at the population level, but specialization of foraging habitats where individuals tended to remain in their respective isotopic niches at least for the summer period. Otolith microchemistry demonstrated that Broad Whitefish could switch isotopic niches, suggesting that prey profitability may change in certain habitats, which could be driven by environmental changes or behavioral fitness decisions. We found otolith microchemistry to be a reliable method to infer Broad Whitefish life history strategies and, when coupled with stable isotope analysis of tissues, provided integrated information on long-term life history patterns, diet, and habitat occupancy for several months prior to capture. This level of diversity and flexibility suggests that the population is ecologically intact and presumably confers some resilience to localized habitat change and disturbance but, as for any fish population, rapid and large-scale landscape changes pose a risk to the long-term stability of Colville River Broad Whitefish.
Variation in δ13Cˈand δ15N among Broad Whitefish
Broad Whitefish exhibited a large range in δ13Cˈand δ15N within muscle and liver tissue, which suggests fish in this population are consuming food resources across a diversity of habitats and trophic levels. Our data aligns with previous research documenting the importance of freshwater, lagoon, nearshore marine, and marine carbon for anadromous fish food webs [103-105]. Research on Broad Whitefish diet has also revealed that fish are generalist foragers, consuming a variety of benthic and pelagic prey items depending upon age and prey abundance [12, 27]. In Arctic lentic and lotic ecosystems, food availability can be limited across space and time and generalist foraging strategies, in which individuals feed on a variety of prey items, promote improved survival, rapid growth, and resilience to environmental variability [106]. For example, Broad Whitefish in Arctic Alaska have been shown to consume a variety of pelagic and benthic invertebrate prey items within a single lake, which had similar δ13C [12]. Conversely, individuals caught in a lake with connection to a stream network exhibited a larger range in δ13Cˈand δ15N, suggesting that individuals may be accessing a broader range of prey options [12]. Our results show a slightly larger range of values, supporting the concept of a highly migratory generalist foraging strategy. A flexible foraging strategy in which both benthic and pelagic prey items are utilized enables individuals to efficiently shift between prey items and rapidly accumulate necessary energy reserves prior to a long and cold winter period [107]. Differences among individuals suggest that there is a diversity of foraging specializations, but since we did not analyze stomach contents for each individual we can not draw conclusions about an individuals diet. Therefore, we do not know if individuals are consuming isotopically similar prey items or many prey items with different isotopic values that average to a middle δ13Cˈand δ15N [17].
Differences in δ13Cˈand δ15N between tissues
Differences in δ13Cˈ between muscle and liver suggest that most individuals fed on prey with similar δ13C (+/- 2.5‰) over weeks and months, while a few individuals switched to prey sources or locations with different δ13C. Previous research demonstrates differences in isotope turnover rates between liver and muscle tissue in fish [108-110] due to the association with metabolism rather than growth in liver tissue [108]. Hesslein et al. estimated the half-life of δ13C and δ15N to be 101 days in juvenile Broad Whitefish muscle tissue, but due to slow growth in adult fish, it is likely that the turnover rate for muscle tissue could be years [27]. Consequently, the turnover rates remain unknown for Broad Whitefish and our data may reflect the integration of prey resources over longer periods. Interestingly, the two individuals that had larger muscle-liver disparity each had semi-anadromous life histories that may facilitate feeding within habitats with isotopically different δ15N. Combined, these results suggest that multiple generalist-foraging strategies and potentially life histories [82] exist among the population, likely taking advantage of a variety of non-overlapping habitats and variations in the spatial abundance of prey.
Muscle δ18O and δD and habitat use
The observed range of δ18O (4.5–10.9‰; Fig 5) suggests that a spectrum of habitat, from low elevation nearshore and estuary habitat to inland higher elevation lakes and rivers, are being utilized by Broad Whitefish. Broad Whitefish δ18O overlap those of Pink Salmon (Oncorhynchus gorbuscha) caught in the Colville River, confirming that some individuals utilize similar nearshore marine habitat leading up to entering freshwater (S3 Table). However, local processes associated with waterbody (e.g., depth, groundwater flow) and origin of water sources (i.e., precipitation, snowmelt, glacier, spring) as well as evaporative effects influence δ18O, which transfer up the food web, further complicating interpretations [96, 111]. Deuterium isotopes are influenced by both isotopic exchange with water during protein syntheses and metabolic water and therefore are a better trophic tracer of aquatic food webs [96]. The large range in δD found here (-237.6– -158.9‰) suggests that food is consumed across a range of habitats. Our results show that individuals with nonanadromous life history types had more depleted δD compared to anadromous individuals. However, even within individuals that only spent time in freshwater, δD had considerable variation, suggesting that some combination of local environmental water and dietary source effect are likely influencing the variation in values. This is supported by previous research, which documented that water δD had minor influence on chironomid and fish tissue δD [96]. These isotopic fractionation processes make it challenging to assign fine-scale habitat use of Broad Whitefish based on isotopes but are useful in differentiating between certain habitats (e.g., freshwater vs. marine habitats) and aquatic ecosystems that have distinct differences in primary producer energy sources (e.g., clear shallow lakes dominated by algae sources vs. turbid rivers dominated by terrestrial sources).
