Quantifying inter-annual variability on the space-use of parental Northern Gannets (Morus bassanus) in pursuit of different prey types

Kyle J N d’Entremont; Isabeau Pratte; Carina Gjerdrum; Sarah N P Wong; William A Montevecchi

doi:10.1371/journal.pone.0288650

. 2023 Jul 14;18(7):e0288650. doi: 10.1371/journal.pone.0288650

Quantifying inter-annual variability on the space-use of parental Northern Gannets (Morus bassanus) in pursuit of different prey types

Kyle J N d’Entremont ^1,^*, Isabeau Pratte ², Carina Gjerdrum ², Sarah N P Wong ², William A Montevecchi ¹

Editor: Vitor Hugo Rodrigues Paiva³

PMCID: PMC10348513 PMID: 37450481

Abstract

Spatial planning for marine areas of multi-species conservation concern requires in-depth assessment of the distribution of predators and their prey. Northern Gannets Morus bassanus are generalist predators that predate several different forage fishes depending on their availability. In the western North Atlantic, gannets employ different dive tactics while in pursuit of different prey types, performing deep, prolonged U-shaped dives when foraging on capelin (Mallotus villosus), and rapid, shallow, V-shaped dives when foraging on larger pelagic fishes. Therefore, much can be inferred about the distribution and abundance of key forage fishes by assessing the foraging behaviour and space-use of gannets. In this study, we aimed to quantify space-use and to determine areas of suitable foraging habitat for gannets in pursuit of different prey types using habitat suitability models and kernel density utilization distributions. We deployed 25 GPS/Time-depth recorder devices on parental Northern Gannets at Cape St. Mary’s, Newfoundland, Canada from 2019 to 2021. To assess the influence of environmental variables on gannets foraging for different prey types, we constructed three different habitat suitability models: a U-shaped dive model, and two V-shaped dive models (early and late chick-rearing). Suitable foraging habitat for capelin, deduced by the U-shaped dive model, was defined by coastal, shallow waters with flat relief and sea surface temperatures (SST) of 11–15° C. Suitable habitat for early V-shaped dives was defined by shallow and coastal waters with steep slope and SST of 12–15°C and ~18°C, likely reflecting the variability in environmental preferences of different prey species captured when performing V-shaped dives. Suitable habitat for late V-shaped dives was defined by shallow coastal waters (<100m depth), as well as waters deeper than 200 m, and by SST greater than 16°C. We show that space-use by gannets can vary both within and between years depending on environmental conditions and the prey they are searching for, with consequences for the extent of potential interaction with anthropogenic activities. Further, we suggest regions defined as suitable for U-shaped dives are likely to be critical habitat of multi-species conservation concern, as these regions are likely to represent consistent capelin spawning habitat.

Introduction

Anthropogenic stressors are negatively impacting marine ecosystems worldwide, particularly in coastal environments where human activity is most concentrated [1]. Marine birds are susceptible to harm from many of these stressors, including light pollution [2, 3], chronic oil pollution [4, 5], and depleted forage fish populations due to overfishing and climate-induced shifts in distribution, phenology, and regional predictability [6–10].

Coastal southeastern Newfoundland (NL) is a region where a high degree of anthropogenic activity and large populations of marine birds overlap. In this region, anthropogenic risks of greatest concern for marine birds include marine traffic (fisheries, shipping, oil transport, tourism, and recreational use), bycatch in longlines and gillnets, light pollution, and chronic ship-source oil pollution [2, 11–13]. Climate change and overfishing have also been linked to massive declines in biomass and recruitment success of three key forage fish species in this region: Atlantic mackerel (Scomber scombrus, [14, 15]), Atlantic herring (Clupea harengus, [16]) and capelin (Mallotus villosus, [17]).

The Northern Gannet (Morus bassanus), the largest breeding seabird in the North Atlantic, is a generalist, opportunistic feeder, that preys on a wide range of forage fish species depending on availability, which changes dramatically within and between years [18–20]. Northern Gannet colonies in the western North Atlantic, including the southernmost colony in the world at Cape St. Mary’s, NL, have exhibited record low productivity in recent years, and plateaued population size, which have been associated with declines in prey availability due to overfishing and climate change [8, 9, 21].

Northern Gannets use different foraging tactics depending on the prey type they are foraging upon. In the western North Atlantic ecosystem, these differences are expressed quantifiably by dive profiles, with prolonged, deep, U-shaped dives associated with pursuit and capture of capelin, while shallow, V-shaped dives are associated with rapid capture of mackerel, Atlantic saury (Scomberesox saurus) and Atlantic herring [19, 20, 22, 23]. Northern Gannets breeding at Cape St. Mary’s, NL, demonstrate distinct shifts in dive profiles, with U-shaped dives falling out of favor to almost exclusively using V-shaped dives as the breeding season progresses [20].

Habitat suitability models have been used broadly to identify critical habitat for several seabird species (e.g., [24–26]). Modelling habitat suitability using locations of different dive profiles allows us to delineate key foraging areas and how they might vary temporally and with the pursuit of different prey types. We propose that these models can also be used as proxies to identify key habitat areas and environmental drivers for the distribution of these key forage fish.

Our main objectives were to 1) identify key foraging areas for Northern Gannets in southeastern Newfoundland, and 2) determine if Northern Gannet foraging areas differed when using different foraging tactics (e.g., dive profiles). From this assessment, we aimed to provide information on how environmental factors might influence the distribution of Northern Gannets and their prey, for a better understanding of critical areas of multi-species conservation management concern in southeastern Newfoundland.

Methods

Study area and species

Cape St. Mary’s Ecological Reserve (46.81°N, 54.18°W) lies west of Placentia Bay, east of St. Mary’s Bay, and north of the southeastern Grand Banks at the southwestern tip of the Avalon Peninsula in eastern Newfoundland, Canada (Fig 1). This site is home to 14,598 breeding pairs of Northern Gannets as of 2018, which represents approximately 14% of the Eastern Canadian population [9, 27]. Since 2010, population size has plateaued, and productivity has been low, like that observed at the largest North American colony located in Quebec (Bonaventure Island, [9]). Average incubation time of gannets in the western North Atlantic is ~44 d (late April to late June) with an average chick-rearing period of ~90 d, ranging from early June to October [28].

Fig 1 — Isobaths (grey lines) are at 50 m intervals. Grey dots are all diving locations recorded in 2019, 2020, and 2021. SPM = Saint-Pierre-et-Miquelon.

GPS device deployment

Ten gannets in 2019, seven gannets in 2020, and eight gannets in 2021 were fitted with either battery (n = 7) or solar-powered (n = 18) Ecotone Uria 300 GPS loggers with Temperature-Depth Recorders (TDR). Five devices were deployed on both July 18, 2019, and August 21, 2019. Seven devices were deployed on July 18, 2020. Eight devices were deployed on July 15, 2021. Tagged birds had chicks that were ~2–4 weeks old when devices were deployed. Tags weighed 13.5 g (dimensions: 36x22x12.5 mm) and were attached to the four innermost rectrices just below the uropygial gland with Tesa ® tape and cable ties. Birds were captured using extendable noose poles, weighed with a 5 kg Pesola ® spring scale, and equipped with Canadian Wildlife Service aluminum bands on their right legs. Mean mass of tagged gannets across all three years was 3547 ± 459 g. GPS devices were < 0.5% of body mass for all individuals and the risk of negative tag effects was minimized [29]. Tags were set to record the location of each bird every 15 min. Dive depth was recorded every 1 s after submersion during dives (i.e. from first entry into water until resurfacing). An Ecotone base station with a directional antenna was installed ~50 m away from the colony to upload data from devices when birds returned to the colony. The detection range of the base station varies from 200–500 m, depending on environmental conditions. Devices were set to only record GPS locations and dive information when out of range of the base station to conserve battery life. Gannets were handled under the Canadian Wildlife Service permit 10332K and Memorial University of Newfoundland Animal Care Committee animal care permit 19-01-WM.

Data processing

All data processing and subsequent analysis were conducted using the statistical software “R” version 4.04 [30]. Dive depth, duration, and bottom time from GPS-tagged gannets were determined for each dive using the package ‘diveMove’ [31]. Dives that were less than 1 m in depth were removed from further analysis, as these may have been associated with bathing bouts and unlikely to be in pursuit of prey. All dives which had a bottom time ≥ 3 s, and/or total duration > 10 s and a depth > 8 m were designated as “U” dives and all dives which had a bottom time < 3 s, and/or durations < 10 s and depth < 8 m were considered “V” dives (see [21]). Foraging locations were considered to be any GPS location recorded within 30 min before a dive (e.g., [20]). Although U-shaped dives peak during early chick-rearing, V-shaped dives are performed by gannets throughout the chick-rearing period. To account for the differing prey species in the region in early and late chick-rearing and the possibility that early V-shaped dives could be associated with herring rather than mackerel, or singular capture of capelin (rather than a U-shaped dive for multiple fish), we divided V-shaped dives in two categories: early and late V-shaped dives. We used the marked drop in daily proportions of U-dives as the cut-off date to classify early vs late V-shaped dives (Fig 2; 2019–16-Aug, 2020 and 2021–10-Aug).

Fig 2 — The black vertical line indicates the cut-off point used to classify V-shaped dives occurring early or late (2019–16-Aug, 2020 and 2021–10-Aug).

Dive distributions

We tested for independence between year and dive shape using a Chi-square test to determine if there was an association in the distribution of dive shapes among years. The spatial distribution of each dive type was analyzed using the package ‘track2KBA’ [32] to estimate 50% and 95% kernel density utilization distributions (UDs). The 50% UD represents core areas of diving locations (e.g., where 50% of dive locations are concentrated, whereas the 95% UD represents the range of diving activity across the animals’ home range). We used the function findScale, which uses First Passage Time analysis to identify the spatial scale of movement at which area-restricted search is occurring within individual trips. This function returns a value corresponding to the log of the average foraging range (mag) and is considered a conservative approach to the estimation of utilization distribution of central place foragers [32]. However, given that we were interested in estimating utilization distributions of diving locations distinctly considered from the animals’ full trajectories, the scale at which those occur was not comparable to the scale at which central place foraging occurs in relation to an animals’ complete movement along a foraging trip. Thus, we multiplied the log of the average foraging range by 2 for our smoothing term h (8 km) to achieve better coverage when considering the 95% UD and ensure we were not under-representing the area used by foraging gannets. The purpose of using the kernel estimator in our case was to visually represent the distribution of the different dive shapes across years. Since prey distribution and availability are driven by environmental conditions [33–36], we assume the two dive profiles reflect prey type availability [37]. Thus, we built three habitat suitability models for each type of dive (U-, early V-, late V-shaped dives).

Habitat suitability modelling

For the computation of habitat suitability models, we extracted environmental variables from a domain representative of the foraging area of parental Northern Gannets as determined from GPS tracks. This domain was defined by the farthest eastern and western distances from the colony reached by an individual performing a dive multiplied by 1.1 (451 km), then by drawing an arc until reaching the continental shelf drop in the south, and until reaching the latitude of the northernmost location reached by a gannet (see Fig 1). In each year and for each dive type, three random locations (hereafter “pseudo-absences”) were generated within the domain for each GPS device derived foraging location (hereafter “presence”) using the spsample function in the R package ‘sp’ ([38], see also [24, 39]). Each pseudo-absence was randomly assigned a date within the range of the study period each year. To build habitat suitability models for each dive type, we included the following covariates: sea surface temperature (SST,°C resolution of 0.01°, daily), depth (GEBCO, m; resolution of 0.004°), slope, distance to colony (km), latitude and longitude. Chlorophyll a was also considered but removed from further models due to poor spatiotemporal coverage over the study period. SST data were retrieved from the Multi-scale Ultra-high Resolution SST Analysis fv04.1 dataset on the Environmental Research Division’s Data Access Program (ERDDAP, https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41.html). For each presence and pseudo-absence, values for all environmental variables were extracted using the package ‘raster’ [40], and distance from the colony (km) was determined.

Given that autocorrelation is inherent to tracking data and that individuals may have different habitat preferences, fitting random slopes for individuals might be useful. However, differing random effect levels prevent mixed effects models from predicting into new datasets [41, 42]. Thus, in our case, GAMs were a practical modelling approach and individuals were not considered as random effects due to the impracticability given our predictions. For each dive type, we determined which variables to include in our final model by constructing a generalized additive model (GAM) with each variable included as the smooth parameters of the model and using penalized thin-plate regression spline. Latitude and longitude were smoothed using a two-dimensional spline. Year was also added as a fixed term in the model. The binomial response was true location (presence, 1), and the randomized background points (pseudo-absence, 0). We first tested for pairwise concurvity in the model components using the concurvity function of the ‘mgcv’ package (version 1.8–42; [43]). Then, for each dive type, automated model selection was performed on the global model using the dredge function of the package “MuMIn” (version 1.45.7; [44]). Models were compared using Akaike information criterion (AICc) and we selected for our final predictive model the one with the smallest AICc (Table 2).

Table 2. Top three candidate models following automated model selection.

