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23 December 2021 Fine-scale Weather Patterns Drive Reproductive Success in the Brown Pelican
Rochelle A. Streker, Juliet S. Lamb, John Dindo, Patrick G. R. Jodice
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Abstract

In the northern Gulf of Mexico, island restoration and creation have been used to mitigate potential negative effects of anthropogenic and environmental stressors to breeding seabirds. The long-term success of such projects can be enhanced when data are available to elucidate how site-specific and larger-scale factors may contribute to reproductive success. Nest-specific daily survival rate (DSR) of Eastern Brown Pelicans (Pelecanus occidentalis carolinensis) during incubation (i.e., pre-hatch; n = 245) and brood-rearing (i.e., post-hatch; n = 185) were measured at two breeding islands in the northern Gulf of Mexico USA in 2017 and 2018 in relation to macro- and micro- scale habitat and environmental measurements. DSR of nests during incubation ranged from 91-99%, and the DSR during brood-rearing exceeded 99% each year. Regional weather variables occurred in top-performing models more often and with more significance compared to microhabitat variables. Results suggest that reproductive success of Brown Pelicans may respond at least in part to weather factors that occur outside of the scope of habitat structure as it is typically incorporated into the restoration or creation of breeding habitat, indicating that climate conditions are likely an important factor in the success of restoration efforts.

The reproductive success of seabirds, whether pelagic or nearshore, is affected by a variety of transboundary factors of both natural and anthropogenic origin. For example, mechanisms that commonly drive reproductive success of seabirds at the local scale include nest predation, quality of nesting habitat, and microclimate (Bried et al. 2008; Robinson and Dindo 2011; Brooks et al. 2013). At the regional scale, prey availability, diet quantity and quality, and regional weather patterns can influence reproductive success (Jodice et al. 2006; Frederiksen et al. 2008; Lamb et al. 2017). Regional drivers may further interact in complex ways with large-scale climate patterns and changes (Ramos et al. 2002; Sherley et al. 2011; Sovada et al. 2014). Local, regional, and global factors driving nest success may also differ within the breeding season. For example, for Least Terns (Sternula antillarum) breeding on natural shell mounds and barrier islands in coastal South Carolina, USA, predation was the primary cause of nest loss but tidal over-wash the primary cause of chick loss (Brooks et al. 2013). Thus, identifying management actions to increase breeding success requires understanding potential sources of reproductive failure at a variety of spatial and temporal scales. Without such detailed data the success or failure of such efforts can be easily misinterpreted, and reproductive failure may be misassigned to manageable factors when in fact non-manageable factors may be relevant (Brooks et al. 2013).

The northern Gulf of Mexico of the USA (hereafter, Gulf) supports a rich assemblage of breeding waterbirds including shorebirds, marsh birds. wading birds, and nearshore seabirds (Wilson et al. 2019). Among the nearshore seabirds, Eastern Brown Pelicans (Pelecanus occidentalis carolinensis; hereafter Brown Pelicans) have been identified as a high-priority species for monitoring and restoration (Jodice et al. 2019). The species breeds throughout the northern Gulf in colonies ranging from less than 100 to ∼5,000 pairs (Robinson and Dindo 2011; Walter et al. 2014; Lamb 2016). The estimated breeding population in the Gulf is ∼25k pair, making it the most populous breeding region for the subspecies in North America (Shields 2014). The species is prone to injury from oil spills including direct mortality and sublethal effects (Haney et al. 2014; Fallon et al. 2018). To offset these effects, restoration plans have been developed with the goal of enhancing and creating breeding habitat for Brown Pelicans and other nearshore seabirds (Deepwater Horizon Natural Resource Damage Assessment Trustees 2017; Louisiana Trustee Implementation Group 2019). Such restoration efforts require a breadth of highly detailed data to be fully successful. For many coastal birds; however, detailed measures of reproductive success and the identification of environmental drivers such as weather and climate that might affect reproductive success are lacking (Jodice et al. 2019; Wilson et al. 2019). These data gaps are likely to inhibit the success of restoration and management projects (Wilson et al. 2019). Given their reliance on robust forage fish populations during breeding, as well as their broad distribution across the region, Brown Pelicans can serve as a useful proxy for assessing breeding habitat quality for other co-occurring waterbirds with similar habitat needs (Lamb et al. 2017). However, given the wide range of colony conditions (e.g., xeric to mangrove (Rhizophora spp.)), sizes (e.g., nest counts from ∼100 to ∼5,000), and characteristics (e.g., ground, shrub, and tree-nesting) for Brown Pelicans and other waterbirds in the Gulf, plans for restoration and management will require a suite of site-specific studies across a range of conditions from which to develop plans and interpret results of their actions.

To inform restoration of coastal habitat for breeding birds in the Gulf, we examined factors affecting the reproductive success of Brown Pelicans at the largest breeding colony in the region. We focused our attention on a suite of nest-based variables and broader environmental measurements, including variables that have been or are often found to be impactful to reproductive success of coastal nesting birds during either incubation or chick-rearing (Table 1). We modeled the relationship between these variables and the daily survival (DSR) of nests and broods of Brown Pelicans during 2017 and 2018 to determine how both island-specific habitat features and external environmental conditions affect reproductive success. Studies such as ours, that simultaneously evaluate effects of local and regional conditions throughout the breeding season, can provide context needed for decision-makers (Wilson et al. 2019).

