Foraging areas of Orlog's gull in an estuarine ecosystem of Argentina: are they underprotected?

doi:10.21203/rs.3.rs-3345929/v1

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Foraging areas of Orlog's gull in an estuarine ecosystem of Argentina: are they underprotected?

https://doi.org/10.21203/rs.3.rs-3345929/v1

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published 15 Mar, 2024

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Seabird populations worldwide are facing significant declines due to various threats, making them valuable bioindicators of marine ecosystem changes. Understanding their foraging behavior and identifying crucial foraging areas is essential for their conservation. In this study, we focused on Olrog’s Gull (Larus atlanticus), a near-threatened species endemic to the Atlantic coast of Argentina, Uruguay, and southern Brazil. Our objectives were to assess the distribution of foraging areas (FAs) and home ranges, describe temporal flight patterns, and evaluate FA overlap with protected areas in the Bahía Blanca Estuary (BBE), Argentina. We used GPS tracking with dynamic Brownian bridge movement models (dBBMM) to analyze Olrog’s Gull behavior during their breeding season. Our results revealed well-defined FAs, with 72% of them being located outside protected areas, raising concerns about potential threats to the species. We observed sex-related differences, with females covering longer distances during foraging flights. Additionally, several FAs were situated near industrial sites, posing health risks due to potential pollution. This study contributes novel insights into Olrog’s Gull foraging ecology, particularly in the most critical breeding area for the species. We developed a dynamic web application for easy access to conservation-relevant information. Our findings emphasize the need for enhanced protection of key FAs, especially those outside existing protected areas, to safeguard the species and its ecosystem. These results underscore the importance of informed policy decisions to preserve Olrog’s Gull populations and their habitats in the face of growing human-related threats.

Larus atlanticus

Estuary of Bahía Blanca

foraging

spatial ecology

Globally, populations of seabirds are declining (Paleczny et al. 2015). There are numerous threats to seabirds including predation, disturbance and habitat loss, which particularly affect them during breeding, and bycatch, pollution and overfishing while they are at sea for much of the rest of the year (Dias et al. 2019). As bioindicators, seabirds can offer insight into marine ecosystem changes (Piatt et al. 2007). They travel between profitable prey patches, and reduce movement when they reach areas with abundant prey (Weimerskirch 2007), so tracking seabirds can indicate areas of prey occurrence (Piatt et al. 2007). Seabird foraging ranges can be used to identify candidate locations for protection (Thaxter et al. 2012), and protecting these areas could benefit whole ecosystems (Hooker and Gerber 2004).

The Olrog’s Gull (Larus atlanticus) is a near threatened species (BirdLife International 2018) endemic to the Atlantic coast of Argentina, Uruguay and southern Brazil (Yorio et al. 2013). Few Olrog’s Gull breeding sites have been identified, and all of them are located in Argentina (Yorio et al. 2013). Most of the breeding population concentrates in the Bahía Blanca Estuary (BBE), Buenos Aires province (Petracci and Sotelo 2013), with the largest colony known to this date located in Isla del Puerto (Delhey et al. 2001a).

During their breeding season in the BBE, Olrog’s Gull adults prey mainly on the grapsid crabs Neohelice granulata (Delhey et al. 2001b) and Cyrtograpsus angulatus, which they feed to their young, and this specialized feeding ecology of Olrog’s Gull makes it highly dependent on intertidal habitats at their breeding grounds. These traits make Olrog’s Gull not only highly dependent on coastal habitats but also especially vulnerable to human-related activities (Burger and Galli 1987; Cornelius et al. 2001). With this background, the identification of foraging areas (henceforth denoted as FA) of Olrog’s Gull becomes crucial for the management of the species through the effective protection of key foraging areas in this large wetland.

Under the under the hypothesis that Olrog’s Gull feeding grounds in the EBB are not effectively protected, the main objectives of this research were (1) to assess the distribution of FAs and home range used by Olrog’s Gull in this area, (2) to evaluate the overlap between FAs and protected areas, and (3) to describe the temporal patterns of flight trajectories.