Plus signs (+) represent the inclusion of covariate use as smooth terms in the global GAM models. Year was considered as a fixed term in the GAM models. Akaike model weights (w) are also shown and further informed model selection. Final models were selected based on the lowest AICc and are represented in bold.

U-shape	Year	Bathy	Lat:Lon	Slope	SST	df	AICc	delta	w
	+	+	+	+	+	34	987.88	0	0.68
	+	+	+		+	31	989.61	1.73	0.29
		+	+	+	+	32	994.95	7.07	0.68
V-shape early	Year	Bathy	Lat:Lon	Slope	SST	df	AICc	delta	w
	+	+	+	+	+	53	4019.12	0	1
	+	+	+		+	45	4091.82	72.7	0
		+	+	+	+	51	4105.98	86.86	0
V-shape late	Year	Bathy	Lat:Lon	Slope	SST	df	AICc	delta	w
	+	+	+		+	39	2450.27	0	0.72
	+	+	+	+	+	34	2452.18	1.9	0.28
	+		+		+	37	2482.87	32.59	0

Open in a new tab

For the duration of the three-year tracking period, we predicted the daily probability of occurrence of each dive shape within the domain defined for Northern Gannets breeding at Cape St. Mary’s. The mean number of dives per day across all three years was 70.8 ± 4.7 SE (n = 199), though the number of dives per day consistently decreased as the breeding season progressed in each year (Fig 3). A grid was overlaid over the domain extent at a resolution corresponding to the lowest common resolution of our final environmental layers (0.01°, ~1000 m for the SST layer). For each day of the study period, we extracted values from the covariates included in our final models at the centroid of each grid square. We predicted the probability of occurrence for U, early and late V-shaped dives using the function predict.gam (‘mgcv’ package) for each day of the tracking study (predicted within the respective time spans for early and late V-dives), obtaining a daily habitat suitability index (HSI) for each dive type. We averaged the resulting HSI raster layers to generate a final predictive map reflecting the average daily probability of occurrence of U, early and late V-shaped dives, and the error of the spatial prediction was summarized by calculating the pixel-specific standard deviation. Given that the only dynamic variable used was SST, minimal differences were noted when using the model to predict HSI for each of the three study years, thus we presented an overall model prediction by averaging daily predictions obtained over the three years.

Results

Dive distributions

There was significant temporal variation in the distributions of U- and V-shaped dives among years (χ² = 122.78, p < 0.001). For example, fewer U-shaped dives were performed by gannets than expected in 2019 and 2021 (Table 1). There were fewer than expected V-shaped dives during early chick-rearing and more than expected during late chick-rearing in 2019, but this effect was reversed in 2021. Only in 2020 were more U-shaped dives recorded than expected, and generally fewer V-shaped dives were observed that year (Table 1).

Table 1. Sample size and tracking period (when dives were recorded) for each year during which Northern Gannets were tracked from Cape St. Mary’s, NL.

Number of observed dives of each shape in each year, and number of expected dives of each shape in each year and their residuals following Chi-square test (χ² = 122.78, df = 4, p < 0.001).

			Observed			Expected			Residuals
Year	N ind.	Tracking period	U	V-early	V-late	U	V-early	V-late	U	V-early	V-late
2019	10	19-Jul to 29-Sept	347	1074	748	419	1200	551	-3.5	-3.6	8.4
2020	7	18-Jul to 26-Sept	543	1075	414	392	1124	516	7.6	-1.5	-4.5
2021	8	15-Jul to 09-Sept	138	797	190	217	622	286	-5.4	7	-5.7

Open in a new tab

The spatial distribution of U-shaped dives by Northern Gannets appeared consistent across years, with 50% UD areas centered around the colony but extending slightly further east in 2021 (Fig 4). Early V-shaped dives had an extended distribution compared to the area used for U-shaped dives, especially in 2021 (Fig 4). The extent of late V-shaped dives was much wider-ranging than the other two dive types, especially in 2019 and 2020 when foraging gannets travelled west to Saint-Pierre-et-Miquelon and to Fortune Bay.

Fig 4 — Utilization distributions are shown by the solid line (50% UD) and the dashed line (95% UD), smoothing parameter h = 8 km. Saint-Pierre-et-Miquelon (SPM).

Model predictions

Response to the suite of environmental variables included in our models predicted that suitable habitat for late V-shaped dives was more extensive and diffuse than for U-shaped and early V-shaped dives (Fig 5), for which the probability of occurrence was more clustered around the southern coast of the Avalon Peninsula. Although early V-shaped dives co-occurred with U-shaped dives, the former were more likely to be farther from the colony, over Placentia Bay, and generally in offshore areas south of the Avalon Peninsula (Fig 5B). U-shaped dives were strikingly more coastal (Fig 5A). Overall, the predictive habitat models for each type of dive captured the variability observed in the foraging distribution of Northern Gannets across years, but also highlighted areas of lower density (outside the 50% UD).

Fig 5 — Spatial habitat predictions for a) U-shaped dives, b) early and c) late V-shaped dives of Northern Gannets tracked from Cape St. Mary’s (yellow diamond) during three breeding seasons. Average of daily habitat suitability index (HSI) scaled from 0 (unsuitable) to 1 (highly suitable) (a, b, c), and standard deviation of daily HSI for d) U-shaped dives, e) early and f) late V-shaped dives. The spatial resolution of the prediction was set to the lowest resolution of our environmental layers (SST, at 1000m). Utilization distributions at 50% for each dive type are overlaid on the top panels for each year represented by different line types (solid—2019, dashed—2020, dotted—2021). Saint-Pierre-et-Miquelon (SPM).

After checking for concurvity of our global model components, we discarded the covariate distance to the colony from the model for each dive type as concurvity with the other covariates included as smooth terms (latitude/longitude, slope, SST) was high (> 0.9). Following model selection, the final GAMs retained all the covariates tested (bathymetry, latitude/longitude, slope, and SST) except the model for late V-dives, which did not include slope (Table 2). For U-shaped dives, the model explained 76.7% (adjusted R² = 0.78) of the total deviance. The model for early V-shaped dives explained 67.8% (adjusted R² = 0.68) of the total deviance, while the model for late V-shaped dives explained 60.2% (adjusted R² = 0.61) of the total deviance.

The partial response curves from the GAM models indicated that the probability of occurrence of U-shaped dives decreased between sea surface temperatures spanning from about 14°C to 18°C (Fig 6A), while probability of occurrence of V-shaped dives during both early and late chick-rearing increased at temperature beyond 16°C and this was slightly more pronounced for V-shaped dives occurring later (Fig 6B and 6C). V-shaped dives were more likely to occur over a broader area compared to U-shaped dives which were more constrained in space and more likely to occur around 54°W and 52°N (Fig 6). Probability of occurrence of U-shaped dives increased slightly when foraging at shallower depths (ca > 75 m). This response was different for V-shaped dives, for which probability of occurrence in relation to depth was positive both for deeper (ca < 200 m) and shallower waters (ca > 100 m). The response to slope was marginal, with fewer data points falling over slopes greater than 8°, but different among dive types and was not a covariate retained for late V-shaped dives. Overall, U-shaped dive occurrence positively responded to flatter sea bottom (0–5°slope, Fig 6A), although this response was marginal. Early V-shaped dives had higher positive response to steeper slope, but also had greater error owing to fewer data points falling over steeper slope.

Fig 6 — Model variables for estimated probability of occurrence of a) U-shaped dives and b) early and c) late V-shaped dives by Northern Gannets tracked during three breeding seasons (2019–2021) at the colony of Cape St. Mary’s, Newfoundland. The y-axis represents the function of each predictor variable with the effective degrees of freedom (edf) of the smooth term in brackets. 0 on the y-axis corresponds to absence of an effect of the predictor variable on the estimated probability of occurrence. Environmental variables included as smooth terms in the GAMs were daily sea surface temperature (SST;°C), bathymetry (Bathy; m), slope (°), and longitude and latitude (°) considered as 2-dimensional spline in the smooth function; the y-axis scale varies to emphasise model fit. The confidence intervals (dashed lines) are shown at 1 standard error above and below the smoothed estimate.

Discussion

This study is the first to quantify associations between the foraging of the Northern Gannet on different prey types (e.g., U-shaped dives for capelin; V-shaped dives for mackerel, saury, etc.) and environmental variables using habitat suitability models in the western North Atlantic.

Increased foraging effort by seabirds, including gannets, is often indicative of decreased prey availability [45–48], suggesting increased foraging effort on capelin was required in 2020, perhaps because other prey (i.e., mackerel, saury) were not yet available, or because capelin availability was low. The notion that an increase in U-shaped dives was associated with lowered prey availability is consistent with the fact that capelin availability (e.g., biomass and spawning locations) in Newfoundland waters was lower than usual in 2020 [20, 49]. The number of V-shaped dives was greater than expected in both 2019 and 2021, suggesting that there may have been increased effort associated with lower availability of mackerel and saury in these years [9]. As capelin is a key prey species for gannets during early chick-rearing due to the size and energetic requirements of chicks [50], this might explain why U-dives were greater than expected when capelin availability was low in 2020. The reliance on capelin in early chick-rearing due to its energy density and size of the chick (e.g., prey larger than the smaller capelin may not be consumable by the smaller chicks at this stage) constrains foraging plasticity at this critical time.

Habitat suitability in pursuit of varying prey types

The U-shaped dive model suggested that suitable habitat for capelin was constrained towards coastal shallow waters with flat bottom relief, with SST ranging between ~11–15°C. Plus, the probability of occurrence decreased as SST increased above 15°C, which is consistent with the tendency for capelin to only spawn in waters below 12°C [51, 52]. Moreover, the decreasing probability of occurrence of U-shaped dives as seafloor slope increases is consistent with the typical spawning site characteristics of capelin in coastal Newfoundland, i.e., flat bottom relief and/or depressions on the seafloor confined by gently sloping marine trenches [53]. This further strengthens previous assertions that U-shaped dives by Northern Gannets in the western North Atlantic are primarily associated with foraging on spawning capelin [20, 22, 23]]. Furthermore, areas deemed highly suitable for capelin foraging by gannets overlaps with putative beach and deep-water spawning areas identified by capelin fishers with extensive knowledge and experience of the local distribution of this species [54]. Thus, as U-shaped dives tend to be specific to capelin in this ecosystem, these habitat suitability models could be considered as a proxy for suitable habitat for capelin. More importantly, the areas deemed highly suitable for capelin within this study are also likely to be critical regions of multi-species management concern as many aquatic (e.g. Atlantic cod Gadus morhua) and avian predators (e.g., black-legged kittiwakes Rissa tridactyla, common murres Uria aalge, Atlantic puffins Fratercula arctica) heavily rely on capelin [55–57].

The early V-shaped dive model suggested that during early chick-rearing, gannets are foraging in areas with shallow waters, over steeper slopes, and constrained to SST ranging from 11–15°C or above 18°C. Thus, the effect of SST on early V-shaped dive occurrence is possibly linked with the water temperature preferences of prey species other than capelin; indeed, mackerel prefer temperatures of 9–13°C while saury tend to inhabit warmer waters of ~18°C [58, 59]. Therefore, it is plausible that early V-shaped dives are used when foraging for mackerel and saury as they start to migrate into the region in late July [60, 61]. As well, this SST range also includes the thermal preference for adult herring (8–12°C, [62]), meaning that V-shaped dives could also indicate foraging on herring. Some V-shaped dives were associated with steeper slopes; and it is unlikely that gannets were foraging for spawning capelin at those sites given capelin prefer areas with flat bottom relief [51, 52]. However, it is possible that some V-shaped dives were in pursuit of small aggregations of capelin and/or capelin migrating to deeper waters away from their spawning grounds [63] given that V-shaped dives also had a slightly higher chance of occurring over flatter bottom relief. Overall, both early and late V-shaped dive models revealed that probabilities of occurrence of both dive types were higher over a broader geographic area, which was reflected in the utilization distribution of both dive types compared to U-shaped dives. Key habitat during late chick-rearing covered a broader geographic range within the study region, that was characterized by relatively shallow waters, but also to a higher probability of utilizing deeper waters, likely as a result of range expansion offshore. Later in the season, as SST increases and capelin abundance decreases, gannets forage on other prey [20], such as saury and mackerel which prefer warmer waters [58, 59].

Overall, the predictions obtained from the models built for each dive type captured the variability observed in the foraging distribution of Northern Gannets across years, and highlighted areas of lower density (outside the 50% UD). For example, this might suggest that the west and inner coast of Placentia Bay represents more favorable habitat for gannets performing U-shaped and early V-shaped dives. Considering the inter-annual variability in space use, such an area might be used in some years, and not others. Finer scale environmental predictors and better knowledge of prey distribution and behaviour would be beneficial, especially for V-shaped dives during late chick-rearing, for which the model explained only 60.2% of the total deviance. V-shaped dives are performed for more than one prey type that could have different habitat preferences, thus making it difficult to capture in a single model. Nonetheless, the results from our models built with different dive types are mirroring what we know about the temperature tolerances of key forage fishes, and gannet behavioural responses to those [7, 64].