Methods

Study Area

All research occurred along the Gulf of Mexico coast of Alabama, USA on Gaillard and Cat islands (Fig. 1). Gaillard Island (30° 30′ N, 88° 02′ W) is in Mobile Bay and was constructed by the Army Corps of Engineers in 1979 and currently supports the largest Brown Pelican colony in the Gulf of Mexico. The island's perimeter is protected by a rock-enforced earthen berm. Along the southern berm where Brown Pelicans nest (roughly 20% of the total island area), the dominant vegetation species are cogon grass (Imperata clindrica), Chinese tallow (Sapium sebiferum), phragmites cane (Phragmities australis), and Sesbania sp. (Robinson and Dindo 2008; Streker 2019). Cat Island (30° 19′ N, 88° 12′ W) in Portersville Bay is a shell-midden island and vegetation includes marsh elder (Iva frutescens) and baccharis (Baccharis hamilifolia; Robinson and Dindo 2008). Gaillard Island supported a breeding population of ∼3,000-4,000 nesting pairs of Brown Pelicans during the study period. Cat Island supported a breeding population of ∼200 nesting pairs of Brown Pelicans in 2017 but no nesting pairs in 2018.

Nest and Brood Monitoring

We established productivity plots within Brown Pelican colonies on Cat Island (2017: n = 2 plots) and Gaillard Island (2017: n = 4 plots; 2018: n = 7 plots). Each plot contained 10-30 nests, depending on nest configuration and proximity of nests to each other. All plots were spaced based on natural contours and aspects of the islands, resulting in a distance between plots ranging from 60-260 m. Plots were visited every 2-11 days depending upon weather conditions and logistics.

Table 1.

Environmental and nest-based variables collected at nests of Eastern Brown Pelicans (Pelecanus occidentalis carolinensis) on Gaillard and Cat islands, Alabama, 2017 and 2018. Terms in italics are used as abbreviated descriptions in the text.

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(Continued)

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Figure 1.

Location of Gaillard Island and Cat Island, Alabama, USA. Daily survival rates of nests and broods of Eastern Brown Pelicans (Pelecanus occidentalis carolinensis) were measured on each island in relation to habitat and environmental variables.

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We enumerated and recorded nest contents during each visit. When chicks became mobile (∼21 days post hatch) they were banded with both a Bird Banding Lab metal band and a plastic, field-readable, 3-letter leg band (2017: n = 145; 2018: n = 156). During subsequent visits, we searched for banded chicks on colony and via observations from a small power boat within 70 m of shore until all banded chicks were located and identified. Both binoculars (10 × 42 mm) and spotting scopes (20-60 x) were used to continuously scan for chicks during these observations. We maintained a distance of ≥ 15 m between observer and chicks to limit disturbance. The interval between resighting each chick was < 5 days in all cases. We continued re-sighting efforts until ≥ 80% of the banded chicks were > 65 days post hatch, which we defined as ‘fledged’ (Schreiber 1979). All monitored clutches were assigned a final fate of either successful (≥ 1 egg hatched) or failed (0 eggs hatched) and all broods were assigned a final fate of either successful (≥ 1 chick fledged) or failed (0 chicks fledged). We determined fate for all clutches and all broods (i.e., no nests or broods had an unknown fate). We refer to these fates as clutch success and brood success, respectively.

We measured habitat and environmental variables (Table 1) during the same period in which we monitored DSR. Nest-based variables that remained fixed throughout the breeding season were recorded at the establishment of plots and included substrate beneath nest, elevation at the base of the nest above sea level and distance from nest to water's edge. Nest-based variables that could change during the breeding season were measured at the establishment of plots and every 2-4 weeks thereafter and included nest height above ground and vegetation cover directly above the nest. We used the average value of the dynamic variables in subsequent analyses. We measured nest height above ground level by placing a level across the nest, then measuring the distance from the ground to the edge of the level (i.e., the rim of the nest). We measured vegetation cover using a photograph taken from the center of the nest, with the lens facing the sky; subsequently, we overlaid a grid of 100 squares on each photo in Adobe Photoshop CC 2019 and enumerated the grids that contained vegetation to establish percent cover.

We measured nest-specific temperature using an Onset HOBO Tidbit v2 temperature datalogger (Fotronic Corporation, Woburn, Massachusetts, USA). Not all nests received loggers and we therefore stratified placement of loggers (n = 28 nests in 2017, n = 31 nests in 2018) by nest height to produce equal sample sizes within each 10 cm interval from 0-140 cm. Dataloggers recorded the temperature hourly throughout each 24-hour period for the entirety of the breeding stage or until failure, and we subsequently calculated the average and maximum temperatures for each interval between nest visits. We measured regional weather by downloading hourly measures of barometric pressure and humidity from the Mobile Downtown Airport weather station (National Weather Service 2019) which is located approximately 12 km from Gaillard Island and 36 km from Cat Island. We calculated average values for each of these parameters for each interval between nest visits.