Study area and species

The study was conducted in the Bahía Blanca Estuary in southwest Buenos Aires province, Argentina. This wetland is characterized by extensive mudflats and marshes of Spartina spp. and Salicornia ambigua, and large populations of N. granulata and C. angulatus crabs (Zalba et al. 2008). In this area there are three protected areas: the Reserva Natural de Usos Múltiples Bahía Blanca, Bahía Falsa, Bahía Verde (2600 km²), Reserva Natural Municipal Costera Bahía Blanca (3.1 km²), and Reserva Natural Islote de la Gaviota Cangrejera/Isla del Puerto (16.1 km²). Every year, the latter concentrates the largest known breeding colony of Olrog’s Gulls (38° 49’ S, 62° 16’ W), which comprises ~ 3,500 pairs distributed in subcolonies adjacent to the intertidal area (Yorio et al. 2013). In the study area, Olrog’s Gulls start laying their eggs in early September, eggs start hatching between late September and early October, and chicks are fully fledged by late December (La Sala et al. 2011a). There are other Olrog’s Gull colonies in this area, but they are considerably smaller (Petracci and Sotelo 2013).

Sampling

Fieldwork was conducted during the late incubation period of 2015 breeding season (1 November through 11 November). Due to the difficult access to the studied colony, and to minimize human disturbance to a vulnerable species during the breeding period, a convenience sampling was conducted. Coulson traps (Weaver and Kadlec 1970) were placed over active nests containing at least one egg, and which could be readily accessed with minimum disturbance to other breeding adults. During animal manipulation, the birds were hooded to minimize stress. After each capture, the trap was changed to a different location, and only one adult Olrog’s Gull per nest was captured. All the birds were fitted with metal and plastic leg bands with unique alpha-numeric identification codes to avoid recapture.

Individuals were weighed with a hand-held spring scale (nearest 10 g), and four measurements were taken using a caliper. Also, a blood sample was collected from each bird by venipuncture of the brachial vein using heparinized syringes with 23G×1-inch needles, and a few drops were placed on a small piece of commercial filter paper, air-dried, and stored at 4–8°C until processed for sex identification by molecular means (see Petracci et al. 2018).

GPS tracking

To characterize the flights of Olrog’s Gull, each bird was instrumented with a global positioning system (GPS) store-on-board logger (Cat-Track i-gotU GT-120), sealed using a rubber shrink tube. The devices were set to record time and position every 11 seconds.

We acknowledge that behavior, time, and energy budget of birds may be directly affected by externally attached devices (Elliott et al. 2007; Vandenabeele et al. 2012). However, studies using GPS with other gull species suggest minimum effects on weight, breeding success and/or survival (Masello et al. 2013; Camphuysen et al. 2015; Thaxter et al. 2016). Here, the presence of potential effects and on the studied birds was minimized by using small tags (20 g, including attachment), which represented 2.6% and 2.2% of the body mass of the captured females and males, respectively. We deployed loggers on one pair member from 17 nests. The devices were attached to the bird’s dorsal mantle cover feathers using adhesive tape. After release, the behavior of each gull was closely monitored for signs of disturbance. Each GPS was left operating on the bird for ca. 24 h, after which the birds were recaptured and the GPS was removed for data transfer. Only one GPS could not be recovered, but both pair members were observed nesting normally, indicating that this gull did not suffer any damage that would compromise its survival.

Home range analysis

We used kernel density estimation (KDE), a measure of the probability of occurrence, to characterize the distribution and define important areas for Olrog’s gulls during the early incubation stage. The use of KDE to characterize home ranges is a well-established method (Laver and Kelly 2008). Modern methods for home range estimation quantify not only the size of the area, but also how intensely animals use different areas within their home range, referred to as a utilization distribution (UD). Here, the dynamic Brownian bridge method (dBBMM) was chosen over the classic kernel method (Worton, 1987) as it better accounts for the auto-correlated nature of telemetry-derived data by basing kernel density estimations on the movement path rather than individual location estimates (Horne et al. 2007; Kranstauber et al. 2012). The dBBMM has been recognized for its broad potential in ecological studies (Farmer et al. 2010; Morten et al. 2022), assessments of the efficacy of marine reserves for marine birds (Mason et al. 2018), and disease outbreak investigations (Takekawa et al. 2010).

The analysis was performed using the “move” R package (Kranstauber et al. 2012) including an error of 10 m., a time step of five min., a margin of 21 locations and window sizes of 43, following Kranstauber et al. (2012).