Risk associated with anthropogenic activity and climate change

Space-use by gannets ranging from Cape St. Mary’s depends on exploitation of different prey bases and their breeding and migratory phenology, so the anthropogenic pressures gannets face in southeastern Newfoundland can differ both intra- and inter-annually. During early chick-rearing (July/early August), gannets typically foraged in coastal waters, while during late chick-rearing, adults were less constrained to the coast and extended their foraging distribution towards more pelagic waters. These patterns would place them at greater risk of encountering gillnets associated with inshore cod and Atlantic herring fisheries [12] during early chick-rearing, and more likely to interact with large vessels (e.g., oil tankers) passing through shipping lanes during late chick-rearing [13, 65].

Given projections of warming ocean climate [66], marine ecosystems such as the western North Atlantic will experience further shifts in the phenology and distribution of critical prey species [67–69], and subsequently, behaviour, foraging distribution, and breeding success of marine top predators [70]. Hence, it is expected that gannets will have to expend greater energy on foraging to compensate for changes in availability, as has already been observed in the western North Atlantic during years of poor capelin availability ([20]; see also [46]).

Capelin has exhibited a 30-fold decline in biomass and delayed spawning in the western North Atlantic since the early 1990s [17, 35]. Continued declines in capelin biomass could occur with earlier sea ice retreat that results in earlier spring bloom of primary producers, ultimately impacting copepods—the key prey of capelin [35]. Such mismatches could represent a cascading effect through the food web creating shortages and mismatches of capelin availability with the food requirements of parental seabirds provisioning offspring [17, 35]. Ocean temperature is the most predictive environmental variable of the horizontal and vertical distribution of capelin from June to November within the study region (e.g., warmer waters linked to decreased presence; [71], with the importance of ocean temperature on capelin distribution being greatest in August. This influence of warming waters on capelin distribution is critical as it completely overlaps with the chick-rearing period of Northern Gannets breeding at Cape St. Mary’s. If current warming trends continue, capelin distributions could shift northwards and to deeper waters during the gannets breeding season, reducing prey availability. However, as gannets exhibit foraging plasticity within and between years (e.g., [20, 64, 72]), they may be able to compensate for these distributional shifts by exploiting other prey species. Along with continued demographic monitoring at the colony to measure population-level impacts, further monitoring of foraging behaviour of parental gannets at Cape St. Mary’s is warranted to assess ocean climate responses to these distributional shifts.

The spawning distribution of Atlantic mackerel is also expected to shift northwards in the coming decades [67], with a significant overlap likely to occur within the foraging range of Cape St. Mary’s gannets during incubation (May-June) and early (July) chick-rearing period [20]. This shift could cause temporal and spatial mismatches between gannets and mackerel, with mackerel becoming available during early chick-rearing, and limited in late chick-rearing as sea water temperature rise above the species’ thermal threshold of ~15–16°C [7, 9, 59]. As mackerel is a critical prey species for Northern Gannets during late chick-rearing [50], such a shift could have consequences for gannet reproductive success if they are unable to supplement their diet with alternative prey sources. Such supplementation of alternate prey sources could be achieved by a potential increase in saury availability if average sea surface temperatures of ~18°C (the preferred temperature of Atlantic saury, [58]) are reached during the late chick-rearing period. It remains to be seen how gannets might respond to such drastic ecosystem shifts. Warming ocean temperatures in spring/early summer could also cause poor herring spawning conditions and induce a shift from spring spawning to mainly autumnal spawning in eastern Newfoundland [73]. Such a seasonal shift would likely change herring abundance throughout the chick-rearing period, from being an important prey during early chick-rearing towards being available during late chick-rearing, which would alter the space-use of foraging gannets throughout chick-rearing.

Conclusions

Northern Gannets are flexible and opportunistic generalist top predators [64] that use different foraging tactics for different prey species and behavioural shifts from exploiting cold-water species in early chick-rearing, to primarily warm-water species in late chick-rearing (e.g., [20]). Knowing these biological patterns, we have shown that space-use by parental Northern Gannets in the western North Atlantic differs depending on the prey species they are foraging on (e.g., inshore, shallow waters for capelin and deeper, more pelagic waters for mackerel and saury, etc.). Further, we demonstrate that examining habitat suitability for organisms employing different foraging tactics is a valuable tool for determining how space-use can change when they are reliant on temporally constrained prey sources.

We also show that Northern Gannets may be susceptible to the negative effects of our warming climate, with foraging habitat suitability being heavily reliant on SST thresholds of their poikilothermic prey. With capelin and herring likely becoming less abundant in early chick-rearing and mackerel likely shifting to be more abundant during early chick-rearing, it is likely that gannets will shift their space-use and prey preferences in Newfoundland as climate change forces distributional and phenological shifts of their prey. These shifts in prey distributions could also change the temporal overlap between gannets and anthropogenic activities (e.g., oil tankers and fishing vessels) and warrants further monitoring in the years ahead.

Acknowledgments

We must thank several people for their help with this study. The Cape St. Mary’s Ecological Reserve staff were invaluable, providing accommodations and logistical support over the years. We thank staff member Chris Mooney in particular, for his assistance with tagging gannets in the field. We thank Rob Ronconi and Sabina Wilhelm of the Canadian Wildlife Service for providing funding support for purchase of tags. We also thank the Newfoundland and Labrador Parks and Natural Areas Division for allowing us to conduct our research at the Cape St. Mary’s Ecological Reserve. Gannets were handled under the Canadian Wildlife Service permit 10332K and Memorial University of Newfoundland and Labrador animal care permit 19-01-WM.

Data Availability

The entire minimal underlying dataset pertinent for this manuscript is publicly available in a data package on the biotelemetry data repository “MoveBank” at the following DOI: https://doi.org/10.5441/001/1.5km7v2s3.

Funding Statement

WAM received grant #2018-06872 from the Natural Sciences and Engineering Research Council of Canada Discovery Grant program. The funder played no role in study design or the publication process. URL: https://www.nserc-crsng.gc.ca/professors-professeurs/grants-subs/dgigp-psigp_eng.asp WAM received the sub-grant # 57177 to Memorial University of Newfoundland and Labrador from the Fisheries and Oceans Canada Coastal Environmental Baseline Program. The funder played no role in study design or the publication process. URL: https://www.dfo-mpo.gc.ca/science/partnerships-partenariats/research-recherche/cebp-pdecr/index-eng.html.