Statistical Analysis

To calculate DSR of nests and broods during the incubation and brood-rearing stages, we used the nest survival module in Program Mark (White and Burnham 1999) via the RMark package (Laake and Rexstad 2014) in program R (R Core Team 2016). The nest survival module models the survival probability (i.e., DSR) over the course of each breeding stage as a function of user-specified covariates using generalized linear models with a logit-link function and binomial errors. Prior to analyses we compared the DSR of clutches and broods between Gaillard and Cat islands and, finding no difference (P > 0.10 for each), pooled data from both islands in subsequent analyses.

We modeled the relationships of the independent variables with DSR separately for incubation and brood rearing. We also included as independent variables Julian date, nest age (clutch success models), and age of first chick hatched (brood success models). The latter two variables are created by RMark using the variables ‘AgeFound’ (age of nest in days the day the nest was found) and ‘AgeDay1’ (age of nest at beginning of study). We calculated all age parameters in RMark based on the date and age of the nest at first check. We tested both linear and quadratic terms for the age and time covariates and used the best-performing term for each variable (quadratic for age covariates in all breeding stages except for 2017 brood-rearing; linear for all time covariates in all models) in subsequent models (Streker 2019). We developed a suite of 14 models to assess the relationship between the independent variables and DSR including global and null models. Variables that were highly correlated (|r| ≥ 0.5) were not included in the same model. For each year of incubation data we reran the top performing models on the subset of nests within which temperature was recorded to assess whether the addition of nest-specific temperature variables substantially improved model fit. Temperature variables were not tested during brood-rearing due to the small sample size of broods that failed that also had temperature loggers (2017: n = 1 nest with temperature logger + brood failure; 2018: n = 7 nests with temperature logger + brood failures).

We used Akaike's information criterion (AIC) to rank the models and evaluated the strength of the models using normalized weights (Burnham and Anderson 2002). There were significant differences in fate between years and breeding stages (P < 0.003 for each); therefore, we ran models separately by year (2017, 2018) and breeding stage (incubation, brood-rearing). We report models that were within ΔAIC ≤ 2 of the lowest-scoring model. To avoid potential biases associated with model-averaging, we report coefficient estimates ± SE from top-performing models only (Fieberg and Johnson 2015). Daily survival rates were calculated from top performing models for each year and breeding stage. We also conducted a post-hoc analysis to determine if the fit of DSR models for nests or broods were improved by including a quadratic term for distance to water. The quadratic term never out-performed the linear term in any breeding stage or year based on AICc values and weights (AICc weight for quadratic terms ≤ 0.39 in all cases) and we therefore report model results from the linear models only. We reported incubation and brooding success as the total number of observed clutches and broods, respectively, divided by the number of successful clutches and brood at the end of their respective breeding stage.

Results

During 2017 - 2018, we monitored 245 clutches during incubation (2017: n = 97; 2018: n = 148) and 185 broods containing 279 chicks during brood-rearing (2017: n = 85 broods, n = 128 chicks; 2018: n = 100 broods, n = 151 chicks). The DSR (± SE) of clutches during incubation in 2017 and 2018 was 0.9940 ± 0.002 and 0.9138 ± 0.002, respectively, and overall clutch success was 0.86 and 0.67, respectively. The DSR (± SE) of broods in 2017 and 2018 was 0.9998 ± 0.0003 and 0.9952 ± 0.006, respectively, and overall brood success was 0.94 and 0.78, respectively. We counted 142 fledged chicks from our sample of banded birds in 2017, and 155 fledged chicks from our banded sample in 2018.

In 2017, three models best predicted DSR during incubation (Table 2). The top-ranked model was approximately 1.6 times as likely to be the best model compared to the second-ranked model, and approximately 2.6 times as likely to be the best model compared to the third-ranked models. Average barometric pressure appeared in all top models, average humidity appeared in two of the top models, and distance from nest to water appeared in one top model. There was a negative relationship between barometric pressure (-0.98 ± 0.28) and DSR (Fig. 2a) and between humidity (-0.73 ± 0.38) and DSR (Fig. 2b) during incubation in 2017.

Table 2.

Top-performing models of daily survival rate of nests and chicks of Eastern Brown Pelicans (Pelecanus occidentalis carolinensis) breeding on Gaillard Island and Cat Island, Alabama, USA, 2017 and 2018. Only models within ΔAIC ≤ 2.0 included.

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In 2018, the global model best predicted DSR during incubation (Table 2). The global model carried 99% of the model weight and included significant terms for date (-0.08 ± 0.01), distance from nest to water (-0.73 ± 0.35), nest elevation (-1.05 ± 0.47), average barometric pressure (-1.11 ± 0.27), average humidity (-1.23 ± 0.24), and maximum temperature at the nest (-3.92 ± 1.44). The three weather variables had stronger negative effects on DSR of nests during 2018 compared to time or microhabitat variables (Fig. 3).

