SciELO - Scientific Electronic Library Online

 
vol.49 suppl.1Somatic growth rates of the Hawksbill Turtle, Eretmochelys imbricata, in Gorgona Natural National Park, Colombia, between 2004 and 2018Community structure of turf algae in interactions with massive corals in Tayrona National Natural Park, Colombian Caribbean author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Boletín de Investigaciones Marinas y Costeras - INVEMAR

Print version ISSN 0122-9761

Bol. Invest. Mar. Cost. vol.49  supl.1 Santa Marta Dec. 2020  Epub Sep 04, 2021

https://doi.org/10.25268/bimc.invemar.2020.49.suplesp.1046 

Research Articles

Association of Sea Surface Temperature and the abundance of the Brown Booby (Sula leucogaster) according to the state of development in the Gorgona National Natural Park

Alejandro Perlaza-Gamboa1  * 
http://orcid.org/0000-0003-0351-7905

Alan Giraldo2 
http://orcid.org/0000-0001-9182-888X

Luis Fernando Payán3 

Felipe A. Estela4 

1Departamento de Biología, Facultad de Ciencias Naturales y Exactas, Universidad del Valle. alejandro.perlaza@correounivalle.edu.co

2Instituto de Investigaciones en Ciencias del Mar y Limnología (Incimar), Universidad del Valle, Cali, Colombia. alan.giraldo@correounivalle.edu.co

3Estación Científica Henry von Prahl, Parque Nacional Natural Gorgona, Parques Nacionales Naturales de Colombia, Cali, Colombia. estacioncientificagorgona@gmail.com

4Departamento de Ciencias Naturales y Matemáticas, Pontificia Universidad Javeriana, Cali, Colombia. felipe.estela@javerianacali.edu.co


ABSTRACT

Variation in the physicochemical conditions of the sea can influence the distribution and abundance of seabirds by affecting the trophic structure of the pelagic environment. For this reason, we aimed to evaluate the association between the abundance of three developmental stages (chicks, juveniles, and adults) of the Brown Booby (Sula leucogaster etesiaca) and the sea surface temperature (SST) and its thermal anomaly (ANOM) in Gorgona Island, Colombian Pacific. These trends were assessed by performing cross-correlations and generalized linear models. Each developmental stage showed a different abundance tendence linked to SST and ANOM variation. It is suggested that these trends are due to the fact that increased sea temperature may be associated with reduced abundance and availability of prey resources. Under these conditions, adults tend to decreased the effort invested in parental care and even reduce the food supply to dependent juveniles and chicks to increase their own survival. These trends may have been associated with a breeding regime that allows fledglings to achieve independence from parents during the period of greatest availability of prey.

KEYWORDS: time delay; prey; Brown Bobby; survival; sea surface temperature

RESUMEN

La variación de las condiciones fisicoquímicas del mar puede influir en la distribución y la abundancia de las aves marinas al afectar la estructura trófica del ambiente pelágico. Por ello se pretendió evaluar la asociación entre la abundancia de tres estados de desarrollo (pollos, juveniles y adultos) del Piquero Café (Sula leucogaster etesiaca) y la variación de la temperatura superficial del mar (TSM) y su anomalía térmica (ANOM) en isla Gorgona, Pacífico colombiano. Estas tendencias fueron evaluadas por medio de correlaciones cruzadas y modelos lineales generalizados. En cada estado de desarrollo la abundancia presentó una tendencia diferente ante la variación de la TSM o ANOM. Se sugiere que dichas tendencias se deben a que el incremento de la temperatura del mar podría estar asociado con una menor abundancia y disponibilidad de recursos presa. Bajo estas condiciones, los adultos tienden a disminuir el esfuerzo invertido en el cuidado parental e, incluso, reducen el suministro de alimento a juveniles dependientes y pollos para aumentar su propia supervivencia. Es posible que estas tendencias hayan estado asociadas con un régimen reproductivo que les permita a los volantones alcanzar la independencia de los padres durante el periodo con mayor disponibilidad de alimento.