To identify the percentage of utilization distribution (UD%) that best describes the FA, we visually identified areas corresponidng to “foraging” (n = 201) and “non-foraging” (n = 103) sites along flight trajectories of four Olrog’s gulls. This was done for two and two females to control potential biases associated to the sex of the birds. Following, we identified the UD% that best classified those areas using the accuracy level and this threshold was used to transform each continuous model into a binary raster map, where foraging and non-FAs were defined as those pixels with values above and below this threshold, respectively. Each FA was comprised of diferente number of pixels which were either adjunct, or disjunt with no-FA interspersed. Then, to improve the visualization of each FA, we identified visually clusters of pixels with values above the defined threshold and built a minumum convex polygon (MCP) around each cluster. The centroid of each FA was calculated to allow for easier spatial location of small foraging areas. Additionally, we estimated home ranges as 100% MPCs.

The temporal pattern of foraging trips was analyzed for each bird. Also, the total and percentage of FA laying inside or outside any of the protected areas was calculated, and the difference of proportion of protected FA between males and females was assesssed using a logistic regression model. The distance between each pixel classified as FA and the centroid of the breeding colony was calculated for each gull, and the difference in distance between sexes was estimated using a mixed effects model that included each gull as a random intercept using the “nlme” R package (Pinheiro and Bates 2000).

To allow better exploration of results, a dynamic application was developed using Google Earth Engine (Gorelik et al. 2017) through its JavaScript API (https://lucianolasala.users.earthengine.app/view/olroggull), which incorporates exploration capabilities for the location of FAs according to our models and allows the exploration of flight trajectories for individual Olrog’s gulls in the study area.

Tracking and foraging patterns

In this study, GPS tags were operative an average of 24.2 h (SD: 6.5; range: 14.8–40.2, n = 14 gulls). The accumulated tracking time for all the birds was 338.72 h (mean: 24.19; range: 15.83–40.87). The distribution of flight trajectories and their point locations showed varying distribution among individuals and between sexes (Fig. 1; see web application for greater detail).

Our model showed that Olrog’s gulls use well defined areas during their foraging trips. We identified a total of 57 FAs distributed across the study area, 41 (72%) of which were located outside the limits of PAs, three (5%) overlapped partially with the latter, and 13 (23%) lay completely inside their boundaries. Also, eight (14%) of the FAs that were located outside PAs, lay inside areas recently incorporated in the Western Hemisphere Shorebird Reserve Network (WHSRN). Finally, 21 (37%) FAs were located along the northern shore of the BBE in close proximity to industrial and sewage effluents.

Mean home range (100% MCP) was larger (p = 0.0021) for females (mean: 3082 ha; range: 1821-5030.4) than males (mean: 1211.8 ha; range: 440.5–1932) (Fig. 2). Mean size of FAs was 13.7% larger for females (mean: 1.23 ha; SD: 0.875; range: 0.21–2.81) compared to males (mean: 1.07 ha; SD: 1.11; range: 0.04–3.07), but this difference was not significant (p = 0.7582) (Fig. 3). On average, however, the odds of using FA under protection were 35 times larger for males than females (OR: 36.1; p = 0.0369; males: 37.7%; females: 1.2%) (Table 1). Three FAs were located in artificial water bodies within the premises of two industrial plants (gulls OG04_M and OG02_F), seven were under direct influence of industrial wastewater discharge points (gulls OG12_H, OG09_M, OG08_M, OG03_F, and OG01_M), and other four were adjacent to the main municipal sewage outfall (gulls OG13_M, OG06_F, and OG04_M) (see web application).

The mean distance travelled by each gull between the nest and each foraging pixel was 8.32 km (range: 2.6–15.1), and this distance was larger (p = 0.0317) for females (mean: 10.9 km; SD: 4.52) compared to males (mean: 8 km; SD: 2.75) (Fig. 4). The temporal pattern of flight trajectories did not vary markedly between males and females, and it was highly variable among individuals with flight and forage activities occurring during night and day hours (Fig. 5).

Our model validation process yielded a mean accuracy of 0.825 (range: 0.741–0.952), a mean sensibility of 0.888 (range: 0.788-1.00), and a mean specificity of 0.699 (range: 0.389–0.944).

A handful of studies have addressed foraging patterns and areas for Olrog’s Gull in other areas during the breeding season (Yorio et al. 2005; Suárez et al. 2012). However, to date there were no studies addressing this topic in the BBE, the most relevant breeding area for the species. Our study is unique by adding novel information regarding the foraging ecology of Olrog’s Gull in general, and in the most important breeding area for the species in particular. Also, we successfully implemented dynamic Brownian bridge movement models as novel approach for this species, and developed a dynamic web application that offers interested parties such as scientists, managers and decision makers, access to relevant information that can be used as a conservation tool, either alone or in combination with other resources.