References

1.Halpern BS, Walbridge S, Selkoe KA, Kappel CV, Micheli F, D’Agrosa C et al., A global map of human impact on marine ecosystems. Science. 2008; 319, 948–952. doi: 10.1126/science.1149345 [DOI] [PubMed] [Google Scholar]
2.Gjerdrum C, Ronconi RA, Turner KL, Hamer, TE. Bird strandings and bright lights at coastal and offshore industrial sites in Atlantic Canada. Avian Conserv Ecol. 2021; 16(1):22. 10.5751/ACE-01860-160122 [DOI] [Google Scholar]
3.Wilhelm SI, Dooley SM, Corbett EP, Fitzsimmons MG, Ryan PC, Robertson GJ. Effects ofland-based light pollution on two species of burrow-nesting seabirds in Newfoundland and Labrador, Canada. Avian Conserv Ecol. 2021; 16(1):12. 10.5751/ACE-01809-160112 [DOI] [Google Scholar]
4.Wiese FK, Robertson GJ. Assessing seabird mortality from chronic oil discharges at sea. J Wildl Manage. 2004; 68: 627–638. 10.2193/0022-541X(2004)068[0627:ASMFCO]2.0.CO;2 [DOI] [Google Scholar]
5.Robertson GJ, Wiese FK, Ryan PC, Wilhelm SI. Updated numbers of murres and dovekies oiled in Newfoundland waters by chronic ship-source oil pollution. In Proceedings of the 37th AMOP Technical Seminar on Environmental Contamination and Response (pp. 265–275). Environment Canada Ottawa, ON; 2014 [Google Scholar]
6.Gulka J, Jenkins E, Maynard LD, Montevecchi WA, Regular PM, Davoren GK. Inter-colony foraging dynamics and breeding success relate to prey availability in a pursuit-diving seabird. Mar Ecol Prog Ser. 2020; 651:183–198. 10.3354/meps13463 [DOI] [Google Scholar]
7.Montevecchi WA, Regular PM, Rail J-F, Power K, Mooney C, d’Entremont KJN et al. Ocean heat wave induces breeding failure at the southern breeding limit of the Northern Gannet Morus bassanus. Mar Ornithol. 2021; 49: 71–78. [Google Scholar]
8.Pelletier D, Guillemette M. Times and partners are a-changin’: Relationships between declining food abundance, breeding success, and divorce in a monogamous seabird species. Peer J. 2022; 10:e13073 doi: 10.7717/peerj.13073 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.d’Entremont KJN, Guzzwell LM, Wilhelm SI, Friesen VL, Davoren GK, Walsh CJ, et al. Northern Gannets (Morus bassanus) breeding at their southern limit struggle with prey shortages as a result of warming waters. ICES J Mar Sci. 2022. a; 79 (1): 50–60. 10.1093/icesjms/fsab240 [DOI] [Google Scholar]
10.Montevecchi WA. Interactions between fisheries and seabirds: Prey modification, discarding and bycatch. In L Youngand E Vander Werf(Editors). Conservation of Marine Birds. Academic Press, London U.K; 2023. [Google Scholar]
11.Lieske DJ, McFarlane Tranquilla L, Ronconi RA, Abbott S. Synthesizing expert opinion to assess the at-sea risks to seabirds in the western North Atlantic. Biol Conserv. 2019; 233: 41−50 10.1016/j.biocon.2019.02.026 [DOI] [Google Scholar]
12.Lieske DJ, McFarlane Tranquilla L, Ronconi RA, Abbott S. ‘Seas of risk’: assessing the threats to colonial nesting seabirds in Eastern Canada. Mar Policy. 2020; 115:103863 10.1016/j.marpol.2020.103863 [DOI] [Google Scholar]
13.Montevecchi WA, Lamarre J, Rouxel Y, Montevecchi M, Blackmore RJ, Bourne C, et al. High-contrast banners designed to deter seabirds from gillnets reduce target fish catch. Mar Ornithol. 2023; 51: 115–123. [Google Scholar]
14.Plourde S, Grégoire F, Lehoux C, Galbraith PS, Castonguay M, Ringuette M. Effect of environmental variability on body condition and recruitment success of Atlantic Mackerel (Scomber scombrus L.) in the Gulf of St. Lawrence. Fish Oceanogr. 2014; 24: 347–363 [Google Scholar]
15.Smith A, Van Beveren E, Girard L, Boudreau M, Brosset P, Castonguay M, et al. Atlantic mackerel (Scomber scombrus L.) in NAFO Subareas 3 and 4 in 2018. Canadian Science Advisory Secretariat (CSAS) Research Document 2020/013 Quebec Region; 2020. [Google Scholar]
16.DFO. Assessment of the southern Gulf of St. Lawrence (NAFO division 4T-4VN) spring and fall spawner components of Atlantic herring (Clupea harengus) with advice for the 2020 and 2021 fisheries. Canadian Science Advisory Secretariat Gulf Region Science Advisory Report 2020/029; 2020.
17.Buren A. D., Murphy H. M., Adamack A. T., Davoren G. K., Koen-Alonso M., Montevecchi W. A., et al. The collapse and continued low productivity of a keystone forage fish species. Mar. Ecol. Prog. Ser. 2019; 616: 155–170. doi: 10.3354/meps12924 [DOI] [Google Scholar]
18.Montevecchi WA. Binary dietary responses of Northern Gannets (Sula bassana) indicate changing food web and oceanographic conditions. Mar Ecol Prog Ser. 2007; 352: 213–220. [Google Scholar]
19.Garthe S, Montevecchi WA, Davoren GK. Inter-annual changes in prey fields trigger different foraging tactics in a large marine predator. Limnol Oceanogr. 2011; 56: 802–812 [Google Scholar]
20.d’Entremont K.J.N., Davoren G.K., Walsh C.J., Wilhelm S.I., Montevecchi W.A. Intra- and inter-annual shifts in foraging tactics by parental Northern Gannets (Morus bassanus) in response to changing prey fields. Mar Ecol Prog Ser. 2022. b; 698: 155–170. 10.3354/meps14164 [DOI] [Google Scholar]
21.Guillemette M, Grégoire F, Bouillet D, Rail J-F, Bolduc F, Caron A, et al. Breeding failure of seabirds in relation to fish depletion: Is there one universal threshold of food abundance? Mar Ecol Prog Ser. 2018; 587:235–245 [Google Scholar]
22.Garthe S, Benvenuti S, Montevecchi WA. Pursuit plunging by Northern Gannets (Sula bassana) feeding on capelin (Mallotus villosus). Proc R Soc B. 2000; 267: 1717–1722 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Garthe S, Guse N, Montevecchi WA, Rail J-F, Grégoire F. The daily catch: Flight altitude and diving behavior of northern gannets feeding on Atlantic mackerel. J Sea Res. 2014; 85: 456–462. [Google Scholar]
24.Raine AF, Gjerdrum C, Pratte I, Madeiros J, Felis JJ, Adams J. Marine distribution and foraging habitat highlight potential threats at sea for the Endangered Bermuda petrel Pterodroma cahow. Endang Species Res. 2021; 45:337–356. 10.3354/esr01139 [DOI] [Google Scholar]
25.Häkkinen H, Petrovan SO, Sutherland WJ, & Pettorelli N. Terrestrial or marine species distribution model: Why not both? A case study with seabirds. Ecol Evol. 2021; 11, 16634–16646. doi: 10.1002/ece3.8272 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Skov H, Humphreys E, Garthe S, Geitner K, Grémillet D, Hamer KC, et al. Application of habitat suitability modelling to tracking data of marine animals as a means of analyzing their feeding habitats. Ecol Modell. 2008; 212 (3–4): 504–512 [Google Scholar]
27.Chardine JW, Rail J-F, Wilhelm S. Population dynamics of Northern Gannets in North America, 1984–2009. J Field Ornithol. 2013; 84(2), 187–192. http://www.jstor.org/stable/24617968 [Google Scholar]
28.Mowbray TB. Northern Gannet (Morus bassanus), version 1.0. In Birds of the World (S. M. Billerman, Editor). Cornell Lab of Ornithology, Ithaca, NY, USA; 2020. 10.2173/bow.norgan.01 [DOI] [Google Scholar]
29.Geen GR, Robinson RA, Baillie SR. Effects of tracking devices on individual birds—a review of the evidence. J Avian Biol. 2019; 50: doi: 10.1111/jav.01823 [DOI] [Google Scholar]
30.R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing. 2021; Vienna. [Google Scholar]
31.Luque SP. Diving behaviour analysis in R. R News. 2007; 7: 8–14. [Google Scholar]
32.Beal M, Oppel S, Handley J, Pearmain EJ, Morera-Pujol V, Carneiro APB, et al. track2KBA: An R package for identifying important sites for biodiversity from tracking data. Meth Ecol Evol. 2021;12:2372–2378. doi: 10.1111/2041-210X.13713 [DOI] [Google Scholar]
33.Carscadden JE, Frank KT, Leggett WC. Ecosystem changes and the effects on capelin (Mallotus villosus), a major forage species. Can J Fish Aquat Sci. 2001; 58:73–85. [Google Scholar]
34.Matches Hipfner J. and mismatches: ocean climate, prey phenology and breeding success in a zooplanktivorous seabird. Mar Ecol Prog Ser. 2008; 368:295–304. [Google Scholar]
35.Buren AD, Koen-Alonso M, Pepin P, Mowbray F, Nakashima B, Stenson G, et al. Bottom-up regulation of capelin, a keystone forage species. PLoS One. 2014; 9:1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Goyert HF. Relationship among prey availability, habitat, and the foraging behavior, distribution, and abundance of common terns Sterna hirundo and roseate terns S. dougallii. Mar Ecol Prog Ser. 2014; 506: 291–302. [Google Scholar]
37.Elliott KH, Woo K, Gaston AJ, Benvenuti S, Dall’Antonia L, Davoren GK. Seabird foraging behaviour indicates prey type. Mar Ecol Prog Ser. 2008; 354:289–303. [Google Scholar]
38.Pebesma EJ RS Bivand. Classes and methods for spatial data in R. R News 2005; 5(2), https://cran.r-project.org/doc/Rnews/. [Google Scholar]
39.Aarts G, MacKenzie M, McConnell B, Fedak M, Matthiopoulos J. Estimating space-use and habitat preference from wildlife telemetry data. Ecography. 2008; 31: 140–160. 10.1111/j.2007.0906-7590.05236.x [DOI] [Google Scholar]
40.Hijmans RJ, van Etten J. raster: Geographic analysis and modeling with raster data. R package version 20–12; 2012. https://cran.r-project.org/web/packages/raster/index.html [Google Scholar]
41.Baylis AMM, Tierney M, Orben RA, Warwick-Evans V, Wakefield E, Grecian WJ, et al. Important At-Sea Areas of Colonial Breeding Marine Predators on the Southern Patagonian Shelf. Sci Rep 9, 8517 (2019). doi: 10.1038/s41598-019-44695-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Warwick-Evans V, Ratcliffe N, Lowther AD, Manco F, Ireland L, Clewlow HL, et al. Using habitat models for chinstrap penguins Pygoscelis antarctica to advise krill fisheries management during the penguin breeding season. Divers Distrib. 2018; 1–16, 1756–1771, 10.1111/ddi.12817 [DOI] [Google Scholar]
43.Wood SN. mgcv: Mixed GAM computation vehicle with automatic smoothness estimation. R package version 1.8–38; 2021. https://cran.r-project.org/web/packages/mgcv/mgcv.pdf [Google Scholar]
44.Barton K. MuMIn. Multi-Model Inference. R package version 1.47.5; 2023. https://CRAN.R-project.org/package=MuMIn
45.Grémillet D, Pichegru L, Kuntz G, Woakes AG, Wilkinson S, Crawford RJM, et al. A junk-food hypothesis for gannets feeding on fishery waste. Proc R Soc B. 2008; 275: 1149–1156. doi: 10.1098/rspb.2007.1763 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Regular PM, Hedd A, Montevecchi WA, Robertson GJ, Storey AE, Walsh CJ. Why timing is everything: Energetic costs and reproductive consequences of resource mismatch for a chick-rearing seabird. Ecosphere. 2014; 5 (12): 1–13. [Google Scholar]
47.Angel LP, Barker S, Berlincourt M, Tew E, Warwick-Evans V, Arnould JPY. Eating locally: Australasian gannets increase their foraging effort in a restricted range. Biology open. 2015;4(10):1298–305. doi: 10.1242/bio.013250 [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Montevecchi WA, Gerrow K, Buren AD, Davoren GK, Lewis KP, Montevecchi MW, et al. Pursuit-diving seabird endures regime shift involving a three-decade decline in forage fish mass and abundance. Mar Ecol Prog Ser. 2019; 627: 171–178. [Google Scholar]
49.Lescure L, Gulka J, Davoren GK. Increased foraging effort and reduced chick condition of razorbills under lower prey biomass in coastal Newfoundland, Canada. Mar Ecol Prog Ser. 2023; 709, 109–123. 10.3354/meps14286 [DOI] [Google Scholar]
50.Montevecchi WA, Ricklefs RE, Kirkham IR, Gabaldon D. Growth energetics of nestling Northern Gannets (Sula Bassanus). Auk. 1984; 101: 334–341. [Google Scholar]
51.Davoren GK. Divergent use of spawning habitat by male capelin (Mallotus villosus) in a warm and cold year. Beh Ecol. 2013; 24(1): 152–161 [Google Scholar]
52.Crook KA, Maxner E, Davoren GK. Temperature-based spawning habitat selection by capelin (Mallotus villosus) in Newfoundland. ICES J Mar Sci. 2017; 74(6): 1622–1629 [Google Scholar]
53.Penton PM, Davoren GK. Physical characteristics of persistent deep-water spawning sites of capelin: Importance for delimiting critical marine habitats. Mar Biol Res. 2012; 8: 778–783. [Google Scholar]
54.Bliss LM, Dawe N, Carruthers EH, Murphy HM, Davoren GK. Using fishers’ knowledge to determine the spatial extent of deep-water spawning of capelin (Mallotus villosus) in Newfoundland, Canada. Front Mar Sci. 2023; 9 doi: 10.3389/fmars.2022.1061689 [DOI] [Google Scholar]
55.Piatt JF. The aggregative response of common murres and Atlantic puffins to their prey. Stud Avian Biol. 1990; 14:36–51. [Google Scholar]
56.Carscadden JE, Montevecchi WA, Davoren GK, Nakashima BS. Trophic relationships among capelin (Mallotus villosus) and seabirds in a changing ecosystem. ICES J Mar Sci. 2002; 59: 1027–1033. [Google Scholar]
57.Link JS, Bogstad B, Sparholt H, Lilly GR. Trophic role of Atlantic cod in the ecosystem. Fish Fish. 2009; 10 (1): 58–87. [Google Scholar]
58.Dudley SFJ, Field JG, Shelton PA. Distribution and abundance of eggs, larvae and early juveniles of saury Scomberesox saurus scombroides (Richardson) off the south-western Cape, South Africa, 1977/78. S Afr J Mar Sci. 1985; 3: 229–237 [Google Scholar]
59.Olafsdottir AH, Utne KR, Jacobsen JA, Jansen T, Óskarsson GJ, Nøttestad L, et al. Geographical expansion of Northeast Atlantic mackerel (Scomber scombrus) in the Nordic Seas from 2007 to 2016 was primarily driven by stock size and constrained by low temperatures. Deep-Sea Res Part II. 2019; 159: 152–168. [Google Scholar]
60.Leim AH, Scott WB. Fishes of the Atlantic coast of Canada. Bull Fish Res Board Can No. 155; 1966. [Google Scholar]
61.Moores JA, Winters GH, Parsons LS. Migrations and biological characteristics of Atlantic mackerel (Scomber scombrus) occurring in Newfoundland waters. J Fish Res Board Can. 1975; 32: 1347–1357 [Google Scholar]
62.Brennan CE, Blanchard H, Fennel K. Putting temperature and oxygen thresholds of marine animals in context of environmental change: A regional perspective for the Scotian Shelf and Gulf of St. Lawrence. PLoS ONE. 2016; 11(12): e0167411. doi: 10.1371/journal.pone.0167411 [DOI] [PMC free article] [PubMed] [Google Scholar]
63.Carscadden JE, Gjøsæter H, Vilhjálmsson H. A comparison of recent changes in distribution of capelin (Mallotus villosus) in the Barents Sea, around Iceland and in the Northwest Atlantic. Prog Ocean. 2013; 114: 64–83 10.1016/j.pocean.2013.05.005 [DOI] [Google Scholar]
64.Montevecchi WA, Benvenuti S, Garthe S, Davoren GK, Fifield DA. Flexible tactics of an opportunistic seabird preying on capelin and salmon. Mar Ecol Prog Ser. 2009; 385: 295–306. doi: dx.doi.org/10.3354/meps08006 [Google Scholar]
65.Hedd A, Regular PM, Wilhelm SI, Rail J-F, Drolet B, Fowler M et al. Characterization of seabird bycatch in eastern Canadian waters, 1998–2011, assessed from onboard fisheries observer data. Aquat Conserv. 2015; 26(3), 530–548. doi: 10.1002/aqc.2551 [DOI] [Google Scholar]
66.Oliver ECJ, Burrows MT, Donat MG, Sen Gupta A, Alexander LV, Perkins-Kirkpatrick SE et al. Projected marine heatwaves in the 21st century and the potential for ecological impact. Front Mar Sci. 2019; 10.3389/fmars.2019.00734 [DOI] [Google Scholar]
67.Mbaye B, Doniol-Valcroze T, Brosset P, Castonguay M, Van Beveren E, Smith A, et al. Modelling Atlantic Mackerel spawning habitat suitability and its future distribution in the north-west Atlantic. Fish Oceanogr. 2020; 29:84–99 [Google Scholar]
68.Walsh HJ, Richardson DE, Marancik KE, Hare JA. Long-term changes in the distributions of larval and adult fish in the northeast US shelf ecosystem. PLoS one. 2015; 10(9), e0137382. 10.1371/journal.pone.0137382 [DOI] [PMC free article] [PubMed] [Google Scholar]
69.Nye JA, Link JS, Hare JA, Overholtz WJ. Changing spatial distribution of fish stocks in relation to climate and population size on the Northeast United States continental shelf. Mar Ecol Prog Ser. 2009; 393, 111–129. 10.3354/meps08220 [DOI] [Google Scholar]
70.Sydeman WJ, Schoeman DS, Thompson SA, Hoover BA, Garcia-Reyes M, Daunt F, et al. Hemispheric asymmetry in ocean change and the productivity of ecosystem sentinels. Science. 2021; 372 (6545): 980–983. doi: 10.1126/science.abf1772 [DOI] [PubMed] [Google Scholar]
71.Andrews S, Leroux SJ, Fortin M-J. Modelling the spatial–temporal distributions and associated determining factors of a keystone pelagic fish. ICES J Mar Sci. 2020; 77 (7–8): 2776–2789. [Google Scholar]
72.Pettex E, Lorentsen S-H, Grémillet D, Gimenez O, Barrett RT, Pons J-P, et al. Multi-scale foraging variability in Northern Gannet (Morus Bassanus) fuels potential foraging plasticity. Mar Biol. 2012; 159 (12): 2743–56. 10.1007/s00227-012-2035-1. [DOI] [Google Scholar]
73.Melvin GD, Stephenson RL, Power MJ. Oscillating reproductive strategies of herring in the western Atlantic in response to changing environmental conditions. ICES J Mar Sci. 2009; 66 (8): 1784–1792. [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0288650.r001

Decision Letter 0

Vitor Hugo Rodrigues Paiva

28 Feb 2023

PONE-D-23-00624Quantifying space-use of parental Northern Gannets (Morus bassanus) in pursuit of different prey typesPLOS ONE

Dear Dr. d'Entremont,

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.