In 2017, two models best predicted DSR during brood-rearing (Table 2). The top ranked model was 1.75 times more likely to be the best model than the second ranked model. Average barometric pressure and average humidity appeared in both top models, and distance from nest to water appeared in one top model. There was a negative relationship between barometric pressure (-0.69 ± 0.21) and DSR (Fig. 4a), and a positive relationship between humidity (2.47 ± 0.51) and DSR during brood-rearing (Fig. 4b) in 2017.

In 2018 a single model with 9 of the 10 variables available (average barometric pressure not included) best predicted DSR during brood-rearing and carried 99% cumulative weight (Table 2). There was a positive relationship between DSR and both humidity (1.53 ± 0.29) and chick age2 (0.09 ± 0.02), and a negative relationship between DSR and Julian date (-0.22 ± 0.11) during brood-rearing in 2018 (Fig. 5). The odds of a brood surviving an additional day increased by 4.6 times for each 1% increase in average humidity and decreased by 0.8 times for each 1 day increase in date of hatching.

Figure 2.

Relationships of daily survival rate of clutches with: (a) barometric pressure (range 101.30-102.20 kPa); and (b) humidity (range 79.5%-86.5%) during incubation in 2017 for Eastern Brown Pelicans (Pelecanus occidentalis carolinensis) breeding on Gaillard Island and Cat Island, Alabama, USA. Dashed lines represent 95% confidence intervals.

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Across the incubation period, clutch success rates in our study ranged from 0.67 to 0.86. During brood-rearing, brood success ranged from 0.78 to 0.94, with 1.02 to 1.29 chicks fledged per nest. These results are comparable to previous estimates from Gaillard Island and other colonies in the region (Table 3).

Discussion

Several variables consistently appeared in top performing models for DSR of Brown Pelican clutches and broods in both years of the study. Regional weather variables occurred more often and with greater significance in the top performing models compared to microhabitat variables. Previous studies on Brown Pelican nest selection at breeding sites in the Gulf, including Gaillard Island, found that reproductive success of Brown Pelicans was related to habitat variables including vegetation cover, nest height, and substrate beneath the nest (Ranglack et al. 1991; Robinson and Dindo 2011; Walter et al. 2013; Lamb et al. 2016). Our results differed from these previous studies in that we did not find significant relationships between most nest-based variables and survival of nests or broods. These differences could result from differences in the response variables being measured: previous studies focused on nest site selection, chick condition, or individual fledging success rather than DSR. The differences could also be due to the addition of weather variables in our modeling, which were not included in the previous studies. Our results suggest that the effects of habitat on reproductive success may be overwhelmed by the importance of weather variables at least in some years, as has been observed for Roseate Terns (Sterna dougallii) nesting on tropical islands and American White Pelicans (P. erythrorhynchos) nesting in North America (Ramos et al. 2002; Sovada et al. 2014).

Average barometric pressure consistently appeared in top models for both clutch and brood survival and negatively influenced daily survival rates of clutches and broods, despite different requirements during these breeding stages. We originally posited that barometric pressure would have a positive relationship with DSR, assuming lower values of barometric pressure would be indicative of severe weather or storms resulting in decreased survival (Breuner et al. 2013). The negative relationship we observed may have occurred because the lower values of barometric pressure measured during our study were primarily an indicator of cloudy days with occasional rain as opposed to more intense weather patterns such as storms. The barometric pressure range for storms is commonly considered to be 98.21-98.88 kPa (Breuner et al. 2013). The minimum average barometric pressure we recorded from local weather data was 100.77 kPa, much higher than the storm range. It appears, therefore, that the relationship that we observed between DSR and barometric pressure could be a result of cloudy, but not stormy, days having a positive effect on DSR until a threshold in barometric pressure is reached beyond which conditions (e.g., sun and heat associated with higher kPa) may negatively affect survival. For example, the shading effect of clouds could reduce temperature and sun exposure of eggs and chicks during the summer breeding season and therefore increase their daily survival (Amat and Masero 2004; Robinson and Dindo 2011; Muzaffar et al. 2012).

Figure 3.

Relationships of daily survival rate of clutches with: (a) maximum nest temperature (29.64-57.66 °C); (b) average barometric pressure (range 101.53-101.66 kPa); (c) average humidity (range 75.09%-79.96%); (d) elevation category (low, high, berm); (e) distance to water (range 8.84-127.74 m); and (f) date (10 April-5 June 2018) during incubation in 2018 for Eastern Brown Pelicans (Pelecanus occidentalis carolinensis) breeding on Gaillard Island and Cat Island, Alabama, USA. Dashed lines represent 95% confidence intervals.

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Figure 4.

Relationships of daily survival rate of broods with: (a) average barometric pressure (range 101.17-102.13 kPa); and (b) average humidity (range 76.37%-90.22%) during brood-rearing of 2017 for Eastern Brown Pelicans (Pelecanus occidentalis carolinensis) breeding on Gaillard Island and Cat Island, Alabama, USA. Dashed lines represent 95% confidence intervals.