Olrog’s Gull females covered larger distances than males during their foraging flights. These differences in flight distance and habitat use could be explained by sex differences in habitat use and selection, as has been also found in other gull species (e.g., Camphuysen et al. 2015; Kazama et al. 2018; Navarro et al. 2010).

Previous research suggested that mercury (Hg) concentrations in feathers of adult Olrog’s Gull from this colony could have potential for long-term effects, with Hg reported values largely falling within the range that is considered toxic (La Sala et al. 2011b). Also, Olrog’s gulls from the same colony have been shown to carry pathogens of human and animal origin such as Salmonella enterica var. typhimurium, Salmonella enterica var. gallinarum and Escherichia coli (La Sala et al. 2014), whereas Olrog’s Gull prey crabs N. granulata and C. angulatus from some of the FAs identified here carried Clostridium perfringens type A in their gastrointestinal tracts (La Sala et al. 2015). With this background, our results raise yet another concern about the health risks for Olrog’s gulls in the study area, and mostly in FAs near industry effluents and sewage outfalls.

Here, Olrog’s Gull used foraging areas located both inside and outside PAs, but unprotected foraging areas were considerably far more common than protected ones. Moreover, the large number of FAs that are subjected to the potential impacts of industrial activities or wastewater pollution raise yet another concern about their potential negative effects on this population. Recently, new areas encompassing a total of 4,760 ha were incorporated in the Western Hemisphere Shorebird Reserve Network (WHSRN). In our study, 14% of the FAs lay inside these areas. However, despite their international importance for the conservation of shorebirds, these sites are not protected by law and remain vulnerable to future human-related activities.

In conclusion, our research reinforces the need to ramp up policy and targeted conservation strategies towards the effective protection of areas that are key for Olrog’s Gull but still laying outside the boundaries of protected areas.

All authors contributed to the study conception and design. Material preparation, field work and data collection were performed by Pablo Petracci, Leandro Marbán, Martín Sotelo, Martín Carrizo and Rodolfo Sarria. All the analyses and first draft of the manuscript were performed by Luciano La Sala and Nicolás Caruso and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contributions

Data Availability

The datasets used in this research are not publicly available due to confidentiality reasons; however, they are available from the corresponding author on reasonable request.

Ethics approval

This study was performed under the permits by Ministerio de Ambiente de la Provincia de Buenos Aires.

Compliance with Ethical Standards

No disclosure of potential conflicts of interest (financial or non-financial) is necessary in this research. High animal welfare standards were followed and stages of our field work were closely overseen by government authorities (park rangers). No informed consent was necessary as humans were not involved in our work.

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Table I. Foraging area (FA) for male and female Olrog’s Gull in the Bahía Blanca Estuary. Total and protected FA (ha) are reported as mean, standard deviation (SD) and range for males and females. Protected FA is also presented as percentage of the total FA.

	Total FA (ha)			Protected FA (ha)			Protected FA (%)
Sex	Mean	SD	Range	Mean	SD	Range	Mean
Males	1.07	1.11	0.04-3.07	0.401	0.51	0-1.3	37.7
Females	1.23	0.875	0.21-2.81	0.014	0.02	0-0.06	1.16

Table II. Home range (MCP 100), core area (MCP 50) and foraging area (FA) for male and female Olrog’s Gull in the Bahía Blanca Estuary. Areas are reported in hectares.

Gull	Sex	MPC 100	MPC 50	FA
OG01	Male	1915.70	949.43	1.88
OG02	Female	2929.27	1300.29	1.32
OG03	Female	5030.43	1779.15	0.61
OG04	Male	1316.67	1164.68	3.07
OG05	Male	777.40	152.32	0.88
OG06	Female	1820.88	242.97	0.21
OG07	Female	3520.30	1045.05	1.84
OG08	Male	1932.03	353.78	1.26
OG09	Male	613.94	13.83	0.04
OG10	Female	1895.09	649.10	0.70
OG11	Male	1486.64	113.87	0.08
OG12	Female	2759.72	1540.23	2.81
OG13	Male	440.48	74.00	0.25
OG14	Female	3618.14	880.76	1.15

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You are reading this latest preprint version

Foraging areas of Orlog's gull in an estuarine ecosystem of Argentina: are they underprotected?

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Abstract

Figures

Introduction

Materials and Methods

Study area and species

Sampling

GPS tracking

Home range analysis

Results

Tracking and foraging patterns

Discussion

Declarations

References

Tables

Status:

Journal Publication

Version 1