Please submit your revised manuscript by Apr 14 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Vitor Hugo Rodrigues Paiva, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

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

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

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for stating the following in the Acknowledgments Section of your manuscript:

"We must thank several people for their help with this study. The Cape St. Mary’s Ecological Reserve staff were invaluable, providing accommodations and logistical support over the years. We thank staff member Chris Mooney in particular, for his assistance with tagging gannets in the field. We also thank the Newfoundland and Labrador Parks and Natural Areas Division for allowing us to conduct our research at the Cape St. Mary’s Ecological Reserve. This study was

funded by the Natural Sciences and Engineering Research Council and an Ocean and Freshwater Contribution Program grant from Fisheries and Oceans Canada to WAM. Additional funding was provided by NSERC (WAM) and Memorial University of Newfoundland and Labrador. Gannets were handled under the Canadian Wildlife Service permit 10332K and Memorial University of Newfoundland and Labrador animal care permit 19-01-WM."

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

"WAM received grant #2018-06872 from the Natural Sciences and Engineering Research Council of Canada Discovery Grant program. The funder played no role in study design or the publication process. URL: https://www.nserc-crsng.gc.ca/professors-professeurs/grants-subs/dgigp-psigp_eng.asp

WAM received the sub-grant # 57177 to Memorial University of Newfoundland and Labrador from the Fisheries and Oceans Canada Coastal Environmental Baseline Program. The funder played no role in study design or the publication process. URL: " ext-link-type="uri" xlink:type="simple">https://www.dfo-mpo.gc.ca/science/partnerships-partenariats/research-recherche/cebp-pdecr/index-eng.html"

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

3. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability.

"Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. Any potentially identifying patient information must be fully anonymized.

Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access.

We will update your Data Availability statement to reflect the information you provide in your cover letter.

4. Please include your full ethics statement in the ‘Methods’ section of your manuscript file. In your statement, please include the full name of the IRB or ethics committee who approved or waived your study, as well as whether or not you obtained informed written or verbal consent. If consent was waived for your study, please include this information in your statement as well.

5. We note that Figure 1 in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright.

We require you to either (a) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (b) remove the figures from your submission:

a. You may seek permission from the original copyright holder of Figure 1 to publish the content specifically under the CC BY 4.0 license.

We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:

“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”

Please upload the completed Content Permission Form or other proof of granted permissions as an "Other" file with your submission.

In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].”

b. If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.

The following resources for replacing copyrighted map figures may be helpful:

USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/

The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/

Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html

NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/

Landsat: http://landsat.visibleearth.nasa.gov/

USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/#

Natural Earth (public domain): http://www.naturalearthdata.com/

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

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

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

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

Reviewer #1: N/A

Reviewer #2: No

Reviewer #3: Yes

Reviewer #4: Yes

**********

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

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

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: No

**********

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

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

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

Reviewer #4: Yes

**********

5. Review Comments to the Author

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

Reviewer #1: Authors,

I enjoyed reading this study about how habitat use models differ based on which behaviour (in this case dive type) is used as a response variable. I think the premise is highly worthwhile, and using the behaviour of gannets to infer the availability of different forage fishes based on foraging mode is really interesting. However, I have some concerns about the methodology and surrounding narrative that I believe need to be addressed. See below for specific comments.

L44-46: This sentence is too complex, maybe split into two, with the latter explaining the depleted forage fish stocks.

L62: Maybe “slowing” instead of “asymptotic” might read a little easier.

L101-104: This section should be represented as a table of deployments.

L120-122: This is a bit confusing: What happens if a bird dives for 10s and has a bottom time of 3s? Could just go by Cox et al. (2016) and solely use bottom time thresholds to separate dive types?

L142-143: I agree that the two types of dive profiles may reflect availability of different prey types, however, this then raises the question of why V-shaped dives were split into early and late? U-shaped dives also occur at almost all times? You mention earlier that U-shaped dives may influence V-shaped dives, but I’m not sure this is really logical. You might need to stick to two different responses (which I would personally opt for), early and late for both dive types, or find stronger justification for the three current responses.

L152-155: I don’t agree with the use of pseudo-absences, when perfectly good absences exist. Why not use locations with no associated dives as the absence in your response? Because dive behaviour is your response, the presence or absence of that behaviour along the track should form your response variable, rather than randomly generated pseudo-absences.

L157: What’s the temporal resolution of SST? Is it MODIS data, and if so, is it level 3 or level 4 type data?

L158: Why not latitude? It may be colinear with SST, but probably worth considering in any case. It would be good to include a 2D lat/lon spline.

L167: Whole model selection using MuMIn::dredge or similar would be much better if feasible.

L170-171: The mgcv::concurvity function is a neat way of looking for multicollinearity within your model. This way is okay too, but the other would be better.

L180-181: If V-shaped dives are being split into early and late, surely they should only be predicted over the time span they are associated with? Please clarify if this is the case or rectify if not.

L188: Maybe association is incorrect here? “Temporal variation in dive types” instead?

L202-204: This spatial variation between early and late V-shaped dives could potentially be good justification for splitting into two responses. However, not sure the pattern is strong enough.

Table 2: Models with nothing but “distance to colony” returning an AUC of 0.9 is a case in point for why pseudo-absences are a poor substitute for genuine absences when trying to determine environmental drivers of behaviour, and not solely distribution. This is evident when adding other environmental variables has a negligible impact on model AUC.

L242-257 figure 5: Model covariates appear a little bit overfit in some cases. In general, you should discuss the model specification in a bit more detail. Are you using cubic or thin-plate splines? Is any shrinkage applied? Shrinkage would be a tidy way to reduce instances of overfitting and return the simplest effective spline. Perhaps transforming heavily skewed variables, such as slope and bathymetry, could be beneficial too, as this might reduce the huge uncertainty around extreme values.

Figure 5: All the bathymetry plots have positive values (assumably on land) with a very high likelihood of dives occurring. Might need to look at how the data are prepared, figure out why this happening, and fix it.

Figure 5: I would also highly recommend the mgcViz package for plotting model outputs from mgcv.

L275-283: Really interesting links here between dive type and prior expectation of the availability of prey. Seems that if a prey type is lacking, they increase the associate dive effort rather than concentrating on other dive types/prey species. Could potentially expand into temporal changes in dietary requirements and why this might prevent plasticity, or might be too complex a topic to just touch on. Just a thought.

L306-308, L321, L370-371: These sentences contradict each other about the temperature preferences of mackerel, or at least seem to?

L346-350: It could be good here to foreshadow the extra energy that gannets may have to expend to target desired prey species? You have a basis for this, given the additional effort in U-shaped dives in the year when capelin was less abundant, and increases in V-shaped dive effort in years with fewer saury and mackerel around. Otherwise, this paragraph seems a bit light and vague for quite an important and relevant point.

L381-387: The conclusion as a whole does not reflect the research that has gone into this paper. Please rewrite, with a focus on the actual findings instead of projecting how space-use will change, which you haven’t really shown.

I hope you find these comments useful.

All the best

Reviewer #2: First of all, I want to congratulate the authors for the great work performed to study the habitat use and spatial distribution of the northern gannet (Morus bassanus) by taking into account their two major diving tactics. Overall, the authors put a considerable amount of effort for habitat suitability modeling exercises, quite complex analyses, and I commend them for this.

Nevertheless, I have a major concern about the modeling approach and some other minor/medium questions that should be taken into consideration before the final approval.

I have added my comments in the word version using track changes, pointing some typographical or grammatical errors, but I provide here the main issues:

INTRODUCTION:

L117: I feel that in this paragraph (L117-L128) should be included more information about the use of habitat suitability models in seabirds. Perhaps authors could indicate some studies where they were successfully applied, even in gannets or other Sulidae species.

L130: Perhaps the ideas in this sentence are in the reverse order. The dive profiles could change when the foraging areas are different, due to the foraging habitat conditions (depth, slope, etc) and to the prey inhabiting these different habitats.

METHODS:

L215: I am concerned about the computation for the estimation of the smoothing parameter (h). Href is a low-conservative method, so possibly we can be dealing with a considerable error that will affect kernel density estimation. I recommend the use of more recent methodologies, such as those in Lascelles et al., 2016 that provide a h value more adapted to your own data.

Lascelles BG, Taylor PR, Miller MGR, Dias MP, Oppel S, Torres L, Hedd A, Le Corre M, Phillips RA, Shaffer SA, Weimerskirch H, Small C (2016) Applying global criteria to tracking data to define important areas for marine conservation. Divers Distrib 22:422–431. doi: 10.1111/ddi.12411

L241-267: Once the individuals performed several dives, I recommend the use of individual as a random factor to avoid pseudo-replication issues. I mean, perhaps an additive mixed model might be more adequate to analyze the data.

Additionally, there are some other gaps that should be clarified in this section:

- Please refer how the pseudo-absences were generated prior modeling exercises.

- It seems that the “year” was not included in the modeling exercises. Since part of this manuscript was focused on the inter-annual variability on the space-use, the “year” must be included as a covariate.

- Have you used smoothed terms in GAM? Perhaps by smoothing SST may be a good way to deal with possible non-linear. distribution of the variable.

- Finally, if smooth terms were used please refer what was the number of thin plate regression splines.

- Besides correlation among the covariates, test for multicollinearity should be evaluated (for instance using the variation inflation factor, VIF), and concurvity if smoothed terms were used.

Two good guides for analyzing ecological data:

Zuur AF, Ieno EN, Smith GM (2007) Analysing ecological data. Springer, New York

Morlini I (2006) On multicollinearity and concurvity in some nonlinear multivariate models. Stat Methods Appl 15:3–26. https://doi.org/10. 1007/s10260-006-0005-9

- Have you used AIC or the ΔAICc? The more correct is using the ΔAICc (the difference in AICc between a given model and the model with the smallest AICc). Nevertheless, I suggest the use of AIC corrected for small sample sizes (AICc), because you were working with a low number of individuals.

Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach. Springer- Verlag, New York

Additive models are quite useful when working with non-linear variables, such as environmental predictors, however, some assumptions must be fulfilled before model runs.

A good book/guide for the mixed models:

Zuur AF, Ieno EN,WalkerN, Saveliev A a., SmithGM (2009) Mixed effects models and extensions in ecology with R. Springer, New York

RESULTS:

L367: In fact, the threshold is not that clear for me, according to Figure 5a. I would rather say that the U-shaped dives probability of occurrence decreased beyond 150 km from the colony, rather than 200 km.

L368: On the other hand, the early V-shaped dives seemed to decrease beyond 200 km rather than 150 km, while the late V-shaped dives have a strong negative relationship with distance to the colony; at least until 200 km.

L370-371: This was more evident for U-shaped dives than for late V-shaped dives. The effect that authors highlight here is not that clear to me. I believe that may be some real effect on U-shaped dives, however, for V-shaped dives the effect is visually weak.

DISCUSSION:

After reading the discussion it feels like some studies may have been left behind. I recommend the inclusion of concrete examples in northern gannets or in other gannet species or even boobies. Despite being different species, they have similar foraging and feeding behavior tactics when foraging, thus it can improve substantially the discussion of your results. Moreover, according to the results, it seems quite important the habitat characteristics (e.g., slope) on determining the diving behavior, however, some studies reported that oceanographic conditions can be preponderant as well.

Some possible suggestions:

Cox SL, Miller PI, Embling CB, Scales KL, Bicknell AWJ, Hosegood PJ, Morgan G, Ingram SN, Votier SC. 2016 Seabird diving behaviour reveals the functional significance of shelf-sea fronts as foraging hotspots. R. Soc. open sci. 3: 160317. http://dx.doi.org/10.1098/rsos.160317

Cleasby IR, Wakefield ED, Bodey TW, Davies RD, Patrick SC, Newton J, Votier SC, Bearhop S, Hamer KC (2015) Sexual segregation in a wide-ranging marine predator is a consequence of habitat selection. Mar Ecol Prog Ser 518:1–12. https:// doi. org/ 10. 3354/ meps1 1112

L399: "We found the number of U-shaped dives was greater than expected in 2020." Please avoid this type of sentences in the discussion. This is already stated in the results.

L639-640: Another important variable that might interest the authors might be the distance travelled between two dives. I am just wondering that if adults dive more frequently and used the same diving tactic can be a good indicator of the distribution of prey among and within years. I do not know if your small database (10, 7, and 8 individuals each year) would allow to test this, however it can be very informative. It may help to explain the inter-annual variability in the spatial use of habitat by gannets.

Please check the track changes in the word file. I added some minor comments there and other suggestions that I hope have improved the quality of the manuscript.