PALABRAS CLAVE: desfase temporal; presas; piquero café; supervivencia; temperatura superficial del mar

INTRODUCTION

Continuous seabird monitoring efforts allow, among other things, to relate population trends to variation in oceanographic conditions (Gaston et al., 2009; Grémillet and Boulinier, 2009; Humphries, 2015). For example, it has been established that changes in the conditions of sea surface temperature (SST) can affect the reproduction and survival of seabirds, by changing the trophic structure of the pelagic environment, due to the alteration in food availability and quality of their prey (Schreiber, 2002; Frederiksen et al., 2006; Tompkins et al., 2017; Champagnon et al., 2018). However, the response to climate change appears to be related to locality, species, sex, and developmental stage (Anderson, 1989; Maness and Anderson, 2013; Champagnon et al., 2018). For example, the survival of juveniles of the Blue-footed Booby (Sula nebouxii) is reduced during the warm phase of the ENSO (El Niño-Southern Oscillation) (Oro et al., 2010), while the number of immature individuals of the Black-browed Albatross (Thalassarche melanophris) increases with increasing SST (Pardo et al., 2017).

The Gorgona National Natural Park (GNNP) has been developing the longest-running seabird monitoring program in Colombia, started in 2002 (Estela et al., 2010). During this monitoring, information on the presence, abundance, and reproductive status of four species of seabirds recurrently sighted in the GNNP (Suliformes and Pelecaniformes) has been continuously recorded (Cadena-López and Naranjo, 2010; Perlaza-Gamboa et al., 2020). Among them is the Brown Booby (Sula leucogaster etesiaca), an endemic subspecies of the American humid tropical Pacific (Ospina-Álvarez, 2004), resident on Gorgona Island where the largest population is located with a colony of approximately 300 individuals and 100 reproductive pairs (Cadena-López and Naranjo, 2010; Estela et al., 2016). This subspecies is considered as threatened in the country (Renjifo et al., 2016).

Considering that the variability of oceanographic conditions associated with GNNP are influenced by ENSO (Blanco, 2009) and this has been identified as a relevant factor for the survival and reproductive aspects of other booby species in the Eastern Tropical Pacific (Anderson, 1989; Ribic et al., 1992; Mauck and Grubb, 1995; Ancona et al., 2012) and on Gorgona Island (Perlaza-Gamboa et al., 2020), we evaluate the temporal dynamics of the Brown Booby colony in this locality, in order to answer the following research question “Does the sea surface temperature affect the temporal variation in the abundance of the different development stages of the Brown Booby (Sula leucogaster etesiaca) on the Gorgona Island?”. To do this, we start with the analysis of the records of the abundance of adults, juveniles and chicks of this species carried out during the monitoring of seabirds in the GNNP from 2002 to 2018, as well as the sea surface temperature (SST) and thermal anomaly (ANOM) in this locality.

STUDY AREA

Within the delimited conservation area for the Gorgona National Natural Park (GNNP), are the Gorgona and Gorgonilla islands (2˚ 55′ 45″-3˚ 00′ 55″ N and 78˚ 09′ 00″-78˚ 14′ 30″ W), located approximately 30 km from the continent (Diaz et al., 2001; Giraldo et al., 2014a). In the extreme north of Gorgona and around Gorgonilla there are a series of emerged rocky islets and promontories, in which the Brown Booby builds its nests (Ospina-Álvarez, 2004; Cadena-López and Naranjo, 2010). These islets have variable shapes and inclinations. The boobies are capable of nesting on land with slopes of less than 10° and up to 90° (Ospina-Álvarez, 2004). The islets may present some vegetation cover, mainly herbaceous, although the nesting sites can be established in parts of the islet devoid of vegetation at an average height of 8.9 m.a.s.l. (Ospina-Álvarez, 2004).

The tide is semi-diurnal, with a height range between 4 and 5 m (Diaz et al., 2001; IDEAM, 2019). Precipitation levels greater than 6000 mm/year are recorded, with higher records between May and November and lower from December to April (Blanco, 2009). Regarding the characteristics of the water column of the pelagic environment, a cold period of high salinity has been reported between January and April, during which the thermocline is located at 7 m depth, and a warm period of low salinity between May and December, during which the thermocline is more than 40 m deep (Giraldo et al., 2008).

