INTRODUCTION

Climate change affects physical conditions of marine systems, eliciting community responses in which some species may shift their distribution or phenology (Doney et al. 2012, Poloczanska et al. 2013, Sydeman et al. 2015). However, not all species in a community respond in the same manner or magnitude, and asymmetries in species’ responses to climate change can alter predator-prey interactions through changes in size, location, and overlap of an organism’s spatial range (Selden et al. 2018). For species that are central place foragers, these shifts in prey distribution can increase the distance between the predator’s foraging zone and its desired prey, ultimately altering food availability (Durant et al. 2007). Some species adapt to these changes by replacing historically preferred prey with different species or by adjusting their spatial range according to changes in their environment (Grémillet and Boulinier 2009).

Instances of predator-prey mismatch as a response to shifting prey communities have been observed in the Gulf of Maine (GOM; Staudinger et al. 2019), which is warming faster than 99% of the world’s oceans (Pershing et al. 2015). In these prey communities, climate-driven ecosystem changes have resulted in more temperate species and fewer subarctic organisms (Pershing et al. 2021). One such change to the GOM prey community can be seen in distributional shifts of Atlantic butterfish (Peprilus triacanthus; hereafter butterfish), a subtropical to temperate fish that is found in Northwest Atlantic waters ranging from Florida, USA to Nova Scotia, Canada (Adams et al. 2015). Butterfish is vulnerable to distributional shift because it is a highly mobile habitat generalist with broad larval dispersal (Hare et al. 2016) and migrates in response to fluctuating water temperature (Hudson and Peros 2013). Consequentially, this warm-water fish has shown significant northward shift in mean latitude in recent decades (Suca et al. 2021), including range expansion into the GOM (Adams 2022). Butterfish were detected in the GOM as early as 1982 (Adams 2022). However, more recently, they are increasing in diets of seabirds within this region (Kress et al. 2017) and are replacing historically preferred prey of seabirds (Scopel et al. 2019). Despite being captured more frequently, butterfish may prove to be unsuitable prey for seabirds because of its dorsoventrally deep-bodied shape, which makes it difficult for gape-limited seabirds to swallow (Kress et al. 2017). This issue is of particular concern for foraging seabirds in the GOM because, in coming decades, habitat suitability for butterfish is predicted to be high in this region (McHenry et al. 2019).

Here, we explore effects of butterfish in the diet of Common Terns (Sterna hirundo) at a breeding site in the GOM. Common Terns are the most widely distributed tern in the GOM and in North America. These birds were overharvested and displaced from their colonies during the 20th century; today, they are considered a Regional Species of Greatest Conservation Need in the U.S. Northeast region (Terwilliger Consulting 2015). Breeding Common Terns are central place foragers constrained by foraging distance away from their young (with a typical clutch size of 2–3 eggs; Arnold et al. 2020). In the GOM, they capture a variety of prey from foraging areas surrounding their breeding colonies, including small and juvenile fishes (particularly species of herring and hake [Clupea, Alosa, Urophycis, and Merluccius species]) and invertebrates such as insects, euphausiids, and squid (Hall et al. 2000, Arnold et al. 2020). Understanding effects of climate-mediated changes on Common Tern prey is particularly important for the protection of this management-dependent seabird, as prey availability is an essential component underlying seabird reproductive success during the breeding season (Schaffner 1986, Cairns 1988, Suddaby and Ratcliffe 1997). Effects of climate change and overfishing on prey availability, as well as increased butterfish in the diet, are specifically cited as threats to breeding terns in New Hampshire, USA (Carloni 2015).

We examined suitability and effects of butterfish in diets of Common Terns to evaluate current and potential future impacts of increasing butterfish abundance with warming temperatures in the GOM. Our specific objectives were:

1. To evaluate the suitability of butterfish for chick consumption, using handling time and feeding success as measures of prey suitability. We hypothesized that due to their deep-bodied morphology, butterfish would be difficult to handle and ultimately less likely to be successfully swallowed compared to other prey items, rendering them unsuitable prey for tern chicks.
2. To examine effects of butterfish on tern chick growth. We expected that increased rates of butterfish provisioned to tern chicks by their parents would negatively affect chick growth.
3. To explore variability in butterfish provisioning among breeding pairs of adults. We examined diet composition across nests and hypothesized that variability in the proportion of butterfish provisioned may be an indicator of an adult’s capacity to respond adaptively to the increasing presence of butterfish in the GOM prey community.

METHODS

Study area

We collected data from Common Terns at a mixed-species tern nesting colony on Seavey Island, New Hampshire, USA (42°58’ N, 70°37’ W), located approximately 10 km offshore in the southwestern GOM. The island serves as the site of New Hampshire’s threatened and endangered tern restoration efforts. Research and management have been conducted on the island every summer (May–August) since 1997. Data presented here were collected on Seavey Island in June and July 2017, June to August 2018, and July and August 2019. During these years, Seavey Island annually supported 2000–3000 pairs of Common Terns, 60–90 pairs of Roseate Terns (S. dougallii), and 1–2 pairs of Arctic Terns (S. paradisaea).

Common Tern chick diet

Feeding watches were made either in-person with binoculars from observation blinds or remotely using video footage recorded from an AXIS P5635-E Mk II PTZ Network Camera. Observations occurred between 5:30 and 21:30. Chicks monitored during feeding watches were banded and regularly marked on the breast with colored ink, allowing us to identify individuals and their corresponding nest identity (ID). We could not consistently identify individual adults during feeding watches, so our diet data were collected at the nest level, representing each pair of adults. The majority of nests were monitored for ≥ 5 h over the course of the breeding season. For nest-level analyses, we removed seven nests (of 53 total) that were observed for < 5 h, finding that the low watch times resulted in feeding rate outliers.

For each chick feeding event, we visually identified prey to the lowest taxonomic resolution possible. Prey items recorded were grouped into five categories: (1) butterfish, (2) herring (comprising Clupea harengus and Alosa spp.), (3) hake (comprising Urophycis chuss, U. tennuis, and Merluccius bilinearis), (4) other fish (in order of relative proportion: Ammodytes spp., Fundulus heteroclitus, Tautogolabrus adspersus, Enchelyopus cimbrius, other gadid species [likely Melanogrammus aeglefinus, Pollachius virens, and Gadus morhua], Cyclopterus lumpus, Menidia menidia, Catostomus commersonii, and Syngnathus fuscus), and (5) invertebrates (primarily euphausiids, insects, and squid). Thirty-five percent of prey items were unidentifiable and were excluded from analyses. Prey size was quantified by visually estimating the length of prey relative to that of the adult tern’s bill, using units of “bill length.”

To assess the suitability of butterfish as prey for Common Tern chicks, we recorded handling time and feeding success. Handling time was defined as number of seconds that a chick held a prey item in its bill before it was swallowed, discarded, or stolen. Handling times were included in analyses regardless of whether prey were swallowed. Feeding success was defined as the proportion of each prey category that was successfully swallowed by chicks; discarded or stolen prey were considered unsuccessful feedings. To test for differences in both handling time and feeding success across prey categories, we used analysis of variance with post-hoc Tukey honestly significant difference (HSD) tests. We used linear regression to assess the relationship between prey size and handling time within each prey category. Statistical analyses were conducted in R (version 4.0.2; R Core Team 2021) and JMP (JMP Pro 15.0.0).

Common Tern chick growth rates

We weighed individual chicks at least twice between 3 and 15 days of age, the period over which chick weight increases linearly and a linear growth rate could be calculated (Arnold et al. 2016). For nests with more than one chick, we used the growth rate of the fastest growing sibling in analyses, as one chick typically received most feedings, and that chick’s growth was therefore more representative of the composition of the diet. Furthermore, in 60% of nests with more than one chick, one sibling tended to die quickly (within one week of hatching in our study population), limiting the potential to collect diet and growth data for multiple chicks in one nest. For growth-diet comparisons, we used feeding data when chicks were between 0 and 15 days old, as these feedings were most relevant to the period of linear chick growth. To assess effects of butterfish in diets on chick growth while accounting for overall feeding rates, we conducted a least-squares regression of chick growth rate, including the effects of proportion of butterfish in the diet, overall feeding rate, and the interaction between those variables. Although we also measured juvenile survival (to 15 days of age) at our study site, this metric was highly influenced by non-dietary factors, including severe weather and predation events. We therefore chose to focus our investigations on chick growth rate as the response metric most immediately influenced by shifts in diet.

Variability in butterfish provisioning

We examined variability in number of butterfish in diets across years and across nests within each year of study. For these analyses, we grouped prey items into two categories: butterfish and all other prey. We compared the number of butterfish relative to all other prey provisioned across the three years of study using a χ² test. To examine variability in butterfish provisioning by different nesting pairs of adults, we compared number of butterfish and other prey by nest ID within each of the three years using a two-tailed Monte Carlo estimate of Fisher’s exact test (Mehta and Patel 2013).

RESULTS

We conducted feeding watches of individual Common Tern nests in 2017 (N = 11, watched on average [± standard deviation, SD] for 18 ± 13 h), 2018 (N = 13, 20 ± 16 h), and 2019 (N = 22, 43 ± 24 h). We successfully identified 110 prey items in 2017, 212 prey items in 2018, and 656 prey items in 2019. Over the three years combined, we observed 92 butterfish, 277 herring, 477 hake, 58 other fish, and 74 invertebrates. Overall, butterfish comprised 17% of the diet in 2017, 19% in 2018, and 5% in 2019.

Suitability of butterfish for chick consumption

Handling time varied significantly among prey categories (F_{4, 499} = 63.9, P < 0.001; Fig. 1). A post-hoc Tukey HSD test indicated that butterfish took significantly longer for chicks to handle (mean ± SD: 328 ± 424 s) than herring (13 ± 35 s), hake (2 ± 6 s), other fish (28 ± 49 s), and invertebrates (3 ± 11 s), with no significant differences among the four latter categories. Feeding success also varied significantly across prey categories (F_{4, 925} = 195.0; P < 0.001; Fig. 1). A post-hoc Tukey HSD test revealed that butterfish were significantly less likely to be swallowed (21 ± 41% swallowed) than herring (95 ± 23%), hake (98 ± 13%), other fish (79 ± 41%), or invertebrates (86 ± 35% ), again with no significant differences among the four latter categories. Butterfish was the only prey category that did not exhibit a significant relationship between prey size and handling time (butterfish: r² = 0.05, P = 0.10; herring: r² = 0.13, P < 0.001; hake: r² = 0.03, P < 0.01; other fish: r² = 0.37, P < 0.01; invertebrates: r² = 0.12, P = 0.02).

Effect of butterfish on chick growth rate

Growth rate of individual Common Tern chicks was negatively associated with proportion of butterfish provisioned when analyzed using least-squares regression (â = −11.8, standard error [SE] = 2.3, t = −5.2, P < 0.01). There was no significant correlation between chick growth rate and overall feeding rate (â = 1.5, SE = 0.8, t = 1.8, P = 0.09). However, there was a significant negative association between growth rate and the interaction of butterfish proportion and overall feeding rate (â = −37.7, SE = 13.8, t = −2.7, P = 0.01; Fig. 2).

Variability in butterfish provisioning

The number of butterfish relative to all other prey in chick diets varied across the three years (χ² = 54.7, degrees of freedom = 2, P < 0.01). We found a significant relationship between diet and nest ID in 2018 (P < 0.01) and 2019 (P = 0.04), but not in 2017 (P = 0.57) using a Monte Carlo version of Fisher’s exact test.

When considering inter-nest variability in butterfish feeding for each year, the mean percentage (± SD) of chick diet that consisted of butterfish was 11 ± 13% in 2017 (ranging from 0–40%), 30 ± 30% in 2018 (ranging from 0–100%), and 4 ± 6% in 2019 (ranging from 0–20%; Fig. 3).

DISCUSSION

Common Tern chicks spent substantial time handling butterfish but infrequently gained nutritive rewards, with only 21% of butterfish being successfully swallowed (Fig. 1). Butterfish was the only prey category for which prey size had no significant effect on handling time. This result indicates that difficulty handling and ingesting butterfish is not a function of total length, but is likely driven by dorsoventral body depth, which, although not directly measured here, typically exceeded the gape of tern chicks across the range of butterfish sizes provisioned by adults. We also observed occasions during which chicks ignored other prey items offered to them while they were preoccupied handling butterfish, compounding nutritive costs of butterfish provisioning. Unconsumed butterfish were often discarded near the nest, where they were either picked up by a neighbor or left long enough to desiccate and decay.

Chicks that were fed higher proportions of butterfish had lower growth rates, likely due to the low probability of successful feeding and the associated energetic costs of long handling times. Although we expected to find that increased overall feeding rates would correlate with higher growth rates in chicks, we found this relationship to be positive but not significant. However, when considering the significant interaction between proportion of butterfish and overall feeding rate (Fig. 2), we found that increased feeding rates were associated with increased growth rate as expected, but only when proportions of butterfish in diets were low. When proportions of butterfish in diets were high, there was no association between feeding rate and chick growth. The association of butterfish provisioning with reduced growth rates in Common Tern chicks is particularly concerning, given the strong linkage between chick growth and survival in seabirds (Maness and Anderson 2013, Kress et al. 2017). Furthermore, post-fledging body mass has been linked to subadult survival in this species, and if chicks fail to put on weight prior to migration, we may see fewer young, prospecting birds returning to this colony in the future (Braasch et al. 2009).

Given that butterfish appear to be highly unsuitable prey for tern chicks, the question remains as to why tern adults feed their chicks this fish. We speculate that when encountering juvenile butterfish on foraging grounds, adult terns may capture this fish because it appears similar to other common, high-quality prey such as juvenile herring and hake, which are similar in length and also laterally compressed. However, once captured, we would presume that the deep-bodied morphology of butterfish would be apparent to an adult tern. This mismatch led us to question whether adults are sensitive to prey suitability.

We quantified variability in butterfish provisioning within the sampled population and found that number of butterfish in diets varied significantly among nesting pairs in 2018 and 2019, although not in 2017 (potentially due to smaller sample size in that year; Fig. 3). This finding highlights that adult terns breeding on the same island during the same season feed their chicks significantly different diets. In all three years, there were breeding pairs that were never observed provisioning butterfish to their chicks, even in 2018, when the relative abundance of butterfish in the diet of terns at this colony was highest. Adult terns adjust the size of prey provisioned when foraging, depending on nutritive needs of nestlings (Quiring et al. 2021), and our results suggest they are species-selective as well. However, these signs of individual specialization may not signal active butterfish avoidance, but could be driven by numerous factors, including other characteristics of the prey field (e.g., the distribution and abundance of high-quality prey) as well as characteristics of individuals birds (e.g., age, sex, physiological fitness, and site fidelity; Phillips et al. 2017, Nisbet et al. 2020). While the actual mechanism of dietary variation at this colony is a topic of ongoing investigation, chicks of terns that capture fewer butterfish, by whatever mechanism, are at an advantage. This consequence provides some means for adaptive response in the face of shifting prey communities in the GOM, contingent on continued availability of suitable prey into the future.

CONCLUSION

The effect of butterfish on Common Tern chicks described here highlights the significant role that prey species composition plays in the reproductive outcomes of terns. Continued monitoring of tern diets will be key to evaluating how and whether these seabirds are able to respond to changes in their prey communities, which are simultaneously affected by climate change and commercial fishing in the GOM (Pershing et al. 2021). Seabird diet data such as those presented here can fill gaps in fish stock assessments (Sydeman et al. 2022), including GOM fisheries for butterfish and other common prey species (e.g., Atlantic herring; Scopel et al. 2018, Deroba et al. 2019). We additionally suggest that seabird diet data can contribute to a more holistic approach to fisheries management (e.g., ecosystem-based fisheries management; Pikitch et al. 2004) that incorporates the needs of predators such as seabirds (Townsend et al. 2019). Through such an approach, juvenile fishes that are important both commercially and ecologically (Pikitch et al. 2014) can be monitored and protected to sustain marine ecosystems as a whole (Pikitch et al. 2004).

LITERATURE CITED

Adams, C. F. 2022. Update on the spatial distribution of butterfish, 1982–2019. Northeast Fisheries Science Center Reference Document 22-04. National Oceanic and Atmospheric Administration Fisheries, Northeast Fisheries Science Center, Woods Hole, Massachusetts, USA. https://doi.org/10.25923/R0P0-TY08

Adams, C. F., T. J. Miller, J. P. Manderson, D. E. Richardson, and B. E. Smith. 2015. Butterfish 2014 stock assessment. Northeast Fisheries Science Center Reference Document 15-06. National Oceanic and Atmospheric Administration Fisheries, Northeast Fisheries Science Center, Woods Hole, Massachusetts, USA. https://doi.org/10.7289/V5WM1BCT

Arnold, J. M., I. C. T. Nisbet, and S. A. Oswald. 2016. Energetic constraint of non-monotonic mass change during offspring growth: a general hypothesis and application of a new tool. Journal of Animal Ecology 85(2):476-486. https://doi.org/10.1111/1365-2656.12467

Arnold, J. M., S. A. Oswald, I. C. T. Nisbet, P. Pyle, and M. A. Patten. 2020. Common Tern (Sterna hirundo), version 1.0. In S. M. Billerman, editor. Birds of the world. Cornell Lab of Ornithology, Ithaca, New York, USA. https://doi.org/10.2173/bow.comter.01

Braasch, A., C. Schauroth, and P. H. Becker. 2009. Post-fledging body mass as a determinant of subadult survival in Common Terns Sterna hirundo. Journal of Ornithology 150:401-407. https://doi.org/10.1007/s10336-008-0362-2

Cairns, D. K. 1988. Seabirds as indicators of marine food supplies. Biological Oceanography 5(4):261-271.

Carloni, J., 2015. Common Tern (Sterna hirundo). Pages 324-339 in New Hampshire wildlife action plan. Revised edition. Appendix A: birds. New Hampshire Fish and Game Department, New Hampshire, USA. https://www.wildlife.state.nh.us/wildlife/documents/wap/appendixa-birds.pdf

Deroba, J. J., S. K. Gaichas, M.-Y. Lee, R. G. Feeney, D. Boelke, and B. J. Irwin. 2019. The dream and the reality: meeting decision-making time frames while incorporating ecosystem and economic models into management strategy evaluation. Canadian Journal of Fisheries and Aquatic Sciences 76(7):1112-1133. https://doi.org/10.1139/cjfas-2018-0128

Doney, S. C., M. Ruckelshaus, J. E. Duffy, J. P. Barry, F. Chan, C. A. English, H. M. Galindo, J. M. Grebmeier, A. B. Hollowed, N. Knowlton, J. Polovina, N. N. Rabalais, W. J. Sydeman, and L. D. Talley. 2012. Climate change impacts on marine ecosystems. Annual Review of Marine Science 4:11-37. https://doi.org/10.1146/annurev-marine-041911-111611

Durant, J. M., D. Ø. Hjermann, G. Ottersen, and N. C. Stenseth. 2007. Climate and the match or mismatch between predator requirements and resource availability. Climate Research 33:271-283. https://doi.org/10.3354/cr033271

Grémillet, D., and T. Boulinier. 2009. Spatial ecology and conservation of seabirds facing global climate change: a review. Marine Ecology Progress Series 391:121-137. https://doi.org/10.3354/meps08212

Hall, C. S., S. W. Kress, and C. R. Griffin. 2000. Composition, spatial and temporal variation of Common and Arctic Tern chick diets in the Gulf of Maine. Waterbirds 23(3):430-439. https://doi.org/10.2307/1522180

Hare, J. A., W. E. Morrison, M. W. Nelson, M. M. Stachura, E. J. Teeters, R. B. Griffis, M. A. Alexander, J. D. Scott, L. Alade, R. J. Bell, A. S. Chute, K. L. Curti, T. H. Curtis, D. Kircheis, J. F. Kocik, S. M. Lucey, C. T. McCandless, L. M. Milke, D. E. Richardson, E. Robillard, H. J. Walsh, M. C. McManus, K. E. Marancik, and C. A. Griswold. 2016. A vulnerability assessment of fish and invertebrates to climate change on the Northeast U.S. continental shelf. Plos One 11(2):e0146756. https://doi.org/10.1371/journal.pone.0146756

Hudson, M., and J. Peros. 2013. Preparing for emerging fisheries: an overview of mid-Atlantic stocks on the move. Gulf of Maine Research Institute, Portland, Maine, USA. https://gmri-org-production.s3.amazonaws.com/documents/Hudson_and_Peros_2013.pdf

Kress, S. W., P. Shannon, and C. O’Neal. 2017. Recent changes in the diet and survival of Atlantic puffin chicks in the face of climate change and commercial fishing in midcoast Maine, USA. Facets 1(1):27-43. https://doi.org/10.1139/facets-2015-0009

Maness, T. J., and D. J. Anderson. 2013. Predictors of juvenile survival in birds. Ornithological Monographs 78:1-55. https://doi.org/10.1525/om.2013.78.1.1

McHenry, J., H. Welch, S. E. Lester, and V. Saba. 2019. Projecting marine species range shifts from only temperature can mask climate vulnerability. Global Change Biology 25(12):4208-4221. https://doi.org/10.1111/gcb.14828

Mehta, C. R., and N. R. Patel. 2013. IBM SPSS exact tests. International Business Machines Corporation, Armonk, New York, USA. https://www.ibm.com/docs/en/SSLVMB_27.0.0/pdf/en/IBM_SPSS_Exact_Tests.pdf

Nisbet, I. C. T., D. Iles, A. Kaneb, C. S. Mostello, and S. Jenouvrier. 2020. Breeding performance of Common Terns (Sterna hirundo) does not decline among older age classes. Auk 137(3):ukaa022. https://doi.org/10.1093/auk/ukaa022

Pershing, A. J., M. A. Alexander, D. C. Brady, D. Brickman, E. N. Curchitser, A. W. Diamond, L. McClenachan, K. E. Mills, O. C. Nichols, D. E. Pendleton, N. R. Record, J. D. Scott, M. D. Staudinger, and Y. Wang. 2021. Climate impacts on the Gulf of Maine ecosystem: a review of observed and expected changes in 2050 from rising temperatures. Elementa: Science of the Anthropocene 9(1):00076. https://doi.org/10.1525/elementa.2020.00076

Pershing, A. J., M. A. Alexander, C. M. Hernandez, L. A. Kerr, A. Le Bris, K. E. Mills, J. A. Nye, N. R. Record, H. A. Scannell, J. D. Scott, G. D. Sherwood, and A. C. Thomas. 2015. Slow adaptation in the face of rapid warming leads to collapse of the Gulf of Maine cod fishery. Science 350(6262):809-812. https://doi.org/10.1126/science.aac9819

Phillips, R. A., S. Lewis, J. González-Solís, and F. Daunt. 2017. Causes and consequences of individual variability and specialization in foraging and migration strategies of seabirds. Marine Ecology Progress Series 578:117-150. https://doi.org/10.3354/meps12217

Pikitch, E. K., K. J. Rountos, T. E. Essington, C. Santora, D. Pauly, R. Watson, U. R. Sumaila, P. D. Boersma, I. L. Boyd, D. O. Conover, P. Cury, S. S. Heppell, E. D. Houde, M. Mangel, É. Plagányi, K. Sainsbury, R. S. Steneck, T. M. Geers, N. Gownaris, and S. B. Munch. 2014. The global contribution of forage fish to marine fisheries and ecosystems. Fish and Fisheries 15(1):43-64. https://doi.org/10.1111/faf.12004

Pikitch, E. K., C. Santora, E. A. Babcock, A. Bakun, R. Bonfil, D. O. Conover, P. Dayton, P. Doukakis, D. Fluharty, B. Heneman, E. D. Houde, J. Link, P. A. Livingston, M. Mangel, M. K. McAllister, J. Pope, and K. J. Sainsbury. 2004. Ecosystem-based fishery management. Science 305(5682):346-347. https://doi.org/10.1126/science.1098222

Poloczanska, E. S., C. J. Brown, W. J. Sydeman, W. Kiessling, D. S. Schoeman, P. J. Moore, K. Brander, J. F. Bruno, L. B. Buckley, M. T. Burrows, C. M. Duarte, B. S. Halpern, J. Holding, C. V. Kappel, M. I. O’Connor, J. M. Pandolfi, C. Parmesan, F. Schwing, S. A. Thompson, and A. J. Richardson. 2013. Global imprint of climate change on marine life. Nature Climate Change 3:919-925. https://doi.org/10.1038/nclimate1958

Quiring, K., G. Carroll, C. Champion, E. W. Heymann, and R. Harcourt. 2021. The diet of greater crested terns off southeast Australia varies with breeding stage and sea surface temperature. Marine Biology 168:143. https://doi.org/10.1007/s00227-021-03947-3

R Core Team. 2021. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/

Schaffner, F. C. 1986. Trends in Elegant Tern and northern anchovy populations in California. Condor 88(3):347-354. https://doi.org/10.2307/1368882

Scopel, L. C., A. W. Diamond, S. W. Kress, A. R. Hards, and P. Shannon. 2018. Seabird diets as bioindicators of Atlantic herring recruitment and stock size: a new tool for ecosystem-based fisheries management. Canadian Journal of Fisheries and Aquatic Sciences 75(8):1215-1229. https://doi.org/10.1139/cjfas-2017-0140

Scopel, L., A. Diamond, S. Kress, and P. Shannon. 2019. Varied breeding responses of seabirds to a regime shift in prey base in the Gulf of Maine. Marine Ecology Progress Series 626:177-196. https://doi.org/10.3354/meps13048

Selden, R. L., R. D. Batt, V. S. Saba, and M. L. Pinsky. 2018. Diversity in thermal affinity among key piscivores buffers impacts of ocean warming on predator-prey interactions. Global Change Biology 24(1):117-131. https://doi.org/10.1111/gcb.13838

Staudinger, M. D., K. E. Mills, K. Stamieszkin, N. R. Record, C. A. Hudak, A. Allyn, A. Diamond, K. D. Friedland, W. Golet, M. E. Henderson, C. M. Hernandez, T. G. Huntington, R. Ji, C. L. Johnson, D. S. Johnson, A. Jordaan, J. Kocik, Y. Li, M. Liebman, O. C. Nichols, D. Pendleton, R. A. Richards, T. Robben, A. C. Thomas, H. J. Walsh, and K. Yakola. 2019. It’s about time: a synthesis of changing phenology in the Gulf of Maine ecosystem. Fisheries Oceanography 28(5):532-566. https://doi.org/10.1111/fog.12429

Suca, J. J., J. J. Deroba, D. E. Richardson, R. Ji, and J. K. Llopiz. 2021. Environmental drivers and trends in forage fish occupancy of the Northeast US shelf. ICES Journal of Marine Science 78(10):3687-3708. https://doi.org/10.1093/icesjms/fsab214

Suddaby, D., and N. Ratcliffe. 1997. The effects of fluctuating food availability on breeding Arctic Terns (Sterna paradisaea). Auk 114(3):524-530. https://doi.org/10.2307/4089260

Sydeman, W. J., E. Poloczanska, T. E. Reed, and S. A. Thompson. 2015. Climate change and marine vertebrates. Science 350(6262):772-777. https://doi.org/10.1126/science.aac9874

Sydeman, W. J., S. A. Thompson, J. F. Piatt, S. G. Zador, and M. W. Dorn. 2022. Integrating seabird dietary and groundfish stock assessment data: Can puffins predict pollock spawning stock biomass in the North Pacific? Fish and Fisheries 23(1):213-226. https://doi.org/10.1111/faf.12611

Terwilliger Consulting. 2015. Taking action together: northeast regional synthesis for state wildlife action plans. Terwilliger Consulting and the Northeast Fish and Wildlife Diversity Technical Committee, Locustville, Virginia, USA. https://rcngrants.org/sites/default/files/final_reports/Northeast%20Regional%20Conservation%20Synthesis_September2015.docx

Townsend, H., C. J. Harvey, Y. deReynier, D. Davis, S. G. Zador, S. Gaichas, M. Weijerman, E. L. Hazen, and I. C. Kaplan. 2019. Progress on implementing ecosystem-based fisheries management in the United States through the use of ecosystem models and analysis. Frontiers in Marine Science 6:641.