Reviewer #3: Thanks to the authors for an interesting and well-written study. The study investigates suitable habitats of forage fishes inferred from the different dive profiles performed by chick-rearing gannets. It identifies important gannet foraging areas and several of their key environmental features using animal-borne biologging data collected over multiple years. The authors propose that a subset of these areas be considered as critical areas of multi-species conservation concern that should be prioritized in protection efforts. In general, the objectives of the study as set out by the authors are achieved and I have no major concerns. Suggestions for improvement are given below.

Please provide higher resolution versions of all figures, especially 3 and 4, these are largely illegible due to blurriness. Consider in figures 3 and 4 to differentiate between land and isobath lines more clearly, for example by using darker grey for land. In addition in figure 3, some panels seem to cut off the southern edge of the distributions.

Line 20: No need to capitalize “Kernel Density”, change to “kernel density”.

Line 33: Replace “incidence on” with “consequences for”.

Line 46: Consider listing one reference per effect (i.e. one for overexploitation by fisheries, one each for climate-induced shifts) to avoid over-referencing.

Line 82: Unclear why “cold-blooded” is relevant here, suggest either deleting or inserting clarification earlier (e.g. at line 77).

Line 90: d’Entremont et al. 2022 a, b or both?

Line 114-115: Assuming devices set to record GPS locations and dive depth. Also please clarify what the range of the base station was.

Line 117: Somewhere at beginning of data processing/analysis please state what software was used (R and R Studio?), and which version.

Line 123-125: Please include a justification (i.e. a reference) for foraging location annotation based on within 30 minute interval between GPS locations (assuming this has to do with transit versus foraging speeds typical for gannets?).

Line 158: No need to redo any analysis, but curious as to why latitude was not included as a covariate.

Line 161-163: Please include information on what the splines were for each covariate (i.e. thin plate regression splines?). Out of interest, were any interaction terms explored for addition to the models, i.e. depth: SST or depth:slope?). Inclusion of interaction terms might help improve deviance explained especially of the V-shaped dive model?

Line 165-170: Please include a reference for the AUC and AIC methods.

Line 188-189: Are the statistical tests of this paragraph described in the methods? If test is among years then surely there should be at least 3 test statistics, i.e. 2019 vs 2020, 2019 vs 2021, 2020 vs 2021? Please also report degrees of freedom.

Line 299: Without going out and testing whether locations of hotspots of U shaped dives contain spawning capelin, or checking corresponding landings by gannets during the early chick-rearing period (i.e. similar to Montevecchi 2007), this is still conjecture, but it is a testable hypothesis for future studies.

Line 343-344: How do you know they are not going for cod during early chick-rearing?

Line 362-364: However, as gannets have been shown to have foraging plasticity, see for example Pettex et al. 2012., and are able to switch over the breeding season i.e. d’Entremont 2022b, it becomes a question of whether the gannets are able to compensate for changing capelin distributions…which is cause for continued monitoring of this colony and situation.

References

Pettex, Emeline, Svein Håkon Lorentsen, David Grémillet, Olivier Gimenez, Robert T. Barrett, Jean Baptiste Pons, Céline Le Bohec, and Francesco Bonadonna. 2012. “Multi-Scale Foraging Variability in Northern Gannet (Morus Bassanus) Fuels Potential Foraging Plasticity.” Marine Biology 159 (12): 2743–56. https://doi.org/10.1007/s00227-012-2035-1.

Reviewer #4: Title: Quantifying space-use of parental Northern Gannets (Morus bassanus) in pursuit of different prey types

This study aimed to assess the distribution and abundance of key forage fishes (namely 1 - capelin, and 2 – other pelagic forage species) in the western North Atlantic by investigating the foraging behaviour and space-use of northern gannets. The study deployed 25 GPS/Time-depth recorder devices on breeding Northern Gannets at Cape St. Mary’s, Newfoundland from 2019 to 2021. Gannets foraging in these waters have been shown to perform two distinctly shaped dives characteristic of the prey they are targeting. U-shaped dives are associated with capture attempts on capelin, while V-shaped dives are linked to other pelagic prey species. The authors used kernel density estimates and habitat suitability models to predict the spatiotemporal distribution of these two different dive types. They created three different habitat suitability models, one for U-shaped dives and two models for V-shaped dives, separated into early and late chick-rearing. The results of the study showed that space-use by gannets varied both within and between years, depending on environmental conditions and the prey they are exploiting. Both dive types generally occurred within shallow coastal waters and cool temperatures (11-15oC), although some V-shaped dives were also performed in waters of ~18oC, coincident with warmer prey species such as Atlantic saury. The authors suggest that regions defined as suitable for U-shaped dives are likely to represent consistent capelin spawning habitat. Given capelin’s importance for many predator species, the authors indicate that these areas, identified as important for spawning capelin, may also be of multi-species conservation concern.

I found this paper to be generally well written, the objectives clearly laid out and the methodology sound. I particularly enjoyed reading the approach for using dive types as a proxy for the distribution of different prey groups. This study makes a nice contribution to the toolkit of approaches for remotely monitoring the state of marine ecosystems. I have made largely minor comments throughout, which I hope the authors will find beneficial.

General comments:

1. This paper considers the distribution of U-shaped and V-shaped dives as a function of environmental conditions and largely ignores the issue of dietary preference. I would like to see some discussion around the effect of dietary preference in determining whether birds would be conducting proportionally more U or V-shaped dives. It seems to me that the study assumes that the preponderance of each dive (prey) type is driven entirely by their availability, without considering a preference for one prey type over another. So, if capelin were the preferred prey, would we not expect the preponderance of U-shaped dives to be nonlinearly related to its availability, remaining the dominant dive type until a threshold after which these dives would be rapidly replaced by V-shaped dives? I think this would be worth some thought, because if there is a level of preference, then clearly the probability of one dive type (V-shaped) occurring is dependent on the probability of the other (U-shaped) not occurring, no? And if there is a confounding effect of preference, this could have implications for how we use such methods to track changes in prey abundance and distribution.

2. The language shifts between present and past tense in a few places. Try to keep tenses consistent throughout.

L. 62. “as asymptomatic population growth”. This comes across as if the colony grew despite years of low productivity. I am not sure if this is what you intended, but either way I think this could be better worded.

L. 70. remove “Clupea harengus” – already defined in L. 55.

L. 71. Change “Parental” to breeding, and remove the later “breeding”

L. 71. Either refer to Newfoundland in full throughout, or define NL with the first reference to Newfoundland.

L. 80. …we aimed…

L. 82. Just refer to prey. To me, the reference to cold-blooded prey implies that they also eat warm-blooded prey, but that you didn’t consider these in this study.

L. 82. …for a better understanding…

L. 102-103. …Uria 300 GPS loggers with Temperature-Depth Recorders…

L. 110. Is the variance metric standard deviation?

L. 112. How do you define a diving bout?

L. 120. It would be helpful to have a figure giving a representative example of a U- and V-shaped dive. This could either be in the main text or in the supplement.

L. 123. This sentence is confusingly worded. Was a dive bout classified as the period of time over which the interval between consecutive dives remained less than 30 min?

L. 126-130. This section could be better explained. It is not altogether clear to me why the authors chose to split V-shaped dives into an early and late season. I think the nature of the influence of U-shaped dives on V-shaped dives could be better described. Would it not be better to account for early/late season effects by fitting the models with a serial autocorrelation structure on date?

L. 140-143. “…we assume that the two dive profiles reflect prey type availability or preference”. I’m not sure I follow this. In my understanding, the distribution of dive shapes would differ considerably depending on whether they represented prey availability or prey preference. For example, if capelin is preferred, you might find the preponderance of U-shaped dives remains dominant even at low capelin densities and high relative availability of other prey. Whereas, if there is no preference, the dominance of dive types would be purely a function of relative availability of their different prey. I think it would be good to at least discuss how the findings here could be influenced by this.

L. 152. This sentence may be better located earlier in the methods. i.e., when describing the fieldwork.

L. 155-160. There should be a reference somewhere to the data products used for these analyses – specifically SST.

L. 159. Were all variables extracted at their native resolution?

L. 160. Were other oceanographic variables considered (e.g. chl a)?

L. 172. It would be good to have reported the mean number of observations (dives) per day, given that predictions were conducted at a daily resolution.

L. 185. …predictions…

L. 188. “association” This could be more clearly stated. It’s not clear whether this implies that they were different or similar.

L. 231-232. Remove “which included distance to the colony, longitude, bathymetry, slope, and sea surface temperature” – this is covered off by the previous sentence.

L. 249-250. Confusingly worded sentence

L 275-276. I’m not sure I agree that an increased number of dives is indicative of decreased prey availability in the case of plunge diving species such as gannets. My understanding is that gannets locate prey from the air and thereafter initiate diving, whereas pursuit divers may undergo multiple exploratory dives to find prey (therefore having to increase dive frequency to locate prey when it is less abundant). Recent work has also found that the number of prey within a prey patch is not a predictor of foraging success (https://doi.org/10.1111/1365-2656.12455) – i.e. they don’t necessarily have to dive more frequently to have success on smaller prey patches. Therefore, I would have expected decreases in prey availability to be associated with concurrent decreases in the frequency of dives.

L. 286. “near” – perhaps towards is a better word choice?

L. 294. “This” – Together, these findings reinforce…

L. 299. “Areas deemed as highly” – Areas deemed highly…

General discussion comments

• There is considerable discussion around the loss of cold-water species (e.g. capelin) from the system and negative effects of this. I would be interested to see some speculation around a possible increased prevalence of warmer water species (e.g. saury), and their potential to (partially) compensate for the loss of colder species. I’m sure they wouldn’t be sufficient to maintain the population, but it might be an interesting discussion point.

• I am wondering if you have access to fisheries data. Given that dive shapes are being linked to different prey types, I think it would be valuable to have the predicted distribution of dives (particularly U-shaped) plotted against the distribution of fishing activity/known spawning grounds. For example, a simple comparison could be to have a kernel density estimate of U-shaped dives overlaid by a kernel density estimate of capelin fishing effort, and/or polygons of their known spawning distribution.

Figures

Fig. 5. It appears that the partial fits for bathymetry show an increase in dive probability over depths of 0 (i.e., over land). Is this just an artefact of inshore foraging close to coastal cliffs? In this case, it would be better to cap all bathymetry values 0 at 0.

**********

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: No

Reviewer #2: No

Reviewer #3: No

Reviewer #4: Yes: David Green

**********

[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.

Attachment

Submitted filename: Manuscript_dEntrremont et al.,_NOGA Habitat Suitability ms_PLOSOne.docx

Click here for additional data file.^{(106.9KB, docx)}

PLoS One. 2023 Jul 14;18(7):e0288650. doi: 10.1371/journal.pone.0288650.r002

Author response to Decision Letter 0

13 May 2023

A response letter has been uploaded to address all reviewer comments.

Attachment

Submitted filename: Response to Reviewers_PlosOne Resubmission.docx

Click here for additional data file.^{(55.7KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0288650.r003

Decision Letter 1

Vitor Hugo Rodrigues Paiva

21 Jun 2023

PONE-D-23-00624R1Quantifying inter-annual variability on the space-use of parental Northern Gannets (Morus bassanus) in pursuit of different prey typesPLOS ONE

Dear Dr. d'Entremont,

Please submit your revised manuscript by Aug 05 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Vitor Hugo Rodrigues Paiva, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

Reviewer #4: All comments have been addressed

**********

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

Reviewer #2: Yes

Reviewer #3: (No Response)

Reviewer #4: Yes

**********

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

Reviewer #2: Yes

Reviewer #3: (No Response)

Reviewer #4: Yes

**********

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

Reviewer #2: Yes

Reviewer #3: (No Response)

Reviewer #4: Yes

**********

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

Reviewer #2: Yes

Reviewer #3: (No Response)

Reviewer #4: Yes

**********

6. Review Comments to the Author

Reviewer #2: I want to congratulate the authors for the thorough revision they carried out. The manuscript is clear, with the statistical procedures and computations clearly stated and understandable. However, on reading through this revised version, I noticed a few typos or very minor grammar issues that I recommend the authors deal with before the acceptance.

I added a few comments and made my correction/suggestions in the file attached.

Reviewer #3: I would like to congratulate the authors on a thorough and well-done revision. My comments have been beyond satisfactorily addressed. Congratulations on this interesting study!

Reviewer #4: I commend the authors on this very interesting study and I appreciate their effort to address the suggestions that I provided on the previous manuscript version. Overall, I am happy with their revisions and feel that they have sufficiently addressed my concerns. I have only a few very minor additional comments (largely typographical) for them to include prior to publication, which I have outline below. Note the Line numbers refer to the tracked changes document.

- L121. …(i.e. from first entry into water until resurfacing)…

- L.146. …early and late V-shaped dives.

- L.369-373. I appreciate that the authors have included this text in response to my previous comment. However, it appears to interrupt the flow and doesn’t really add anything – so maybe better to remove. Perhaps the authors could instead consider changing the wording in L. 365. to: “Increased diving effort in pursuit-diving seabirds, including gannets…”

Also, my understanding is that, in the Angel et al. 2015 paper, the authors only found a significant difference in dive rate for male gannets and only in a single year. So, I’d suggest either changing “diving effort” to “foraging effort”, or removing the Angel et al. 2015 ref.