MATERIALS AND METHODS

The information used for this research corresponded to the monthly abundance records of Brown Booby carried out by trained officials of the GNNP, between 2002 and 2018, through visual censuses along a predetermined route within the framework of the seabird monitoring program. of this protected area (Figure 1). These records are made on two consecutive days of the first week of each month. Detailed information on the methodology associated with this monitoring program can be obtained in Payán (2016) and Perlaza-Gamboa et al. (2020).

Figure 1 Generalities of the monitoring of seabirds of the Gorgona NPN, Colombian Pacific. A) Route taken during the monitoring. B) Example of an islet in the northern sector of the Island. C) Female and chick of the Brown Booby (Sula leucogaster etesiaca). Photographs: Felipe A. Estela. 

Each individual observed was assigned to one of three stages of development defined according to the characteristics of their plumage: Chicks were identified by their characteristic white down, juveniles by presenting a general grayish-brown coloration with dark brown spots, and adults by the contrast between the dark brown color of the head, neck, and back, with the white of the lower chest and belly (Hilty and Brown, 2001; Ospina-Álvarez, 2004). The abundances were standardized by dividing the number of individuals observed by the total distance traveled in each of the samplings. To give uniformity to the abundance data, only the sampling events in which the two observation days were carried out were considered for the numerical analysis. The chicks abundances recorded since 2002 were used since their identification was always possible. However, during the first years of sampling, it was not discerned between adult and juvenile individuals, so to analyze these two stages of development, the data obtained from 2011 were used, the year from which it began to differentiate between these two categories. Data from individuals with unidentified developmental status were not used. For the descriptive analysis of these data, the median was used as the central tendency parameter and the maximum and minimum abundance as dispersion parameters, to reduce the influence of atypical data and because they were discrete data.

The Gorgona Island SST data were obtained from the monthly satellite images recorded by the MODIS-Aqua sensor of the Ocean Biology Processing Group (OBPG), at the CPC16 station of the ERFEN sampling mesh (3° 0′ 0″ N-78° 0′ 0″ W) (OBPG, 2015). The thermal anomaly (ANOM) was calculated by subtracting the monthly historical average for the period 2002-2018 from the monthly time series of the SST.

To establish the time lag of the possible association between temperature and the abundance of chicks, adults, and juveniles, a cross-correlation was implemented between the monthly abundance records with the SST and the ANOM of Gorgona Island. The greatest lag (Lag) allowed for chicks was four months since it is the period that includes the incubation period plus the time it takes for the chicks to grow until they are visible in the nest (Nelson, 1978; Ospina-Álvarez, 2004). For the juveniles, the greatest lag allowed was seven months, which corresponds, on average for the species, to the time from incubation to the feeding of fledglings by the parents (Nelson, 1978; Ospina-Álvarez, 2004). Finally, for adults, the maximum lag allowed was 12 months, since this period completely covers the variation in their abundance. The strength of the correlation was measured with the autocorrelation function (ACF), which for this study acquires a value of -1 for the highest negative correlation and 1 for the highest positive correlation.

A generalized linear model (GLM) was developed for each stage of development independently, to explain the possible relationship between abundance and SST and ANOM, that presented significant correlations, taking into account the time lag found in the cross-correlation. The quasipoisson distribution was used because count data were evaluated and there was no overdispersion. The analyzes and Figures were made in the R program (R Core Team, 2018). The ggplot2 package was used for the Figures (Wickham, 2016), astsa for the cross-correlation (Stoffer, 2017) and MASS for the models (Venables and Ripley, 2002), in addition to other functions to organize the data (Wickham, 2007; Fox and Weisberg, 2011; Trapletti and Hornik, 2018).

RESULTS

During the study period, 184 monthly records of Brown Booby chicks and 92 monthly records of adults and juveniles were made. The abundance of adults presented the greatest variation, with a monthly median of 5.70 ind/km and a maximum and minimum of 11.02 and 2.00 ind/km respectively. Chicks presented a monthly median of 0.22 ind/km (minimum = 0 ind/km and maximum = 2.62 ind/km) and the juveniles 0.42 ind/km (minimum = 0 ind/km and maximum = 1.54 ind/km), with higher records, in both cases, during the last semester (Figure 2).

Figure 2 Monthly variation of the abundance of A) adults, B) chicks and C) juveniles of the Brown Booby (Sula leucogaster etesiaca) on Gorgona Island, Colombian Pacific. The box represents the median and 25% and 75% percentiles. The bars represent the non-outlier maximum and minimum value and the points correspond to outliers. 

The sea surface temperature of Gorgona Island presented a median equal to 27.26 °C, with records between 25.47 °C and 28.05 °C. The adults did not present any significant correlation with SST or ANOM. In contrast, the abundance of juveniles showed a significant correlation with ANOM and SST, with a time lag of two and one months, respectively. This suggests that the number of juveniles is associated with the ANOM registered two months before and with the SST of the previous month. Finally, the abundance of chicks was correlated with the ANOM without any time lag, and with the SST reported four months earlier (Table 1).

Table 1 Cross-correlation between the monthly abundance of chicks, juveniles, and adults of the Brown Booby (Sula leucogaster etesiaca) with the sea surface temperature (SST) of Gorgona Island (Gor) and its thermal anomaly (ANOM). ACF = strength of correlation. ANOM = thermal anomaly. Lag = time lag of correlation measured in months. NS = nonsignificant correlation. 

According to the generalized linear model (GLM) developed between the abundance of juveniles with the ANOM (coefficient = 0.33; P < 0.001) and the SST (coefficient = 0.52; P < 0.001), considering the respective lag (Lag), the number of juveniles tends to decrease with the increase of both thermal variables (Figure 3A and 3B). On the other hand, the abundance of chicks tends to decrease with the increase in ANOM (coefficient = 0.58; P = 0.017) (Figure 3C), but increases with increasing SST (coefficient = 2.08; P < 0.001) (Figure 3D).

Figure 3 Relationship of the abundance of juveniles and chicks of the Brown Booby (Sula leucogaster etesiaca) with the thermal anomaly (ANOM) (A and C) and the sea surface temperature (SST) (B and D) of Gorgona Island, Colombian Pacific. The shaded area represents the 95% confidence interval. 

DISCUSSION

The abundance of chicks and juveniles Brown Boobies associated with Gorgona Island was higher in the last months of the year, probably as a consequence of the concentration of reproductive effort between July and September, a condition that was reported by Cadena-López and Naranjo (2010). However, this species on Gorgona Island exhibits reproductive activity throughout the year, with a low intra-annual variation in population size (Ospina-Álvarez, 2004; Cadena-López and Naranjo, 2010; Perlaza-Gamboa et al., 2020). In this reproductive regime, egg laying mainly occurs between June and August, with an incubation period between 40 and 44 days, followed by a period between one and three months in which the chicks grow until they are visible and acquire the characteristic white down, that at the end of this period they begin to molt to a brown plumage (Nelson, 1978). Once these individuals make the first flight, at approximately 96 days of age (Nelson, 1978; Ospina-Álvarez, 2004), they are fed by the parents for the next three to eight weeks, although this period can be extended depending on prey availability (Schreiber and Norton, 2002). This system encourages individuals to acquire independence from their parents during the first months of the year, during which time greater productivity has been reported in the pelagic environment near Gorgona Island (Giraldo et al., 2014b).

This reproductive strategy has been reported for other species of seabirds, which begin to reproduce when there is less productivity in the ecosystem and their prey is less available, but it allows the juveniles to achieve independence from their parents when there is the greatest availability of prey. (Passuni et al., 2016, 2018). In general, this strategy is carried out, mainly, by birds whose food is widely distributed, such as seabirds (Nelson, 1978; Furness and Monaghan, 1987; Vilchis et al., 2006). In addition, it is worth mentioning that the four-month lag in the positive correlation between the abundance of chicks and the SST suggests that the greater abundance observed in October and November is influenced by the temperatures registered in the middle of the year, at which time the transition between the period of highest to lowest productivity occurs in the Eastern Tropical Pacific (Pennington et al., 2006) and probably in the surroundings of Gorgona Island (Giraldo et al., 2014b). This pattern is similar to that observed in the Mexican tropical Pacific, where the reproductive period was mainly associated with the warmest and least productive time of the year, but coincides with the increase in the availability of migratory warm-water prey (Hernández-Vázquez et al., 2017). For these reasons, to understand the reproductive regime of the Brown Booby on Gorgona Island, it is necessary to deepen the knowledge about the intra-annual population variation of its prey resources, as well as to determine the period in which most of the offspring acquire independence from parents.

It is likely that the lower productivity associated with warmer waters, and greater precipitation between May and December (Diaz et al., 2001; Giraldo et al., 2014b), causes greater loss of chicks, as has been reported for other seabirds in the Eastern Pacific (Jaksic and Fariña, 2010). This could trigger more frequent second clutches by reproductive pairs (Nelson, 1978), resulting in a greater number of chicks observed in recent months. On the other hand, the negative correlation found between the abundance of chicks and the thermal anomaly suggests that these individuals are affected by changes in sea temperature, possibly through the decrease in the food provided by their parents. For example, for some seabirds, increases in sea temperature and decreases in reproductive success have been associated with altered sea productivity and prey availability (Ancona et al., 2011; Furness, 2016). The lower availability of prey resources related to warmer waters may explain the decrease in the abundance of juvenile Brown Booby when SST and ANOM increase in the pelagic environment of Gorgona Island.

During adverse conditions, such as low prey availability, some long-lived species, such as the Brown Booby (Hennicke et al., 2012) generally tend to minimize individual costs of reproduction (Mauck and Grubb, 1995). For example, adults reduce the effort invested in parental care and the supply of food to dependent juveniles or chicks, to increase their survival, but decrease reproductive success (Maness and Anderson, 2013). This strategy may explain why no significant correlation was observed between adults and SST or ANOM, but it was observed in chicks and juveniles. Furthermore, the abundance of this booby described by Perlaza-Gamboa et al. (2020) could be mainly due to the decrease in the number of juveniles, possibly because the food supply was lower when the SST increased. However, this effect is likely less in species that have parental care before and after the chicks become fledglings (Stienen and Brenninkmeijer, 2002; Maness and Anderson, 2013), as is the case of the Brown Booby (Ospina-Álvarez, 2004). Nevertheless, these hypotheses must be confirmed by a study that evaluates the strategies carried out by parents during stressful conditions, and their consequences on the development and survival of their offspring before and after having achieved independence.

CONCLUSIONS

The SST and ANOM of Gorgona Island are associated with the trends observed in the population variation of chicks and juveniles of the Brown Booby, possibly through an effect on the supply of pelagic fish provided by the parents, since it is probable that these Individuals cannot meet the needs of the young, but they do manage to stay alive during times of food shortage. This is evidenced in a lower number of juveniles and chicks during the months with the greatest anomalies, which suggests that the variation in SST and ANOM may affect the reproduction of this population. Also, possibly the reproductive regime ensures that the young achieve independence from the parents when there is greater availability of prey resources.

ACKNOWLEDGEMENTS

To Ximena Zorrilla and Héctor Chirimía from the Gorgona National Natural Park (GNNP). To Julio César Herrera Carmona for his help in the construction of the SST time series and to Wilmar Alexander Torres for his recommendations for the development of statistical analyzes. To WWF and to the Calidris Association for supporting the seabird monitoring program from its inception until now. This research work was co-financed by the GNNP, the Universidad del Valle, and WWF-Colombia, and was carried out within the framework of an understanding agreement between the GNNP and the Animal Ecology research group of the Universidad del Valle. Publication 008 of the Institute of Marine Sciences and Limnology (Incimar) of Universidad del Valle

BIBLIOGRAFÍA/LITERATURE CITED

Ancona, S., S., Sánchez-Colón, C., Rodríguez, and H. ,Drummond. 2011. El Niño in the warm tropics: local sea temperature predicts breeding parameters and growth of blue-footed boobies. J. An. Ecol., 80: 799-808. https://doi.org/10.1111/j.1365-2656.2011.01821.xLinks ]

Ancona, S., I., Calixto-Albarrán, and H., Drummond. 2012. Effect of El Niño on the diet of a specialist seabird, Sula nebouxii, in the warm eastern tropical Pacific. Mar. Ecol. Progr. Ser., 462: 261-271. https://doi.org/10.3354/meps09851Links ]

Anderson, D.J. 1989. Differential responses of boobies and other seabirds in the Galapagos to the 1986-87 El Nino-Southern Oscillation event. Mar. Ecol. Progr. Ser., 52: 209-2016. [ Links ]

Blanco, J.F. 2009. The hydroclimatology of Gorgona Island: seasonal and Enso-Rel. patterns. Actual. Biol., 1(91): 111-121. [ Links ]

Cadena-López, G. y L.G., Naranjo. 2010. Distribución, abundancia y reproducción de las aves marinas residentes en el Parque Nacional Natural Gorgona, Colombia. Bol. SAO, 20: 22-32. [ Links ]

Champagnon, J., J. D. ,Lebreton, H., Drummond, and D. J. ,Anderson. 2018. Pacific decadal and El Niño oscillations shape survival of a seabird. Ecology, 99(5): 1063-1072. https://doi.org/10.1002/ecy.2179Links ]

Díaz, J.M., J.H. ,Pinzón, A.M., Perdomo, L.M., Barrios y M., López-Victoria. 2001. Generalidades. 17-26. En Barrios, L. M. y M., Lopez-Victoria (Eds.), Gorgona marina: contribución al conocimiento de una isla única. Ser. Publ. Esp. Invemar, (7). [ Links ]

Estela, F.A., M., López Victoria, L.F., Castillo y L.G., Naranjo. 2010. Estado del conocimiento sobre aves marinas en Colombia después de 110 años de investigación. Bol. SAO, 20: 2-21. [ Links ]

Estela, F.A., G., Cadena y J., Lasso-Zapata. 2016. Sula leucogaster. 139-143. En Renjifo, L.M., Á. M., Amaya-Villarreal, J., Burbano-Girón y J., Velásquez-Tibatá (Eds.). Libro rojo de aves de Colombia. Volumen II: ecosistemas abiertos, secos, insulares, acuáticos continentales, marinos, tierras altas del Darién y Sierra Nevada de Santa Marta y bosques húmedos del centro, norte y oriente del país. Pont. Univ. Javeriana e Inst. Alexander von Humboldt, Bogotá. 563 p. [ Links ]

Fox, J. and S., Weisberg. 2011. An R Companion to Applied Regression [software]. Thousand Oaks: Sage. http://socserv.socsci.mcmaster.ca/jfox/Books/Companion.04/04/2019.Links ]

Frederiksen, M., M., Edwardst, A.J., Richardson, N.C. ,Halliday, and S., Wanless. 2006. From plankton to top predators: bottom-up control of a marine food web across four trophic levels. J. An. Ecol., 75(6): 1259-1268. https://doi.org/10.111 1l/j.1365-2656.2006.01Links ]

Furness, R.W. 2016. Impacts and effects of ocean warming on seabirds. 271-288. En Laffoley, D. y J. M., Baxter (Eds.). Explaining ocean warming: causes, scale, effects and consequences. IUCN, Gland, Switzerland. [ Links ]

Furness, R.W. and P., Monaghan. 1987. Seabird ecology. Chapman & Hall, New York. [ Links ]

Gaston, A.J., D.F., Bertram, A. W., Boyne, J.W. ,Chardine, G. ,Davoren, A.W., Diamond, A., Hedd, W.A., Montevecchi, J.M., Hipfner, M.J.F. ,Lemon, M.L., Mallory, J.F., Rail, and G.J., Robertson. 2009. Changes in Canadian seabird populations and ecology since 1970 in relation to changes in oceanography and food webs. Environ. Rev., 17: 267-286. https://doi.org/10.1139/A09-013Links ]

Giraldo, A., E., Rodríguez-Rubio y F. ,Zapata. 2008. Condiciones oceanográficas en isla Gorgona, Pacífico oriental tropical de Colombia. Latin Am. J. Aq. Res., 36(1): 121-128. https://doi.org/10.3856/vol36-issue1-fulltext-12Links ]

Giraldo, A., M.C., Díaz-Granados y C.F., Gutiérez-Landázuri. 2014a. Isla Gorgona, enclave estratégico para los esfuerzos de conservación en el Pacífico Oriental Tropical. Rev. Biol. Trop., 62: 1-12. [ Links ]

Giraldo, A., B., Valencia, J.D., Acevedo y M., Rivera. 2014b. Fitoplancton y zooplancton en el área marina protegida de Isla Gorgona, Colombia, y su relación con variables oceanográficas en estaciones lluviosa y seca. Rev. Biol. Trop., 62: 117-132. [ Links ]