Broad Whitefish isotopic niches
Our results show the greatest support for four isotopic niches, but variation within cluster groups suggests a more complex interpretation of physical and biological resources utilized by Broad Whitefish. The hierarchal clustering approach partitioned Broad Whitefish into groups with similar muscle isotopic signatures and provided integrated records of aquatic habitat occupied and prey resources consumed. The isotope cluster groups identified here represent generalized ecological niches utilized by Broad Whitefish over the growing season (ca. three months).The vast majority of individuals had isotopic signatures representative of coastal river, stream, and lake habitat (Group 3) or coastal lagoon and delta habitat (Group 1) which, as corroborated by previous research (e.g., [12, 27, 112]), signifies the importance of these two ecological niches. Within these cluster groups, it is likely that individuals with more negative values inhabited river deltas that receive significant terrestrial inputs while those with less negative values use coastal lagoon areas and consume prey items that incorporate more marine sources [104]. Cluster group four contained the most depleted δ13Cˈ and is representative of freshwater food webs where terrestrial (e.g., peat, detritus, soil organic matter) and freshwater carbon (e.g., algae, macrophytes) sources form the base of the food web. Individuals within cluster group four also contained the lowest δD and δ18O, which suggests these fish are using freshwater habitats more inland, and potentially at higher elevations. However, it is also possible that evaporative processes in shallow water bodies are depleting water isotopic values, which then transfer up through the food web [30]. Conversely, individuals within cluster group two had enriched δ13Cˈ, δD, and δ18O relative to the other groups. These values suggest that individuals within this group spent the majority of their time in nearshore marine areas and consumed prey that primarily utilize marine-based carbon [113].We suspect that the within-and among-cluster variation was caused by the influence of aquatic habitat heterogeneity that influences stable isotopes within Arctic food webs. Freshwater habitats are influenced by their position in the landscape (e.g., geographic and elevational), physical properties of the waterbody (e.g., morphometry), and biogeochemical processes within the waterbody, which cumulatively influence the isotopic composition of food webs from primary producers up [22, 95]. For example, if a waterbody is shallow and clear, it is likely that autochthonous pathways (e.g., algae) will provide greater support to the food web base [114] and consequently, δ13C and δD in primary consumers will tend to be more negative compared to sites that depend upon terrestrial peat, or marine-derived carbon inputs [22, 30, 113]. The variation in isotopes suggests that a range of allochthonous and autochthonous carbon from freshwater, terrestrial and marine sources is creating a diversity of food resources with different isotopic values within and between similar waterbody features. For example, the δ13C can reflect the pelagic-benthic primary production continuum in larger lakes, the terrestrial-aquatic continuum in rivers and riverine lakes, or the freshwater-marine continuum. The range of values could also be caused by a variety of ecological niches utilized by fish, with individuals centered in a cluster more dependent on one specific niche or prey item, while individuals near the periphery may migrate between and utilize multiple niches or switch between isotopically different prey items, thereby utilizing a portfolio of resources across the Arctic, as seen in other locations [115, 116].
Life history strategies
Comparing muscle tissue stable isotope ratios within otolith-derived life history strategies revealed high isotopic niche diversity. Otolith microchemistry confirms that individuals with more enriched muscle tissue δ13Cˈ, δD, and δ18O tend to use marine habitats (except for overwintering), while individuals that frequently move between habitats (i.e., freshwater, estuarine, marine) had less enriched values. Both of these patterns are supported by evidence for diverse anadromous and semi-anadromous life history patterns [45, 117]. Numerous individuals with tissue isotopic values reflective of freshwater habitats were revealed by otolith microchemistry to be anadromous or semi-anadromous. These individuals utilized fresh water for months or years prior to capture but had also previously spent significant time in marine habitat as anadromous or semi-anadromous individuals [82]. Therefore, if only tissue samples were used to classify life history strategy, they would have been misclassified. Such abrupt shifts from marine to freshwater habitat use by long-lived anadromous fish has been documented for Coregonids [34, 117, 118]. Conversely, our results show that δ13Cˈ, δD, and δ18O are generally predictive of nonanadromous individuals, with δ13Cˈ and δ18O reflecting the proportion of time spent in freshwater versus estuarine habitats, with individuals that spent their entire lives in fresh water having the most depleted values.
Conservation implications
The isotopic niches identified here represent the important habitats utilized by Broad Whitefish across the Beaufort Sea region. The variation within and among isotopic niches suggests that Broad Whitefish utilize a diversity of habitats within freshwater, estuarine, and marine habitats. For example, an individual may exclusively use freshwater lake habitat or move between river, stream, and lake habitats to forage. Diverse foraging behaviors and life history strategies have evolved to maximize foraging efficiency and adapt to dispersed and a shifting heterogeneous mosaic of food resources in the Arctic [12]. Climate change is rapidly altering the Arctic landscape [50-54], causing eutrophication [66] and browning of lakes and rivers [67, 68], altering food web dynamics and potentially reducing fitness for Broad Whitefish that utilize benthic prey items, which could lead to reduced diversity of foraging strategies, slower growth, or lower survival. Arctic riverscapes contain a myriad of stream and lake networks that are at risk from anthropogenic fragmentation that could create barriers (e.g., perched road culverts, drying of channel segments), hindering movement patterns and reducing Broad Whitefish access to food resources. Arctic oil and gas development infrastructure has caused cumulative impacts to permafrost [53, 54], which can cause stream flow modifications that can affect fish access to important habitats. Arctic development fragments and disrupts aquatic ecosystems [119], which can further introduce stressors to juvenile and adult fishes [52, 119] that include increased sedimentation [120-123], modifications of streamflow [124], obstructions to fish passage [125-127], reduced instream habitat quality [128], and pollution [129].To help buffer populations, it will be necessary for land managers and conservation planners to maintain natural flow regimes, limit barriers along nearshore areas, and preserve aquatic habitat complexity. Preserving connectivity is also important for reducing impacts from infrastructure like roads and from streamflow changes associated with ongoing climate change. Maintaining a diversity of connected niches will facilitate long-term population stability, buffering populations from future environmental and anthropogenic perturbations [130-132].
Summary of Broad Whitefish sampled.
Table displaying population structure, tissues sampled, and sample size for Broad Whitefish (Coregonus nasus) caught at three locations within the Colville River, AK, USA watershed.(DOCX)Click here for additional data file.
Summary of isotope data from Arctic ecosystems used in Fig 2.
Table displaying δ15N and δ13C for various Arctic plants invertebrates, fish, and mammals.(DOCX)Click here for additional data file.
Summary of isotope data for additional fish species sampled.
Summary of muscle tissue δD and δ18O for Pink Salmon (Oncorhynchus gorbuscha) and Northern Pike (Esox lucius) caught in the lower Colville River, AK, USA.(DOCX)Click here for additional data file.
Stable isotope (δ13Cˈ, δ15N, δ18O, δD) mean and range values for cluster groups from Broad Whitefish (Coregonus nasus) caught in the Colville River, AK, USA.
(DOCX)Click here for additional data file.
Stable isotope (δ13Cˈ, δ15N, δ18O, δD) mean and range values for classified life history types of Broad Whitefish (Coregonus nasus) caught in the Colville River, AK, USA.
(DOCX)Click here for additional data file.(XLSX)Click here for additional data file.25 Jan 2022
PONE-D-21-39878
Broad Whitefish (Coregonus nasus ) isotopic niches: stable isotopes reveal diverse foraging strategies and habitat use in Arctic Alaska
PLOS ONE
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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: Thank you for the opportunity to review this interesting work. I found it to be of much potential, yet I have several points of concern that ought to be addressed.This centers mostly around the introductions structure, a lack of species specific information in the discussion and some further details being required. Please note that I am no expert on the species for which reason my comments on the discussion remained very poor. References have not been checked and I do not judge the language as I am not a native English speaker.Abstract:I have no major comments to the abstract except one suggestion: While the findings are presented fairly well, the implications are handled only with one minor half-sentence statement at the end “maintaining these diverse connected habitats will facilitate long term population stability, buffering populations from future environmental and anthropogenic perturbations.”. Perhaps the authors could expand slightly on what this (perhaps by condensing the findings if word limit is an issue).Introduction:- Line 57-67: I haven’t read such a broad yet very appealing and nice beginning of an introduction in a while.- The introduction is currently excessively long and hard to follow as the nature of the study (isotopes) is somewhat minimalized due to the large and overwhelming sections on the species, the Arctic, and oil/gas development.- I would recommend moving the section on the Arctic Alaska prior to the introduction of the broad whitefish and do you really need the excessive introduction on the oil and gas development? I would suggest combining (and streamlining) the section on Alaska and oil/gas development and moving it up. This way, the section on the target species would be followed by what currently starts in line 146: “Broad Whitefish population…”.Methods:- Line 207-215: Perhaps adding coordinates would be a welcomed detail.- Line 215: Was this euthanization approach in line with regional / local guidelines? Please add information on the underlying legislation that permits this procedure as I cant see from the listed Permit that this was included. Adding a sentence if this approach was in lines with said guidelines or laws (if so) should suffice.- How was the sex identified?- Why fork and not total length?- Line 231-268: I actually enjoyed this introduction to stable isotopes.- Line 269-271: Could you perhaps add a reference?- Line 271-287: I concur completely with the argumentation- Line 311-326: Although I worked with isotopes and niche space myself and quite excessively, I see this section very hard to follow and ultimately, to understand. Perhaps the authors could build on the already written text and try to better explain it?- Line 327-329: Question 1: More generally, I wonder why didn’t you perform actual diet analysis?- Line 331-332: Please add a reasoning for that analysis.Results:Overall, the presentation of the results is very orderly and condensed.- Generally, I am concerned about the origin on these species’ data. Although they are listed in Table S2, its questionable how the data was made comparable. Perhaps I overlooked it previously, but comparability among sites / samples from different period can be difficult.Discussion:A general comment: In order to review the discussion I would need a relatively more profound knowledge on the ecology of the target species – which I don’t have. Hence, I am not able to look in depth into behavioural or conservation implications. Yet, this might be something the authors would want to provide the reader with.- Line 472-474: I would suggest putting more emphasize on the differences between dN/dC and all analysed istopes in conjunction into this first section. This high resolution obtained and the identified differences are crucial and a neat find as well. Even if just briefly and later on discussed in detail- Line 506-514: One crucial point that has been neglected is the physiological difference between those tissues and the associated bioaccumulation factors of them.- Line 599: Is there any actual measure that could be undertaken aside from conserving the current situation?Figure 1: This is a highly interesting figure. I have some problems with the direct comparability of species like Arctic Char and Northern Pike due to the differences in ecosystems, but this figure does an incredibly good job at displaying the huge niche of whitefish.Figure 2: no commentFigure 3: no commentFigure 4: I would suggest not using yellow as it is very hard to see.Figure 5: I would suggest not using yellow as it is very hard to see.Figure 6: no commentReviewer #2: General comments:This study examined trophic and life history diversity in a population of broad whitefish inhabiting the Colville River drainage basin in northern Alaska. Approximately 100 adult fish were sampled from the mainstem river and analyzed for C, N, O and H stable isotope compositions in muscle and liver, and for Sr isotopic composition in otoliths. The data were used to interpret diversity in habitat use and trophic ecology within the population. The manuscript is suitable subject matter for PLoS One.The description of the study is straightforward, and the manuscript is generally easy to read. However, the writing is sometimes too detailed or repetitive and the manuscript could be condensed considerably. I also had some difficulty understanding the data analysis methods, and consequently, with interpreting results. Details are outlined below. Though both the isotopic clustering and otolith chemistry categorization point to three or four life history groupings, they do not appear to correspond strongly. As a result, the interpretation descends into considerable arm-waving that needs to be condensed.Provided these problems can be dealt with, I think there is sufficient material here for an interesting story to be told. I recommend that the manuscript be rejected in its current form but a re-analyzed and revised version could be reconsidered.Specific comments and suggestions for revision:Lines 91-92. Should read “….isotope ratios in animal tissues change in predictable ways across landscapes [29], and when used in combination….”Lines 101-103. Be more specific here; what does a high 87Sr/86Sr ratio signify? Does “Sr values” mean “Sr ratios” in this context (line 103).Lines 112-115. Are you suggesting that a short growing season promotes high diversity in habitat and resource use?Lines 122-145. The information on climate and developmental stressors on the landscape can be condensed into a single paragraph.Line 153. When you say “rivers across the Beaufort Coastal Plain” are you referring to rivers that are tributary to the Colville (i.e., within the Colville drainage basin) or other nearby rivers that drain directly into the Beaufort Sea?Line 207. Should read “adult Broad Whitefish”Line 218. From where on the body was the muscle biopsy removed?Lines 220-222. Not sure what ‘integration’ implies here exactly. Because these are large, mature and slow-growing fish, I suspect the isotopic change for these tissues is quite slow. Presumably ‘integration’ is primarily through anabolism (rather than tissue replacement) and it seems doubtful that these fish would increase in mass by any more than 20-30% per year.Lines 234-235. Delete “…and organic carbon from plant detritus and soil”. Organic carbon is part of DOC, not DICLine 235. Delete “(fractionation)”. Uptake of carbon dioxide by plants is not fractionation, though fractionation does occur during uptake.Lines 249-254. These sentences are confusing. The explanation as to why N isotope ratios of DIN may differ between marine and freshwater ecosystems is not clear.Line 255. Delete “level”Lines 231-287. This whole section is too detailed for the Methods. Some of it can go in the Introduction, as justification for the isotopic approach, but most of this should be condensed to a single paragraph in the Methods that summarizes how you intend to interpret variation in each of the isotope ratios examined.Lines 297-306. Again, condense, or move to the supplemental information file.Lines 319-321. Not clear how the lipid normalization was carried out. Presumably this was only for the C stable isotope ratios?Lines 328-329. Should read “…between muscle and liver tissues (i.e., muscle minus liver) for both delta15N and delta13C”Lines 329-330. A correlation analysis of what? Be specific.Lines 331-334. Not clear why both correlation analysis and regression analysis are carried out on the same data set.Lines 338-339. Omit “…due to instrument constraints (i.e., time, funding, instrument availability)”. You do not need to justify why not all the otoliths were analyzed.Lines 339-340. At least briefly mention the otolith prep and the instrumentation used. Presumably LA-ICP-MS?Line 350. Should read “If Sr data were highly…” Data is plural.Lines 354-355. Need to define FEB on first usage.Line 357. What does “[v]” mean in this context?Lines 352-366. I found this whole paragraph very difficult to understand, right from the calculation of concentrations through to the categorizations.Lines 380-384, Fig. 2 caption. Because broad whitefish data from this study are being compared with data from other species and studies, the geographic scope of the other data needs to be defined in the caption. Did all the other data come from the same area of northern Alaska? Also, the broad whitefish point should be a mean +/- SD so that its variability is directly comparable to the other points. Using ranges inflates the relative variability.Lines 390-391. This is poorly worded. Presumably you are talking about relationships between delta13C and delta15N within each of the two tissues? Were the relationships positive or negative?Line 401, Fig 3 caption. Suggest indicating that blue is less than or equal to 40 cm and red is greater than or equal to 65 cm. Also, should read “For both isotope ratios, positive values indicate…”Lines 431-435. Table 1 provides the same information as Figure 6. I suggest deleting the table.Lines 460-463. Table 2 provides the same information as Figure 7. I suggest deleting the table.Somewhere in Discussion. Should mention how trophic diversity is measured and how this can influence the interpretation of results. Trophic diversity has both within-individual and among-individual components. In this study, diversity is measured among-individuals but not within-individuals. The among-individual diversity is sometimes interpreted as a measure of individual specialization.Somewhere in Discussion. It should be stated more clearly that delta13C variation can be interpreted in various ways. Delta13C can reflect the pelagic-benthic primary production continuum in larger lakes, and can also reflect the terrestrial-aquatic (or allochthonous-authochthonous) continuum in rivers, or more riverine lakes. Most terrestrial primary production is very 13C depleted, similar to pelagic production. It can also reflect the freshwater-marine continuum, as in the Colville system.Lines 646-670, Acknowledgements. Condense considerably.********** 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: NoReviewer #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.]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 PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.28 Apr 2022View LetterDate: Jan 25 2022 06:28PMTo: "Jason C. Leppi" jcleppi@alaska.edu;jason_leppi@tws.orgFrom: "PLOS ONE" plosone@plos.orgSubject: PLOS ONE Decision: Revision required [PONE-D-21-39878]PONE-D-21-39878Broad Whitefish (Coregonus nasus ) isotopic niches: stable isotopes reveal diverse foraging strategies and habitat use in Arctic AlaskaPLOS ONEDear Dr. Leppi,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.Specifically, Even though both reviewers found the study interesting, they highlighted a number of important flaws, to the point that one of them suggested a rejection. 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The PLOS ONE style templates can be found athttps://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf andhttps://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdfThank you for the feedback. We reviewed the style requirements and have updated the file names, title page, and supporting information material.2. We note that you have referenced (J.C. Leppi unpublished data) which has currently not yet been accepted for publication. Please remove this from your References and amend this to state in the body of your manuscript: (ie “J.C. Leppi unpublished data”) as detailed online in our guide for authorshttp://journals.plos.org/plosone/s/submission-guidelines#loc-reference-styleWe removed the unpublished data citation and added a new citation. See L. 647.3. We note that Figure 1 in your submission contain [map/satellite] images which may be copyrighted. 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Please do not edit.]Thank you for the feedback we have created a new figure that only contains public domain data layers. See revised figure 1.Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. 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: YesReviewer #2: Partly________________________________________2. Has the statistical analysis been performed appropriately and rigorously?Reviewer #1: YesReviewer #2: Yes________________________________________3. 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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: YesReviewer #2: Yes________________________________________5. Review Comments to the AuthorPlease 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: Thank you for the opportunity to review this interesting work. I found it to be of much potential, yet I have several points of concern that ought to be addressed.This centers mostly around the introductions structure, a lack of species specific information in the discussion and some further details being required. Please note that I am no expert on the species for which reason my comments on the discussion remained very poor. References have not been checked and I do not judge the language as I am not a native English speaker.We thank you for the thoughtful and detailed review of our manuscript. Your comments and suggestions helped us to greatly improve our manuscript. Thank you for taking the time to review our manuscript.Sincerely,Jason Leppi, Dan Rinella, Mark Wipfli, and Matthew WhitmanNote: All line numbers referenced in this document refer to the Revised Manuscript with Track Changes documentAbstract:I have no major comments to the abstract except one suggestion: While the findings are presented fairly well, the implications are handled only with one minor half-sentence statement at the end “maintaining these diverse connected habitats will facilitate long term population stability, buffering populations from future environmental and anthropogenic perturbations.”. Perhaps the authors could expand slightly on what this (perhaps by condensing the findings if word limit is an issue).Made change. See L. 53¬¬¬¬¬¬–55.Introduction:- Line 57-67: I haven’t read such a broad yet very appealing and nice beginning of an introduction in a while.Thank you for the positive feedback regarding our introduction. We spent significant time crafting it.- The introduction is currently excessively long and hard to follow as the nature of the study (isotopes) is somewhat minimalized due to the large and overwhelming sections on the species, the Arctic, and oil/gas development.Thank you for the suggestion. We removed the section on Arctic oil and gas development from the introduction. However, we think it is important to keep information on the species (Broad Whitefish) in the introduction because it sets the stage for the research.- I would recommend moving the section on the Arctic Alaska prior to the introduction of the broad whitefish and do you really need the excessive introduction on the oil and gas development? I would suggest combining (and streamlining) the section on Alaska and oil/gas development and moving it up. This way, the section on the target species would be followed by what currently starts in line 146: “Broad Whitefish population…”.Thank you for the suggestion. We removed the section on Arctic oil and gas development from the introduction and moved the paragraph on climate impacts prior to the paragraph that describes Broad Whitefish. See L. 109–121.Methods:- Line 207-215: Perhaps adding coordinates would be a welcomed detail.The location of our sampling occurred at three locations (Puviksuk, Umiat, Itkillik) on the Colville River which are shown in Fig1. We feel as thought the Fig1 maps provide adequate detail for the research.- Line 215: Was this euthanization approach in line with regional / local guidelines? Please add information on the underlying legislation that permits this procedure as I cant see from the listed Permit that this was included. Adding a sentence if this approach was in lines with said guidelines or laws (if so) should suffice.Yes, our methods were in line with Institutional Animal Care and Use Committee Protocol standard euthanization procedures to minimize animal suffering. We added a clarifying sentence. See L. 247–248.- How was the sex identified?Sex for all individuals was determined visually while taking tissue samples for stable isotope analysis. Females had eggs, males had milt, and a small percentage had neither and were classified as unidentified.- Why fork and not total length?Fork length was measured to be more consistent with measurements between individuals.- Line 231-268: I actually enjoyed this introduction to stable isotopes.Thank you, but unfortunately, reviewer #2 requested that we remove this introductory content from the methods section. The vast majority of this content has been removed.- Line 269-271: Could you perhaps add a reference?Added reference. See L. 290.- Line 271-287: I concur completely with the argumentationThank you for your feedback.- Line 311-326: Although I worked with isotopes and niche space myself and quite excessively, I see this section very hard to follow and ultimately, to understand. Perhaps the authors could build on the already written text and try to better explain it?Thank you for the suggestion. We updated and rearranged the text to be clearer. We hope that it is now more clear. See L. 332–354.- Line 327-329: Question 1: More generally, I wonder why didn’t you perform actual diet analysis?Good question. We did not perform a diet analysis because the individuals caught had empty stomachs. We checked their stomach contents and didn’t find any prey items. The vast majority of individuals were prespawners and it is thought that fish stop or reduce feeding while migrating.- Line 331-332: Please add a reasoning for that analysis.Made change. See L. 360–361.Results:Overall, the presentation of the results is very orderly and condensed.Thank you, we also feel that the results section is presented well.- Generally, I am concerned about the origin on these species’ data. Although they are listed in Table S2, its questionable how the data was made comparable. Perhaps I overlooked it previously, but comparability among sites / samples from different period can be difficult.Thank you for the feedback. The goal of the figure is to show a depiction of the variation of � 13C and � 15N across freshwater, estuarine, and marine ecosystems as it relates to our Broad Whitefish samples. Broad Whitefish are highly migratory and likely use vast areas of the Arctic to fulfill their life cycle. The samples that were collected outside the study area are only used to help visualize how Broad Whitefish isotope values relate to other species within Arctic ecosystems. In addition to whitefish samples, we collected samples from Northern Pike and Pink Salmon caught in our nets and invertebrates from several sites in the Colville River watershed. The data and references for species collected is clearly listed in S2 Table.Discussion:A general comment: In order to review the discussion I would need a relatively more profound knowledge on the ecology of the target species – which I don’t have. Hence, I am not able to look in depth into behavioural or conservation implications. Yet, this might be something the authors would want to provide the reader with.Thank you for the feedback. We provide text in the discussion that describes behavioral and conservation implications. See Conservation implications section L. 656–681.- Line 472-474: I would suggest putting more emphasize on the differences between dN/dC and all analysed istopes in conjunction into this first section. This high resolution obtained and the identified differences are crucial and a neat find as well. Even if just briefly and later on discussed in detailThank you for the feedback. We discuss the difference between δ13Cˈand δ15N in the discussion section labeled “Variation in δ13Cˈand δ15N among Broad Whitefish”. See L. 531–552.- Line 506-514: One crucial point that has been neglected is the physiological difference between those tissues and the associated bioaccumulation factors of them.We updated the text to briefly expand upon the physiological differences between liver and muscle tissue. See L. 557–563.- Line 599: Is there any actual measure that could be undertaken aside from conserving the current situation?Good question. Given our limited knowledge of Arctic Broad Whitefish movement and habitat use and the generally pristine nature of the landscape we think that conserving habitat and minimizing impacts is the right level of detail for this section at this point.Figure 1: This is a highly interesting figure. I have some problems with the direct comparability of species like Arctic Char and Northern Pike due to the differences in ecosystems, but this figure does an incredibly good job at displaying the huge niche of whitefish.Thank you. We also feel that Fig 2 (not Fig 1) does a good job at show differences of δ13Cˈand δ15N between ecosystems and across species.Figure 2: no commentFigure 3: no commentFigure 4: I would suggest not using yellow as it is very hard to see.We think that the colors used in the plot are adequate, which are trying to balance visual appeal with functionality.Figure 5: I would suggest not using yellow as it is very hard to see.We think that the colors used in the plot are adequate which are trying to balance visual appeal with functionality.Figure 6: no commentReviewer #2: General comments:This study examined trophic and life history diversity in a population of broad whitefish inhabiting the Colville River drainage basin in northern Alaska. Approximately 100 adult fish were sampled from the mainstem river and analyzed for C, N, O and H stable isotope compositions in muscle and liver, and for Sr isotopic composition in otoliths. The data were used to interpret diversity in habitat use and trophic ecology within the population. The manuscript is suitable subject matter for PLoS One.The description of the study is straightforward, and the manuscript is generally easy to read. However, the writing is sometimes too detailed or repetitive and the manuscript could be condensed considerably. I also had some difficulty understanding the data analysis methods, and consequently, with interpreting results. Details are outlined below. Though both the isotopic clustering and otolith chemistry categorization point to three or four life history groupings, they do not appear to correspond strongly. As a result, the interpretation descends into considerable arm-waving that needs to be condensed.Provided these problems can be dealt with, I think there is sufficient material here for an interesting story to be told. I recommend that the manuscript be rejected in its current form but a re-analyzed and revised version could be reconsidered.We thank you for the thoughtful and detailed review of our manuscript. Your comments and suggestions helped us to greatly improve our manuscript. Thank you for taking the time to review our manuscript.Sincerely,Jason Leppi, Dan Rinella, Mark Wipfli, and Matthew WhitmanNote: All line numbers referenced in this document refer to the Revised Manuscript with Track Changes documentSpecific comments and suggestions for revision:Lines 91-92. Should read “….isotope ratios in animal tissues change in predictable ways across landscapes [29], and when used in combination….”Made change. See L. 93–95.Lines 101-103. Be more specific here; what does a high 87Sr/86Sr ratio signify? Does “Sr values” mean “Sr ratios” in this context (line 103).Made change. See L. 106.Lines 112-115. Are you suggesting that a short growing season promotes high diversity in habitat and resource use?No, we don’t think it has to do with the length of the growing season, but rather the availability, timing, and duration of aquatic habitats. We suspect that surface water phenology influences Broad Whitefish foraging ecology similar to other species that live in ecosystems where the availability of habitat and food resources frequently change. See reference below.Heim KC, McMahon TE, Calle L, Wipfli MS, Falke JA. A general model of temporary aquatic habitat use: water phenology as a life history filter. Fish Fish. 2019;20:802–816. https://doi.org/10.1111/faf.12386Lines 122-145. The information on climate and developmental stressors on the landscape can be condensed into a single paragraph.Made change. Removed paragraph on development stressors from the introduction.Line 153. When you say “rivers across the Beaufort Coastal Plain” are you referring to rivers that are tributary to the Colville (i.e., within the Colville drainage basin) or other nearby rivers that drain directly into the Beaufort Sea?Good question. We don’t know where fish are foraging, but it is likely from a variety of habitats across the Arctic. Broad Whitefish have been observed using a variety of freshwater habitats within the Beaufort Coastal plain as well as estuarine and nearshore habitat along the Beaufort Sea coast. There is evidence that Broad Whitefish migrate from nearby rivers such as Fish Creek or Little Putuligayak River to the Colville to potentially spawn and/or overwinter (Morris 2000;2003), but fish could utilize other areas. There is also documented evidence of Broad Whitefish using nearshore areas to the east of the Colville River during the summer.Morris WA. Seasonal movements of broad whitefish (Coregonus nasus) in the freshwater systems of the Prudhoe Bay oil field. 2000. [Master's thesis, University of Alaska Fairbanks]. ScholarWorks@UA publishing. http://hdl.handle.net/11122/6783Morris WA. Seasonal movements and habitat use of Arctic grayling (Thymallus arcticus), burbot (Lota lota), and broad whitefish (Coregonus nasus) within the Fish Creek drainage of the National Petroleum Reserve-Alaska, 2001–2002; Technical Report No. 03-02. 2003. Alaska Department of Natural Resources, Office of Habitat Management. https://www.adfg.alaska.gov/static/home/library/pdfs/habitat/03_02.pdfGreen DG, Priest JT, Gatt KP, Sutton TM. Beaufort Sea Nearshore Fish Monitoring Study: 2018 Annual Report. Report for Hilcorp Alaska, LLC by the University of Alaska Fairbanks, College of Fisheries and Ocean Sciences, Department of Fisheries, Fairbanks, Alaska.2018. http://www.north-slope.org/assets/images/uploads/2018_Beaufort_Sea_Nearshore_Fish_Monitoring_Annual_Report.pdfLine 207. Should read “adult Broad Whitefish”Made change. See L. 223.Line 218. From where on the body was the muscle biopsy removed?From the epaxial muscle near the dorsal fin. We added clarifying text to the manuscript. See L. 234.Lines 220-222. Not sure what ‘integration’ implies here exactly. Because these are large, mature and slow-growing fish, I suspect the isotopic change for these tissues is quite slow. Presumably ‘integration’ is primarily through anabolism (rather than tissue replacement) and it seems doubtful that these fish would increase in mass by any more than 20-30% per year.Yes, we agree and have incorporated your suggestion into the manuscript. See L.236 and L. 238–241. It is likely that isotopic change of Broad Whitefish muscle is much longer that the stated 88 days, but we really don’t know how long. Vander Zanden et al. 2015 provide a good review on the topic and evidence that the half-life of isotopes in fish muscle tissue is around 88 days. Within the review, Hesslein et al. 1993 provide evidence for Broad Whitefish muscle half-life of 101.9 days.Vander Zanden MJ, Clayton MK, Moody EK, Solomon CT, Weidel BC. Stable isotope turnover and half-life in animal tissues: a literature synthesis. PLOS ONE. 2015;10 (1): e0116182. https://doi.org/10.1371/journal.pone.0116182Hesslein RH, Hallard KA, Ramlal P. Replacement of sulfur, carbon, and nitrogen in tissue of growing broad whitefish (Coregonus nasus) in response to a change in diet traced by delta S-34, delta C-13, and delta N-15. Can J Fish Aquat Sci. 1993; 50:2071-2076. https://doi.org/10.1139/f93-230Lines 234-235. Delete “…and organic carbon from plant detritus and soil”. Organic carbon is part of DOC, not DICDeleted textLine 235. Delete “(fractionation)”. Uptake of carbon dioxide by plants is not fractionation, though fractionation does occur during uptake.Deleted textLines 249-254. These sentences are confusing. The explanation as to why N isotope ratios of DIN may differ between marine and freshwater ecosystems is not clear.Deleted textLine 255. Delete “level”Deleted textLines 231-287. This whole section is too detailed for the Methods. Some of it can go in the Introduction, as justification for the isotopic approach, but most of this should be condensed to a single paragraph in the Methods that summarizes how you intend to interpret variation in each of the isotope ratios examined.Good suggestion. We reduced the method section significantly by removing text. Deleted text, see revised methods section, L. 251–288 and L. 297–308.Lines 297-306. Again, condense, or move to the supplemental information file.OK. We condensed the text by removing the description on internal standards. See L. 319–325.Lines 319-321. Not clear how the lipid normalization was carried out. Presumably this was only for the C stable isotope ratios?Yes, we conducted lipid normalization only for the δ13C values. We revised the text to be more clear. See L. 332–338.Lines 328-329. Should read “…between muscle and liver tissues (i.e., muscle minus liver) for both delta15N and delta13C”Made change. See L. 357.Lines 329-330. A correlation analysis of what? Be specific.This information is within the first paragraph. See L.355–357. We also added clarifying text at L. 360–361.Lines 331-334. Not clear why both correlation analysis and regression analysis are carried out on the same data set.To help determine if an individual's diet remained stable or changed over the summer period, we visually and quantitatively compared the difference between δ13Cˈand δ15N muscle and liver tissues (i.e., muscle minus liver) for both δ13Cˈand δ15N using multiple approaches. See L. 355–363.Lines 338-339. Omit “…due to instrument constraints (i.e., time, funding, instrument availability)”. You do not need to justify why not all the otoliths were analyzed.Made change. Deleted text.Lines 339-340. At least briefly mention the otolith prep and the instrumentation used. Presumably LA-ICP-MS?OK. Made change. See L. 368–373.Line 350. Should read “If Sr data were highly…” Data is plural.Made change. See L. 389.Lines 354-355. Need to define FEB on first usage.Thank you. We updated the reference material name in the text. See L. 382.Line 357. What does “[v]” mean in this context?The units for 88Sr is voltage (V), which are the measurements of the number of 88Sr atoms hitting the instrument detector (faraday cup). Made change. See L. 384.Lines 352-366. I found this whole paragraph very difficult to understand, right from the calculation of concentrations through to the categorizations.Thank you for the feedback. We revised the text to be more clear. See L. 393–409.Lines 380-384, Fig. 2 caption. Because broad whitefish data from this study are being compared with data from other species and studies, the geographic scope of the other data needs to be defined in the caption.Good suggestion. We update Fig 2 caption. See L. 425–432.Did all the other data come from the same area of northern Alaska?No, some information is from northern Alaska, while other information is from the northern Yukon and Northwest Territories. See L. 428–432.Also, the broad whitefish point should be a mean +/- SD so that its variability is directly comparable to the other points. Using ranges inflates the relative variability.Made change. See updated Fig 2.Lines 390-391. This is poorly worded. Presumably you are talking about relationships between delta13C and delta15N within each of the two tissues? Were the relationships positive or negative?Lines 390–393 (438–411 in revised manuscript), within the tissue comparison paragraph describes the correlation and linear relationship between tissue types (muscle vs. liver) for δ13Cˈ and δ15N. The relationship between muscle and liver δ13Cˈ and muscle and liver δ15N were both positive.Line 401, Fig 3 caption. Suggest indicating that blue is less than or equal to 40 cm and red is greater than or equal to 65 cm. Also, should read “For both isotope ratios, positive values indicate…”Made change. See L. 449–450.Lines 431-435. Table 1 provides the same information as Figure 6. I suggest deleting the table.We deleted the table from the manuscript but included it as a table within the supplementary information section.Lines 460-463. Table 2 provides the same information as Figure 7. I suggest deleting the table.We deleted the table from the manuscript but included it as a table within the supplementary information section.Somewhere in Discussion. Should mention how trophic diversity is measured and how this can influence the interpretation of results. Trophic diversity has both within-individual and among-individual components. In this study, diversity is measured among-individuals but not within-individuals. The among-individual diversity is sometimes interpreted as a measure of individual specialization.Thank you for the suggestion. We added clarifying text to the discussion section. See L. 516–517, L. 548–552.Somewhere in Discussion. It should be stated more clearly that delta13C variation can be interpreted in various ways. Delta13C can reflect the pelagic-benthic primary production continuum in larger lakes, and can also reflect the terrestrial-aquatic (or allochthonous-authochthonous) continuum in rivers, or more riverine lakes. Most terrestrial primary production is very 13C depleted, similar to pelagic production. It can also reflect the freshwater-marine continuum, as in the Colville system.Thank you for the clarifying suggestion. We added suggested text to the manuscript. See L. 628–631.Lines 646-670, Acknowledgements. Condense considerably.Made suggested changes. Please see the condensed acknowledgment section. See L. 707–731.________________________________________6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). 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Please contact the publication office if you have any questions.Submitted filename: Response to Reviewers.docxClick here for additional data file.13 Jun 2022Broad Whitefish (Coregonus nasus ) isotopic niches: stable isotopes reveal diverse foraging strategies and habitat use in Arctic AlaskaPONE-D-21-39878R1Dear Dr. Leppi,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.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. 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For more information, please contact onepress@plos.org.Kind regards,Giorgio Mancinelli, Ph.D.Academic EditorPLOS ONEAdditional Editor Comments (optional):I have considered the changes made by the authors to the original version of the manuscript, and my conclusions are that they have considerably increased the quality of the ms, making it acceptable for publication in PLOS ONE.Reviewers' comments:1 Jul 2022PONE-D-21-39878R1Broad Whitefish (Coregonus nasus) isotopic niches: stable isotopes reveal diverse foraging strategies and habitat use in Arctic AlaskaDear Dr. Leppi: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. 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