- L427. …those sites…

- L475. …greater energy on foraging…

- L481. …results in an earlier spring bloom of primary producers…

- L537. …with foraging habitat suitability being heavily reliant on sea surface temperature thresholds of their poikilothermic prey.

- Methods – Habitat Suitability Modelling: I agree with why it wasn’t used, but I think it would still be good to mention why chl a was not included in the analyses – i.e. it was considered, but removed due to poor spatio-temporal coverage over the study period.

**********

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

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

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

Reviewer #2: Yes: Ivo dos Santos

Reviewer #3: No

Reviewer #4: Yes: David Green

**********

Attachment

Submitted filename: Re-revised MS_dEntremont et al.,_PlosONE_TrackChanges.docx

Click here for additional data file.^{(405.6KB, docx)}

PLoS One. 2023 Jul 14;18(7):e0288650. doi: 10.1371/journal.pone.0288650.r004

Author response to Decision Letter 1

27 Jun 2023

Please refer to Reviewer Response Letter attachment.

Attachment

Submitted filename: Response to Reviewers_v2.docx

Click here for additional data file.^{(16.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0288650.r005

Decision Letter 2

Vitor Hugo Rodrigues Paiva

3 Jul 2023

Quantifying inter-annual variability on the space-use of parental Northern Gannets (Morus bassanus) in pursuit of different prey types

PONE-D-23-00624R2

Dear Dr. d'Entremont,

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

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

Kind regards,

Vitor Hugo Rodrigues Paiva, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0288650.r006

Acceptance letter

Vitor Hugo Rodrigues Paiva

6 Jul 2023

PONE-D-23-00624R2

Quantifying inter-annual variability on the space-use of parental Northern Gannets (IMorus bassanus) in pursuit of different prey types

Dear Dr. d'Entremont:

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

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

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

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

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Vitor Hugo Rodrigues Paiva

Academic Editor

PLOS ONE

Associated Data

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

Supplementary Materials

Attachment

Submitted filename: Manuscript_dEntrremont et al.,_NOGA Habitat Suitability ms_PLOSOne.docx

Click here for additional data file.^{(106.9KB, docx)}

Attachment

Submitted filename: Response to Reviewers_PlosOne Resubmission.docx

Click here for additional data file.^{(55.7KB, docx)}

Attachment

Submitted filename: Re-revised MS_dEntremont et al.,_PlosONE_TrackChanges.docx

Click here for additional data file.^{(405.6KB, docx)}

Attachment

Submitted filename: Response to Reviewers_v2.docx

Click here for additional data file.^{(16.8KB, docx)}

Data Availability Statement

[pone.0288650.ref001] 1.Halpern BS, Walbridge S, Selkoe KA, Kappel CV, Micheli F, D’Agrosa C et al., A global map of human impact on marine ecosystems. Science. 2008; 319, 948–952. doi: 10.1126/science.1149345 [DOI] [PubMed] [Google Scholar]

[pone.0288650.ref002] 2.Gjerdrum C, Ronconi RA, Turner KL, Hamer, TE. Bird strandings and bright lights at coastal and offshore industrial sites in Atlantic Canada. Avian Conserv Ecol. 2021; 16(1):22. 10.5751/ACE-01860-160122 [DOI] [Google Scholar]

[pone.0288650.ref003] 3.Wilhelm SI, Dooley SM, Corbett EP, Fitzsimmons MG, Ryan PC, Robertson GJ. Effects ofland-based light pollution on two species of burrow-nesting seabirds in Newfoundland and Labrador, Canada. Avian Conserv Ecol. 2021; 16(1):12. 10.5751/ACE-01809-160112 [DOI] [Google Scholar]

[pone.0288650.ref004] 4.Wiese FK, Robertson GJ. Assessing seabird mortality from chronic oil discharges at sea. J Wildl Manage. 2004; 68: 627–638. 10.2193/0022-541X(2004)068[0627:ASMFCO]2.0.CO;2 [DOI] [Google Scholar]

[pone.0288650.ref005] 5.Robertson GJ, Wiese FK, Ryan PC, Wilhelm SI. Updated numbers of murres and dovekies oiled in Newfoundland waters by chronic ship-source oil pollution. In Proceedings of the 37th AMOP Technical Seminar on Environmental Contamination and Response (pp. 265–275). Environment Canada Ottawa, ON; 2014 [Google Scholar]

[pone.0288650.ref006] 6.Gulka J, Jenkins E, Maynard LD, Montevecchi WA, Regular PM, Davoren GK. Inter-colony foraging dynamics and breeding success relate to prey availability in a pursuit-diving seabird. Mar Ecol Prog Ser. 2020; 651:183–198. 10.3354/meps13463 [DOI] [Google Scholar]

[pone.0288650.ref007] 7.Montevecchi WA, Regular PM, Rail J-F, Power K, Mooney C, d’Entremont KJN et al. Ocean heat wave induces breeding failure at the southern breeding limit of the Northern Gannet Morus bassanus. Mar Ornithol. 2021; 49: 71–78. [Google Scholar]

[pone.0288650.ref008] 8.Pelletier D, Guillemette M. Times and partners are a-changin’: Relationships between declining food abundance, breeding success, and divorce in a monogamous seabird species. Peer J. 2022; 10:e13073 doi: 10.7717/peerj.13073 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0288650.ref009] 9.d’Entremont KJN, Guzzwell LM, Wilhelm SI, Friesen VL, Davoren GK, Walsh CJ, et al. Northern Gannets (Morus bassanus) breeding at their southern limit struggle with prey shortages as a result of warming waters. ICES J Mar Sci. 2022. a; 79 (1): 50–60. 10.1093/icesjms/fsab240 [DOI] [Google Scholar]

[pone.0288650.ref010] 10.Montevecchi WA. Interactions between fisheries and seabirds: Prey modification, discarding and bycatch. In L Youngand E Vander Werf(Editors). Conservation of Marine Birds. Academic Press, London U.K; 2023. [Google Scholar]

[pone.0288650.ref011] 11.Lieske DJ, McFarlane Tranquilla L, Ronconi RA, Abbott S. Synthesizing expert opinion to assess the at-sea risks to seabirds in the western North Atlantic. Biol Conserv. 2019; 233: 41−50 10.1016/j.biocon.2019.02.026 [DOI] [Google Scholar]

[pone.0288650.ref012] 12.Lieske DJ, McFarlane Tranquilla L, Ronconi RA, Abbott S. ‘Seas of risk’: assessing the threats to colonial nesting seabirds in Eastern Canada. Mar Policy. 2020; 115:103863 10.1016/j.marpol.2020.103863 [DOI] [Google Scholar]

[pone.0288650.ref013] 13.Montevecchi WA, Lamarre J, Rouxel Y, Montevecchi M, Blackmore RJ, Bourne C, et al. High-contrast banners designed to deter seabirds from gillnets reduce target fish catch. Mar Ornithol. 2023; 51: 115–123. [Google Scholar]

[pone.0288650.ref014] 14.Plourde S, Grégoire F, Lehoux C, Galbraith PS, Castonguay M, Ringuette M. Effect of environmental variability on body condition and recruitment success of Atlantic Mackerel (Scomber scombrus L.) in the Gulf of St. Lawrence. Fish Oceanogr. 2014; 24: 347–363 [Google Scholar]

[pone.0288650.ref015] 15.Smith A, Van Beveren E, Girard L, Boudreau M, Brosset P, Castonguay M, et al. Atlantic mackerel (Scomber scombrus L.) in NAFO Subareas 3 and 4 in 2018. Canadian Science Advisory Secretariat (CSAS) Research Document 2020/013 Quebec Region; 2020. [Google Scholar]

[pone.0288650.ref016] 16.DFO. Assessment of the southern Gulf of St. Lawrence (NAFO division 4T-4VN) spring and fall spawner components of Atlantic herring (Clupea harengus) with advice for the 2020 and 2021 fisheries. Canadian Science Advisory Secretariat Gulf Region Science Advisory Report 2020/029; 2020.

[pone.0288650.ref017] 17.Buren A. D., Murphy H. M., Adamack A. T., Davoren G. K., Koen-Alonso M., Montevecchi W. A., et al. The collapse and continued low productivity of a keystone forage fish species. Mar. Ecol. Prog. Ser. 2019; 616: 155–170. doi: 10.3354/meps12924 [DOI] [Google Scholar]

[pone.0288650.ref018] 18.Montevecchi WA. Binary dietary responses of Northern Gannets (Sula bassana) indicate changing food web and oceanographic conditions. Mar Ecol Prog Ser. 2007; 352: 213–220. [Google Scholar]

[pone.0288650.ref019] 19.Garthe S, Montevecchi WA, Davoren GK. Inter-annual changes in prey fields trigger different foraging tactics in a large marine predator. Limnol Oceanogr. 2011; 56: 802–812 [Google Scholar]

[pone.0288650.ref020] 20.d’Entremont K.J.N., Davoren G.K., Walsh C.J., Wilhelm S.I., Montevecchi W.A. Intra- and inter-annual shifts in foraging tactics by parental Northern Gannets (Morus bassanus) in response to changing prey fields. Mar Ecol Prog Ser. 2022. b; 698: 155–170. 10.3354/meps14164 [DOI] [Google Scholar]

[pone.0288650.ref021] 21.Guillemette M, Grégoire F, Bouillet D, Rail J-F, Bolduc F, Caron A, et al. Breeding failure of seabirds in relation to fish depletion: Is there one universal threshold of food abundance? Mar Ecol Prog Ser. 2018; 587:235–245 [Google Scholar]

[pone.0288650.ref022] 22.Garthe S, Benvenuti S, Montevecchi WA. Pursuit plunging by Northern Gannets (Sula bassana) feeding on capelin (Mallotus villosus). Proc R Soc B. 2000; 267: 1717–1722 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0288650.ref023] 23.Garthe S, Guse N, Montevecchi WA, Rail J-F, Grégoire F. The daily catch: Flight altitude and diving behavior of northern gannets feeding on Atlantic mackerel. J Sea Res. 2014; 85: 456–462. [Google Scholar]

[pone.0288650.ref024] 24.Raine AF, Gjerdrum C, Pratte I, Madeiros J, Felis JJ, Adams J. Marine distribution and foraging habitat highlight potential threats at sea for the Endangered Bermuda petrel Pterodroma cahow. Endang Species Res. 2021; 45:337–356. 10.3354/esr01139 [DOI] [Google Scholar]

[pone.0288650.ref025] 25.Häkkinen H, Petrovan SO, Sutherland WJ, & Pettorelli N. Terrestrial or marine species distribution model: Why not both? A case study with seabirds. Ecol Evol. 2021; 11, 16634–16646. doi: 10.1002/ece3.8272 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0288650.ref026] 26.Skov H, Humphreys E, Garthe S, Geitner K, Grémillet D, Hamer KC, et al. Application of habitat suitability modelling to tracking data of marine animals as a means of analyzing their feeding habitats. Ecol Modell. 2008; 212 (3–4): 504–512 [Google Scholar]

[pone.0288650.ref027] 27.Chardine JW, Rail J-F, Wilhelm S. Population dynamics of Northern Gannets in North America, 1984–2009. J Field Ornithol. 2013; 84(2), 187–192. http://www.jstor.org/stable/24617968 [Google Scholar]

[pone.0288650.ref028] 28.Mowbray TB. Northern Gannet (Morus bassanus), version 1.0. In Birds of the World (S. M. Billerman, Editor). Cornell Lab of Ornithology, Ithaca, NY, USA; 2020. 10.2173/bow.norgan.01 [DOI] [Google Scholar]

[pone.0288650.ref029] 29.Geen GR, Robinson RA, Baillie SR. Effects of tracking devices on individual birds—a review of the evidence. J Avian Biol. 2019; 50: doi: 10.1111/jav.01823 [DOI] [Google Scholar]

[pone.0288650.ref030] 30.R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing. 2021; Vienna. [Google Scholar]

[pone.0288650.ref031] 31.Luque SP. Diving behaviour analysis in R. R News. 2007; 7: 8–14. [Google Scholar]

[pone.0288650.ref032] 32.Beal M, Oppel S, Handley J, Pearmain EJ, Morera-Pujol V, Carneiro APB, et al. track2KBA: An R package for identifying important sites for biodiversity from tracking data. Meth Ecol Evol. 2021;12:2372–2378. doi: 10.1111/2041-210X.13713 [DOI] [Google Scholar]

[pone.0288650.ref033] 33.Carscadden JE, Frank KT, Leggett WC. Ecosystem changes and the effects on capelin (Mallotus villosus), a major forage species. Can J Fish Aquat Sci. 2001; 58:73–85. [Google Scholar]

[pone.0288650.ref034] 34.Matches Hipfner J. and mismatches: ocean climate, prey phenology and breeding success in a zooplanktivorous seabird. Mar Ecol Prog Ser. 2008; 368:295–304. [Google Scholar]