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Figure 5.

Relationships of daily survival rate of broods with: (a) average humidity (range 71.31%-85.65%); (b) nest age (1-41 days post-hatch); and (c) date (12 June-23 July 2018) during brood-rearing of 2018 for Eastern Brown Pelicans (Pelecanus occidentalis carolinensis) breeding on Gaillard Island and Cat Island, Alabama, USA. Dashed lines represent 95% confidence intervals.

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Table 3.

Summary of metrics of reproductive success from published studies or reports of Eastern Brown Pelicans (Pelecanus occidentalis carolinensis) in the Gulf of Mexico and the South Atlantic Bight, USA.

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Average humidity also consistently appeared in top performing models for DSR of clutches and broods; however, the relationship differed between clutch (nonlinear and negative) and brood (nonlinear and positive) stages. We found that humidity recorded from a local weather station often performed better in our models than nest-specific temperature variables. Humidity and temperature can be combined in a temperature-humidity index (El-Tarabany 2015; Young et al. 2018) which may reflect the heat stress experienced by an organism. During incubation, a negative relationship of nest survival with temperature and/or humidity could be caused by decreased survival of eggs due to heat stress (Sherley et al. 2011; Oswald and Arnold 2012), and our results suggest this occurred primarily above a specific threshold for Brown Pelicans during this study. In contrast, the significant positive relationship we observed between brood success and humidity in both years could occur if chicks can demonstrate an increased resilience to heat as they become capable of thermoregulation or if higher air temperatures are associated with higher humidity and these conditions promote chicks remaining drier and warmer during the frequent rainstorms in the region (Konarzewski and Taylor 1989; Hart et al. 2017).

Variables related to timing of breeding and to microhabitat structure of nests rarely had a significant effect on DSR during incubation or brood-rearing. Our observation of a decrease in DSR over time during brood-rearing and Julian date is consistent with previous studies (Antolos et al. 2006; Svagelj and Quintana 2011). However, we observed this relationship only in 2018, possibly due to the overall high reproductive success across all nests in 2017. Distance to water had a weak negative effect on DSR during incubation in 2018. Many studies of seabirds nesting on islands have found that proximity to water decreased reproductive success and recruitment, as wave activity, precipitation, and flooding from storm events increased the mortalities in nests closer to water sources (Sherley et al. 2011; Walter et al. 2013; Bonter et al. 2014). However, most Brown Pelican nests on Gaillard Island occur between the armored island perimeter and the berm, and thus appear to be relatively protected from over-wash events. For example, following Tropical Storm Cindy and Hurricanes Harvey, Irma, and Nate in 2018, we observed that vegetation and nesting material/substrate were reduced on the low-lying Cat Island and Brown Pelicans did not nest there; however, vegetation and nesting material/substrate did not appear to be similarly impacted on Gaillard Island and Brown Pelicans continued to nest there (Streker 2019).Our data suggest that the enhanced elevation, armored shoreline, and abundant shrub and nesting material on Gaillard Island may serve to reduce the effect of nest microhabitat on breeding success.

Although our study site is a regionally important colony and supports the largest number of breeding Brown Pelicans in the Gulf, extrapolation of results from any single colony is complicated by the broad nesting range of Brown Pelicans in the northern Gulf. Measures of apparent success during our study were within the range reported by Schreiber (1979) and Blus and Keahy (1978). Similarly, fledging rates from our study were also within the ranges of previous studies (Mendenhall and Prouty 1979; Mcnease et al. 1984; Walter et al. 2013; Lamb et al. 2016, Lamb et al. 2020). Thus, our data appear to represent relatively typical levels of breeding success for the region, suggesting that our results may be relevant to colonies outside the explicit study area. No single study, however, is likely to encompass the full range of factors affecting reproductive success, as factors are likely to vary among sites as well as within sites among years. Moreover, Brown Pelicans occupy a range of habitats including but not limited to xeric barrier islands in the southwest, complex estuaries in the central coast, and mangrove systems in the southeast, which likely respond differently to environmental drivers. For those reasons, and because the species continues to be a focus in the region, long-term monitoring of the species across a variety of habitats could help to improve understanding of how reproductive success responds to acute and chronic stressors (Jodice et al. 2019).

Our results suggest that DSR of clutches and broods of Brown Pelicans during our study responded more strongly to regional weather than to microhabitat features. Habitat variables that may act in synergy with storms, such as distance to water and nest elevation, improved model fit in some cases but were minimally significant, suggesting that modifying or creating islands to be more resilient to storms may enhance reproductive success of Brown Pelicans. Our data therefore indicate that the reproductive success of Brown Pelicans may be driven in whole or in part by environmental factors that operate at non-local scales and that are not within the control of management or restoration efforts. This is not to say that manageable factors (e.g., nesting habitat, elevation) should be ignored, but rather that stakeholders may want to consider the success of a management action through a broad lens that also includes the potential for unmeasured or unmanageable factors to play a role.

Acknowledgments

This research was funded by the Bureau of Ocean and Energy Management (Interagency Agreement no. M12PG00014) and the United States Geological Survey. Drs. Jeff Gleason and Dave Moran were instrumental in identifying, developing, and administering these funds. Field research was conducted with permission from the Clemson University Animal Care and Use Committee (2013-026), the U.S. Department of the Interior, Geological Survey, Bird Banding Laboratory (22408), and Alabama Department of Natural Resources. We would also like to thank the Department of Forestry and Environmental Conservation at Clemson University, Dauphin Island Sea Lab, the Buccaneer Yacht Club, and our field and lab technicians for their assistance and support. Drs. Orin Robinson and Troy Farmer provided comments on an earlier draft of this manuscript. Kathy Hixson assisted in the production of final figures. The South Carolina Cooperative Fish and Wildlife Research Unit is jointly supported by the U.S. Department of the Interior, Geological Survey, South Carolina Department of Natural Resources, and Clemson University. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Data generated during this study are available as a U.S. Geological Survey data release (Streker et al. 2020).

Literature Cited

1.

Amat, J. A. and J. A. Masero. 2004. How Kentish plovers, Charadrius alexandrines, cope with heat stress during incubation. Behavioral Ecology and Sociobiology 56: 26–33. Google Scholar

2.

Antolos, M., D. D. Roby, D. E. Lyons, S. K. Anderson and K. Collis. 2006. Effects of nest density, location, and timing on breeding success of Caspian Terns. Waterbirds 29: 465–473. Google Scholar

3.

Blus, L. J. and J. A. Keahy. 1978. Variation in reproductivity with age in the Brown Pelican. Auk 95: 128–134. Google Scholar

4.

Bonter, D. N., S. A. MacLean, S. S. Shah and M. C. Moglia. 2014. Storm-induced shifts in optimal nesting sites: a potential effect of climate change. Journal of Ornithology 155: 631–638. Google Scholar

5.

Bried, J., M. C. Magalhaes, M. Bolton, V. C. Neves, E. Bell, J. C. Pereira, L. Aguiar, L. R. Monteiro and R. S. Santos. 2008. Seabird habitat restoration on Praia Islet, Azores Archipelago. Ecological Restoration 27: 27–36. Google Scholar

6.

Breuner, C. W., R. S. Sprague, S. H. Patterson and H. A. Woods. 2013. Environment, behavior, and physiology: do birds use barometric pressure to predict storms? Journal of Experimental Biology 216: 1932–1990. Google Scholar

7.

Brooks, G. L., F. J. Sanders, P. D. Gerard and P. G. R. Jodice. 2013. Daily survival rate for nests and chicks of Least Terns (Sternula antillarum) at natural nest sites in South Carolina. Waterbirds 36: 1–10. Google Scholar

8.

Burnham, K. P. and D. R. Anderson. 2002. Model Selection and Multi-model Inference: A Practical Information-theoretic Approach. 2nd ed., Springer-Verlag, New York, New York, USA. Google Scholar

9.

Deepwater Horizon Natural Resource Damage Assessment Trustees. 2017. Deepwater Horizon Oil Spill Natural Resource Damage Assessment: Strategic Framework for Bird Restoration Activities. Deepwater Horizon Natural Resource Damage Assessment Trustees, Washington, D.C.  http://www.gulfspillrestoration.noaa.gov/restoration-planning/gulf-plan , 10 March 2019. Google Scholar

10.

Dickey, M. H., G. Gauthier and M. C. Cadieux. 2008. Climatic effects on the breeding phenology and reproductive success of an arctic-nesting goose species. Global Change Biology 14: 1973– 1985. Google Scholar

11.

Fallon, J. A., E. P. Smith, N. Schoch, J. D. Paruk, E. A. Adams, D. C. Evers, P. G. R. Jodice, C. Perkins, S. Schulte and W. A. Hopkins. Hematological indices of injury to lightly oiled birds from the Deepwater Horizon Oil Spill. Environmental Toxicology and Chemistry 37: 451–461. Google Scholar

12.

Fieberg, J. and D. H. Johnson. 2015. MMI: Multi-model inference or models with management implications? Journal of Wildlife Management 79: 708–718. Google Scholar

13.

Frederiksen, M., F. Daunt, M. P. Harris and S. Wanless. 2008. The demographic impact of extreme events: stochastic weather drives survival and population dynamics in a long-lived seabird. British Ecological Society 77: 1020–1029. Google Scholar

14.

Guttery, M. R., D. K. Dahlgren, T. A. Messmer, J. W. Connelly, K. P. Reese, P. A. Terletzky, N. Burkepile and D. N. Koons. 2013. Effects of landscape-scale environmental variation on greater sage-grouse chick survival. PLoS ONE 8: e65582. Google Scholar

15.

Haney, C. J., H. J. Geiger and J. W. Short. 2014. Bird mortality from the Deepwater Horizon oil spill. II. Carcass sampling and exposure probability in the coastal Gulf of Mexico. Marine Ecology Progress Series 513: 239–203. Google Scholar

16.

Hart, L. A., C. T. Downs and M. Brown. Keeping it regular: Development of thermoregulation in four tropical seabird species. Journal of Thermal Biology 64: 19–25. Google Scholar

17.

Jodice, P. G., D. D. Roby, K. R. Turco, R. M. Suryan, D. B. Irons, J. F. Piatt, M. T. Schultz, D. G. Rosenau, A. B. Kettle and J. A. Anthony. 2006. Assessing the nutritional stress hypothesis: relative influence of diet quantity and quality on seabird productivity. Marine Ecology Progress Series 325: 267–279. Google Scholar

18.

Jodice, P. G. R., E. M. Adams, J. S. Lamb and Y. G. Satgé. 2019. Strategic Bird Monitoring Guidelines for the northern Gulf of Mexico: Seabirds. Pages 133–172 in Strategic Bird Monitoring Guidelines for the northern Gulf of Mexico ( R. R. Wilson, A. M. V. Fournier, J. S. Gleason, J. E. Lyons and M. S. Woodrey, Eds.). Mississippi Agricultural and Forestry Experiment Station Research Bulletin 1228, Mississippi State University, Mississippi, USA. Google Scholar

19.

Konarzwski, M. and J. R. E. Taylor. 1989. The influence of weather conditions of growth of Little Auk (Alle alle) chicks. Scandinavian Journal of Ornithology 20: 112–116. Google Scholar

20.

Laake, J. and E. Rextad. 2014. RMark - an alternative approach to building linear models in MARK. Pages C1–C113 in Program MARK: a Gentle Introduction, 12th ed. ( E. Cooch and G. C. White, Eds.). Colorado State University, Fort Collins, Colorado, USA.  http://www.phidot.org/software/mark/docs/book/ , accessed 15 August 2018. Google Scholar

21.

Lamb, J. S. 2016. Ecological drivers of Brown Pelican movement patterns and reproductive success in the Gulf of Mexico. Ph.D. Dissertation. Clemson University, Clemson, South Carolina, USA. Google Scholar

22.

Lamb, J. S., K. M. O'Reilly and P. G. R. Jodice. 2016. Physical condition and stress levels during early development reflect nutrition and predict nestling survival in a nearshore seabird. Conservation Physiology 4: cow060 Google Scholar

23.

Lamb, J. S., Y. G. Satgé and P. G. R. Jodice. 2017. Diet composition and provisioning rates of nestlings determine reproductive success in a subtropical seabird. Marine Ecology Progress Series 581: 149–164. Google Scholar

24.

Lamb, J. S., Y. G. Satgé, R. A. Streker, P. G. R Jodice. 2020. Ecological drivers of Brown Pelican movement patterns, health, and reproductive success in the Gulf of Mexico. OCS Study BOEM-2020-036. U.S. Dept. of the Interior, Bureau of Ocean Energy Management, Gulf of Mexico OCS Region, New Orleans, Louisiana, USA. Google Scholar

25.

Louisiana Trustee Implementation Group. 2019. Final Phase II Restoration Plan/Environmental Assessment #1.1: Queen Bess Island Restoration, Baton Rouge, Louisiana. Deepwater Horizon Natural Resources Damage Assessment Trustee Council, Washington, D.C.  https://www.gulfspillrestoration.noaa.gov/2019/03/louisiana-trustees-release-final-restoration-plan-queen-bess-island , accessed 10 April 2020. Google Scholar

26.

Mcnease, L., T. Joanen, D. Richard, J. Shepard and S. A. Nesbitt. 1984. The brown pelican restocking program in Louisiana. Transactions of the Southeastern Association of Fish and Wildlife Agencies 36: 165–173. Google Scholar

27.

Mendenhall, V. M. and R. M. Prouty. 1979. Recovery of breeding success in a population of Brown Pelicans. Waterbirds 2: 65–70. Google Scholar

28.

Muzaffar, S. B., R. Gubiani and S. Benjamin. 2012. Reproductive performance of the Socotra Cormorant Phalacrocorax nigrogularis on Siniya Island, United Arab Emirates: planted trees increase hatching success. Waterbirds 35: 626–631. Google Scholar

29.

Murphy, E. C., A. M. Springer and D. G. Roseneau. 1991. High annual variability in reproductive success of black-legged kittiwakes at colony in western Alaska. Journal of Animal Ecology 60: 515–534. Google Scholar

30.

National Weather Service. 2019. Mobile, Mobile Downtown Airport, Mobile, Atlanta, Georgia. National Oceanic and Atmospheric Administration, National Weather Service, Silver Spring, Maryland, USA.  https://www.weather.gov/wrh/Climate?wfo=mob , accessed 10 October 2018. Google Scholar

31.

Oswald, S. A. and J. M. Arnold. 2012. Direct impact of climatic warming on heat stress in endothermic species: seabirds as bioindicators of changing thermoregulatory constraints. Integrative Zoology 7: 121–136. Google Scholar

32.

Ramos, J. A., A. M. Maul, V. Ayrton, I. Bullock, J. Hunter, J. Bowler, G. Castle, R. Mileto and C. Pacheco. 2002. Influence of local and large-scale weather events and timing of breeding on tropical roseate tern reproductive parameters. Marine Ecology Progress Series 243: 271–279. Google Scholar

33.

Ranglack, G. S., R. A. Angus and K. R. Marion. 1991. Physical and Temporal factors influencing breeding success of Cattle Egrets (Bubulcus ibis) in a west Alabama colony. Colonial Waterbirds 14: 140–149. Google Scholar

34.

R Core Team. 2016. R: a language and environment for statistical computing v. 3.3.2. R Foundation for Statistical Computing, Vienna, Austria.  https://www.Rproject.org/ , accessed 15 August 2018. Google Scholar

35.

Robinson, O. J. and J. J. Dindo. 2008. Survey for colonial nesting birds on seven islands of coastal Alabama. Alabama Birdlife 54: 37–43. Google Scholar

36.

Robinson, O. J. and J. J. Dindo. 2011. Egg success, hatching success, and nest-site selection of Brown Pelicans, Gaillard Island, Alabama, USA. Wilson Journal of Ornithology 123: 386–390. Google Scholar

37.

Schreiber, R. W. 1979. Reproductive performance of the Eastern Brown Pelican. Science 317: 1–43. Google Scholar

38.

Shields, M. 2014. Brown Pelican (Pelecanus occidentalis). V. 2.0. in The Birds of North America ( P. G. Rodewald, Ed.). Cornell Lab of Ornithology, Ithaca, New York, USA.  https://doi.org/10.2173/bna.609 , accessed 11 April 2020. Google Scholar

39.

Sherley, R. B., K. Ludynia, L. G. Underhill, R. Jones and J. Kemper. 2011. Storms and heat limit the nest success of Bank Cormorants: implications of future climate change for a surface-nesting seabird in southern Africa. Journal of Ornithology 153: 441– 455. Google Scholar

40.

Sovada, M. A., L. D. Igl, P. J. Pietz and A. J. Bartos. 2014. Influence of climate change on productivity of American White Pelicans, Pelecanus erythrorhynchos. PLoS ONE 9: e83430. Google Scholar

41.

Streker, R. 2019. Reproductive ecology and diet of Brown Pelicans in the Gulf of Mexico. M.s. Thesis. Clemson University, Clemson, South Carolina, USA. Google Scholar

42.

Streker, R., J. S. Lamb, Y. G. Stagé and P. G. R. Jodice. 2020. Reproductive Physiology of Brown Pelican Along the Coast of Alabama, 2017-2018: data release. U.S. Department of the Interior, Geological Survey, Reston, Virginia, USA.  https://doi.org/10.5066/P9AB53QZ , accessed 13 April 2020. Google Scholar

43.

Svagelj, W. S. and F. Quintana. 2011. Breeding performance of the Imperial Shag (Phalacrocorax atriceps) in relation to year, laying date, and nest location. Emu 111: 162–165 Google Scholar

44.

El-Tarabany, M. S. 2016. Impact of temperature-humidity index on egg-laying characteristics and related stress and immunity parameters of Japanese quails. International Journal of Biometeorology 60: 957–964. Google Scholar

45.

Walsberg, G. E. and C. A. Schmidt. 1992. Effects of variable humidity on embryonic development and hatching success of Mourning Doves. Auk 109: 309–314. Google Scholar

46.

Walter, S. T., M. R. Carloss, T. J. Hess and P. L. Leberg. 2013. Hurricanes, habitat degradation, and land loss effects on Brown Pelican nesting colonies. Journal of Coastal Research 29: 187–195. Google Scholar

47.

Walter, S. T., M. R. Carloss, T. J. Hess and P. L. Leberg. 2014. Demographic trends of Brown Pelicans in Louisiana before and after the Deepwater Horizon oil spill. Journal of Field Ornithology 85: 421–429. Google Scholar

48.

White, G. C. and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals. Bird Study 46: 120–139. Google Scholar

49.

Wilson, R. R., A. M. V. Fournier, J. S. Gleason, J. E. Lyons and M.S. Woodrey (eds.). 2019. Strategic Bird Monitoring Guidelines for the northern Gulf of Mexico. Mississippi Agricultural and Forestry Experiment Station Research Bulletin 1228, Mississippi State University, Mississippi State, Mississippi, USA. Google Scholar

50.

Young, A. H., K. R. Knapp, A. Inamdar, W. B. Rossow and W. Hankins. 2018. The international satellite cloud climatology project, H-Series climate data record product. Earth System Science Data 10:583–593. Google Scholar
Rochelle A. Streker, Juliet S. Lamb, John Dindo, and Patrick G. R. Jodice "Fine-scale Weather Patterns Drive Reproductive Success in the Brown Pelican," Waterbirds 44(2), 153-166, (23 December 2021). https://doi.org/10.1675/063.044.0202
Received: 14 April 2020; Accepted: 25 November 2020; Published: 23 December 2021
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KEYWORDS
Brown Pelican
daily survival rate
Gulf of Mexico
Pelecanus occidentalis carolinensis
weather
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