Grémillet, D. and T., Boulinier. 2009. Spatial ecology and conservation of seabirds facing global climate change: a review. Mar. Ecol. Progr. Ser., 391(2): 121-137. https://doi.org/10.3354/meps08212Links ]

Hennicke, J.C., B., King, D., Drynan, L.J., Hardy, A., Stokes, and S. ,Taylor. 2012. New life-span records of the Brown Booby Sula leucogaster. Mar. Ornithol., 40(2), 125-126. [ Links ]

Hernández-Vázquez, S., E., Mellink, J.A. ,Castillo-Guerrero, R., Rodríguez-Estrella, J.Á., Hinojosa-Larios y V.H., Galván-Piña. 2017. Ecología reproductiva del bobo café (Sula leucogaster) en tres islas del Pacífico Tropical mexicano. Ornitol. Neotrop., 28: 57-66. [ Links ]

Hilty, S.L. y W.L., Brown. 2001. Guía de las aves de Colombia. Princeton, New Jersey. 1040 p. [ Links ]

Humphries, G.R.W. 2015. Estimating regions of oceanographic importance for seabirds using a-spatial data. PLoS ONE, 10(9): e0137241. https://doi.org/10.1371/journal.pone.0137241Links ]

IDEAM. 2019. Pronóstico de pleamares y bajamares Costa Caribe colombiana 2020. Inst. Hidrol. Meteorol. Est. Amb., Bogotá. 135 p. [ Links ]

Jaksic, F.M. and J.M., Fariña. 2010. El Niño and the birds: a resource-based interpretation of climatic forcing in the southeastern Pacific. An. Inst. Patagonia, 38(1): 121-140. https://doi.org/10.4067/s0718-686x2010000100009Links ]

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

Mauck, R.A. and T.C., Grubb. 1995. Petrel parents shunt all experimentally increased reproductive costs to their offspring. An. Behav., 49: 999-1008. https://doi.org/10.1006/anbe.1995.0129Links ]

Nelson, J.B. 1978. The Sulidae, gannets and boobies. Oxford University Press, Oxford. 1012 p. [ Links ]

OBPG. 2015. MODIS aqua level 3 SST thermal IR monthly 4km daytime v2014.0. https://podaac.jpl.nasa.gov/dataset/MODIS_AQUA_L3_SST_THERMAL_MONTHLY_4KM_DAYTIME_V2014.0. 21/01/2019.Links ]

Oro, D., R. ,Torres, C., Rodríguez, and H., Drummond. 2010. Climatic influence on demographic parameters of a tropical seabird varies with age and sex. Ecology, 91(4): 1205-1214. [ Links ]

Ospina-Álvarez, A. 2004. Ecología reproductiva y colonialidad del piquero café Sula leucogaster (Aves: Sulidae), en el PNN Gorgona, Pacífico colombiano. Tesis Biol., Univ. Valle, Cali. 116 p. [ Links ]

Pardo, D., S. ,Jenouvrier, H., Weimerskirch, and C., Barbraud. 2017. Effect of extreme sea surface temperature events on the demography of an age-structured albatross population. Phil. Trans. Royal Soc. B. Biol. Sci., 372: 20160. https://doi.org/10.1098/rstb.2016.0143Links ]

Passuni, G., C., Barbraud, A., Chaigneau, H., Demarcq, J., Ledesma, A., Bertrand, R. ,Castillo, A., Perea, J. ,Mori, V. A., Viblanc, J., Torres-Maita, and S., Bertrand. 2016. Seasonality in marine ecosystems: Peruvian seabirds, anchovy, and oceanographic conditions. Ecology, 97(1), 182-193. https://doi.org/10.1890/14-1134.1Links ]

Passuni, G., C., Barbraud, A., Chaigneau, A., Bertrand, R., Oliveros-Ramos, J., Ledesma, R., Castillo, M., Bouchon, and S., Bertrand. 2018. Long-term changes in the breeding seasonality of Peruvian seabirds and regime shifts in the Northern Humboldt Current System. Mar. Ecol. Progr. Ser., 597: 231-242. https://doi.org/10.3354/meps12590Links ]

Payan, L.F. 2016. Informe de monitoreo de aves marinas, Parque Nacional Natural Gorgona, Febrero - Diciembre 2016. Cali. [ Links ]

Pennington, J.T., K.L. ,Mahoney, V.S., Kuwahara, D.D. ,Kolber, R., Calienes, and F.P. ,Chavez. 2006. Primary production in the eastern tropical Pacific: a review. Progr. Oceanogr., 69(2-4): 285-317. https://doi.org/10.1016/j.pocean.2006.03.012Links ]

Perlaza-Gamboa, A., A., Giraldo, L.F. ,Payán y F.A., Estela. 2020. Variación poblacional de tres especies de piqueros (Suliformes: Sulidae) en isla Gorgona, Pacífico colombiano, según la temperatura del mar. Rev. Biol. Trop., 68(2): 704-713. [ Links ]

R Core Team. 2018. R: a language and environment for statistical computing (Version 3.5.2). R Foundation for Statistical Computing, Vienna. https://www.r-project.org.04/04/2019.Links ]

Renjifo, L.M., Á.M., Amaya-Villarreal, J., Burbano-Girón y J., Velásquez-Tibatá (Eds). 2016. Libro rojo de aves de Colombia. Volumen II: Ecosistemas abiertos, secos, insulares, acuáticos continentales, marinos, tierras altas del Darién y Sierra Nevada de Santa Marta y bosques húmedos del centro, norte y oriente del país. Bogotá, D.C.: Editorial Pontificia Universidad Javeriana e Instituto Alexander von Humboldt. [ Links ]

Ribic, C.A., D.G., Ainley, and L.B., Spear. 1992. Effects of El Nino and La Nina on seabird assemblages in the equatorial Pacific. Mar. Ecol. Progr. Ser., 80: 109-124. https://doi.org/10.3354/meps080109Links ]

Schreiber, E.A. 2002. Climate and weather effects on seabirds: 179-216. En Schreiber, E.A. y J., Burger (Eds.). Biology of marine birds. CRC Press, Boca Ratón, USA. [ Links ]

Schreiber, E.A. and R.L., Norton. 2002. Brown Booby (Sula leucogaster), version 2.0. En Poole, A. y F.B., Gill (Eds.). The birds of North America online. Cornell Lab of Ornithology, Ithaca, USA. https://doi.org/10.2173/bna.649Links ]

Stienen, E.W.M. and A., Brenninkmeijer. 2002. Variation in growth in Sandwich Tern chicks Sterna sandvicensis and the consequences for pre- and post-fledging mortality. Ibis, 144: 567-576. https://doi.org/10.1046/j.1474-919X.2002.00086.xLinks ]

Stoffer, D. 2017. astsa: Applied Statistical Time Series Analysis [software]. https://cran.r-project.org/package=astsa. 04/04/2019.Links ]

Tompkins, E.M., H.M., Townsend, and D.J., Anderson. 2017. Decadal-scale variation in diet forecasts persistently poor breeding under ocean warming in a tropical seabird. PLoS ONE, 12(8): 1-24. https://doi.org/10.1371/journal.pone.0182545Links ]

Trapletti, A. and K., Hornik. 2018. tseries: Time Series Analysis and Computational Finance [software]. https://cran.r-project.org/package=tseries. 04/04/2019.Links ]

Venables, W.N. and B.D., Ripley. 2002. Modern applied statistics with S [software]. Springer, New York, USA. http://www.stats.ox.ac.uk/pub/MASS4.04/04/2019.Links ]

Vilchis, L.I., L.T., Balance, and P.C., Fiedler. 2006. Pelagic habitat of seabirds in the Eastern Tropical Pacific: effects of foraging ecology on habitat selection. Mar. Ecol. Progr. Ser., 315: 279-292. https://doi.org/10.3354/meps315279Links ]

Wickham, H. 2007. Reshaping data with the reshape package [software]. J. Statist. Softw., 21(12): 1-20. http://www.jstatsoft.org/v21/i12/. 04/04/2019.Links ]

Wickham, H. 2016. ggplot2: Elegant graphics for data analysis [software]. Springer-Verlag, New York. http://ggplot2.org. 04/04/2019.Links ]

Received: July 23, 2020; Accepted: October 14, 2020

*Autor de correspondencia: ecologia.animal@correounivalle.edu.co

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License