[pone.0288650.ref035] 35.Buren AD, Koen-Alonso M, Pepin P, Mowbray F, Nakashima B, Stenson G, et al. Bottom-up regulation of capelin, a keystone forage species. PLoS One. 2014; 9:1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0288650.ref036] 36.Goyert HF. Relationship among prey availability, habitat, and the foraging behavior, distribution, and abundance of common terns Sterna hirundo and roseate terns S. dougallii. Mar Ecol Prog Ser. 2014; 506: 291–302. [Google Scholar]

[pone.0288650.ref037] 37.Elliott KH, Woo K, Gaston AJ, Benvenuti S, Dall’Antonia L, Davoren GK. Seabird foraging behaviour indicates prey type. Mar Ecol Prog Ser. 2008; 354:289–303. [Google Scholar]

[pone.0288650.ref038] 38.Pebesma EJ RS Bivand. Classes and methods for spatial data in R. R News 2005; 5(2), https://cran.r-project.org/doc/Rnews/. [Google Scholar]

[pone.0288650.ref039] 39.Aarts G, MacKenzie M, McConnell B, Fedak M, Matthiopoulos J. Estimating space-use and habitat preference from wildlife telemetry data. Ecography. 2008; 31: 140–160. 10.1111/j.2007.0906-7590.05236.x [DOI] [Google Scholar]

[pone.0288650.ref040] 40.Hijmans RJ, van Etten J. raster: Geographic analysis and modeling with raster data. R package version 20–12; 2012. https://cran.r-project.org/web/packages/raster/index.html [Google Scholar]

[pone.0288650.ref041] 41.Baylis AMM, Tierney M, Orben RA, Warwick-Evans V, Wakefield E, Grecian WJ, et al. Important At-Sea Areas of Colonial Breeding Marine Predators on the Southern Patagonian Shelf. Sci Rep 9, 8517 (2019). doi: 10.1038/s41598-019-44695-1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0288650.ref042] 42.Warwick-Evans V, Ratcliffe N, Lowther AD, Manco F, Ireland L, Clewlow HL, et al. Using habitat models for chinstrap penguins Pygoscelis antarctica to advise krill fisheries management during the penguin breeding season. Divers Distrib. 2018; 1–16, 1756–1771, 10.1111/ddi.12817 [DOI] [Google Scholar]

[pone.0288650.ref043] 43.Wood SN. mgcv: Mixed GAM computation vehicle with automatic smoothness estimation. R package version 1.8–38; 2021. https://cran.r-project.org/web/packages/mgcv/mgcv.pdf [Google Scholar]

[pone.0288650.ref044] 44.Barton K. MuMIn. Multi-Model Inference. R package version 1.47.5; 2023. https://CRAN.R-project.org/package=MuMIn

[pone.0288650.ref045] 45.Grémillet D, Pichegru L, Kuntz G, Woakes AG, Wilkinson S, Crawford RJM, et al. A junk-food hypothesis for gannets feeding on fishery waste. Proc R Soc B. 2008; 275: 1149–1156. doi: 10.1098/rspb.2007.1763 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0288650.ref046] 46.Regular PM, Hedd A, Montevecchi WA, Robertson GJ, Storey AE, Walsh CJ. Why timing is everything: Energetic costs and reproductive consequences of resource mismatch for a chick-rearing seabird. Ecosphere. 2014; 5 (12): 1–13. [Google Scholar]

[pone.0288650.ref047] 47.Angel LP, Barker S, Berlincourt M, Tew E, Warwick-Evans V, Arnould JPY. Eating locally: Australasian gannets increase their foraging effort in a restricted range. Biology open. 2015;4(10):1298–305. doi: 10.1242/bio.013250 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0288650.ref048] 48.Montevecchi WA, Gerrow K, Buren AD, Davoren GK, Lewis KP, Montevecchi MW, et al. Pursuit-diving seabird endures regime shift involving a three-decade decline in forage fish mass and abundance. Mar Ecol Prog Ser. 2019; 627: 171–178. [Google Scholar]

[pone.0288650.ref049] 49.Lescure L, Gulka J, Davoren GK. Increased foraging effort and reduced chick condition of razorbills under lower prey biomass in coastal Newfoundland, Canada. Mar Ecol Prog Ser. 2023; 709, 109–123. 10.3354/meps14286 [DOI] [Google Scholar]

[pone.0288650.ref050] 50.Montevecchi WA, Ricklefs RE, Kirkham IR, Gabaldon D. Growth energetics of nestling Northern Gannets (Sula Bassanus). Auk. 1984; 101: 334–341. [Google Scholar]

[pone.0288650.ref051] 51.Davoren GK. Divergent use of spawning habitat by male capelin (Mallotus villosus) in a warm and cold year. Beh Ecol. 2013; 24(1): 152–161 [Google Scholar]

[pone.0288650.ref052] 52.Crook KA, Maxner E, Davoren GK. Temperature-based spawning habitat selection by capelin (Mallotus villosus) in Newfoundland. ICES J Mar Sci. 2017; 74(6): 1622–1629 [Google Scholar]

[pone.0288650.ref053] 53.Penton PM, Davoren GK. Physical characteristics of persistent deep-water spawning sites of capelin: Importance for delimiting critical marine habitats. Mar Biol Res. 2012; 8: 778–783. [Google Scholar]

[pone.0288650.ref054] 54.Bliss LM, Dawe N, Carruthers EH, Murphy HM, Davoren GK. Using fishers’ knowledge to determine the spatial extent of deep-water spawning of capelin (Mallotus villosus) in Newfoundland, Canada. Front Mar Sci. 2023; 9 doi: 10.3389/fmars.2022.1061689 [DOI] [Google Scholar]

[pone.0288650.ref055] 55.Piatt JF. The aggregative response of common murres and Atlantic puffins to their prey. Stud Avian Biol. 1990; 14:36–51. [Google Scholar]

[pone.0288650.ref056] 56.Carscadden JE, Montevecchi WA, Davoren GK, Nakashima BS. Trophic relationships among capelin (Mallotus villosus) and seabirds in a changing ecosystem. ICES J Mar Sci. 2002; 59: 1027–1033. [Google Scholar]

[pone.0288650.ref057] 57.Link JS, Bogstad B, Sparholt H, Lilly GR. Trophic role of Atlantic cod in the ecosystem. Fish Fish. 2009; 10 (1): 58–87. [Google Scholar]

[pone.0288650.ref058] 58.Dudley SFJ, Field JG, Shelton PA. Distribution and abundance of eggs, larvae and early juveniles of saury Scomberesox saurus scombroides (Richardson) off the south-western Cape, South Africa, 1977/78. S Afr J Mar Sci. 1985; 3: 229–237 [Google Scholar]

[pone.0288650.ref059] 59.Olafsdottir AH, Utne KR, Jacobsen JA, Jansen T, Óskarsson GJ, Nøttestad L, et al. Geographical expansion of Northeast Atlantic mackerel (Scomber scombrus) in the Nordic Seas from 2007 to 2016 was primarily driven by stock size and constrained by low temperatures. Deep-Sea Res Part II. 2019; 159: 152–168. [Google Scholar]

[pone.0288650.ref060] 60.Leim AH, Scott WB. Fishes of the Atlantic coast of Canada. Bull Fish Res Board Can No. 155; 1966. [Google Scholar]

[pone.0288650.ref061] 61.Moores JA, Winters GH, Parsons LS. Migrations and biological characteristics of Atlantic mackerel (Scomber scombrus) occurring in Newfoundland waters. J Fish Res Board Can. 1975; 32: 1347–1357 [Google Scholar]

[pone.0288650.ref062] 62.Brennan CE, Blanchard H, Fennel K. Putting temperature and oxygen thresholds of marine animals in context of environmental change: A regional perspective for the Scotian Shelf and Gulf of St. Lawrence. PLoS ONE. 2016; 11(12): e0167411. doi: 10.1371/journal.pone.0167411 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0288650.ref063] 63.Carscadden JE, Gjøsæter H, Vilhjálmsson H. A comparison of recent changes in distribution of capelin (Mallotus villosus) in the Barents Sea, around Iceland and in the Northwest Atlantic. Prog Ocean. 2013; 114: 64–83 10.1016/j.pocean.2013.05.005 [DOI] [Google Scholar]

[pone.0288650.ref064] 64.Montevecchi WA, Benvenuti S, Garthe S, Davoren GK, Fifield DA. Flexible tactics of an opportunistic seabird preying on capelin and salmon. Mar Ecol Prog Ser. 2009; 385: 295–306. doi: dx.doi.org/10.3354/meps08006 [Google Scholar]

[pone.0288650.ref065] 65.Hedd A, Regular PM, Wilhelm SI, Rail J-F, Drolet B, Fowler M et al. Characterization of seabird bycatch in eastern Canadian waters, 1998–2011, assessed from onboard fisheries observer data. Aquat Conserv. 2015; 26(3), 530–548. doi: 10.1002/aqc.2551 [DOI] [Google Scholar]

[pone.0288650.ref066] 66.Oliver ECJ, Burrows MT, Donat MG, Sen Gupta A, Alexander LV, Perkins-Kirkpatrick SE et al. Projected marine heatwaves in the 21st century and the potential for ecological impact. Front Mar Sci. 2019; 10.3389/fmars.2019.00734 [DOI] [Google Scholar]

[pone.0288650.ref067] 67.Mbaye B, Doniol-Valcroze T, Brosset P, Castonguay M, Van Beveren E, Smith A, et al. Modelling Atlantic Mackerel spawning habitat suitability and its future distribution in the north-west Atlantic. Fish Oceanogr. 2020; 29:84–99 [Google Scholar]

[pone.0288650.ref068] 68.Walsh HJ, Richardson DE, Marancik KE, Hare JA. Long-term changes in the distributions of larval and adult fish in the northeast US shelf ecosystem. PLoS one. 2015; 10(9), e0137382. 10.1371/journal.pone.0137382 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0288650.ref069] 69.Nye JA, Link JS, Hare JA, Overholtz WJ. Changing spatial distribution of fish stocks in relation to climate and population size on the Northeast United States continental shelf. Mar Ecol Prog Ser. 2009; 393, 111–129. 10.3354/meps08220 [DOI] [Google Scholar]

[pone.0288650.ref070] 70.Sydeman WJ, Schoeman DS, Thompson SA, Hoover BA, Garcia-Reyes M, Daunt F, et al. Hemispheric asymmetry in ocean change and the productivity of ecosystem sentinels. Science. 2021; 372 (6545): 980–983. doi: 10.1126/science.abf1772 [DOI] [PubMed] [Google Scholar]

[pone.0288650.ref071] 71.Andrews S, Leroux SJ, Fortin M-J. Modelling the spatial–temporal distributions and associated determining factors of a keystone pelagic fish. ICES J Mar Sci. 2020; 77 (7–8): 2776–2789. [Google Scholar]

[pone.0288650.ref072] 72.Pettex E, Lorentsen S-H, Grémillet D, Gimenez O, Barrett RT, Pons J-P, et al. Multi-scale foraging variability in Northern Gannet (Morus Bassanus) fuels potential foraging plasticity. Mar Biol. 2012; 159 (12): 2743–56. 10.1007/s00227-012-2035-1. [DOI] [Google Scholar]

[pone.0288650.ref073] 73.Melvin GD, Stephenson RL, Power MJ. Oscillating reproductive strategies of herring in the western Atlantic in response to changing environmental conditions. ICES J Mar Sci. 2009; 66 (8): 1784–1792. [Google Scholar]

PERMALINK

Quantifying inter-annual variability on the space-use of parental Northern Gannets (Morus bassanus) in pursuit of different prey types

Kyle J N d’Entremont

Isabeau Pratte

Carina Gjerdrum

Sarah N P Wong

William A Montevecchi

Roles

Abstract

Introduction

Methods

Study area and species

Fig 1. Foraging domain (blue) used in the habitat modelling for parental Northern Gannets breeding at Cape St. Mary’s, Newfoundland, Canada (yellow diamond).

GPS device deployment

Data processing

Fig 2. Daily proportion of U- and V-shaped dives performed by Northern Gannets.

Dive distributions

Habitat suitability modelling

Table 2. Top three candidate models following automated model selection.

Fig 3. Mean number of dives per day (Julian Date) performed by all individual gannets across all three years.

Results

Dive distributions

Table 1. Sample size and tracking period (when dives were recorded) for each year during which Northern Gannets were tracked from Cape St. Mary’s, NL.

Fig 4. Spatial distribution of U- (red), early (blue) and late (purple) V-shaped dives performed by Northern Gannet tracked from Cape St. Mary’s (yellow diamond) for each year of the study.

Model predictions

Fig 5.

Fig 6.

Discussion

Habitat suitability in pursuit of varying prey types

Risk associated with anthropogenic activity and climate change

Conclusions

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Vitor Hugo Rodrigues Paiva

Roles

Author response to Decision Letter 0

Decision Letter 1

Vitor Hugo Rodrigues Paiva

Roles

Author response to Decision Letter 1

Decision Letter 2

Vitor Hugo Rodrigues Paiva

Roles

Acceptance letter

Vitor Hugo Rodrigues Paiva

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases