To provide an easy and reliable work tool to identify the sex of individuals, adult Black-browed Albatrosses (Thalassarche melanophrys) (n = 31) were weighed and measured, and the sex determined using DNA analyses. Stepwise discriminant analysis showed upper bill depth and weight to be the best predictor variables for sex determination. This model classified correctly 95.0% of the males and 81.8% of the females (overall success was 90.3%). Additionally, a single measure discriminant analysis of upper bill depth was developed that is able to separate sexes using a threshold upper bill depth of 29.87 mm, with values above this point being males and values below it being females.
Easy and reliable methods to identify the sex of individuals are useful for the study of many aspects of avian biology, such as evolutionary ecology and genetics, population dynamics, behavior, dispersion, and migration and conservation genetics, but also for active management of species and populations (Clutton-Brock 1986; Sarrazin and Barbault 1996; Newton 1998). Procellariiformes generally exhibit sexual dimorphism where males are larger and heavier than females, but the degree of overlap renders sexing without behavioral or morphometric confirmation difficult (Hedd et al. 1998). Accurate and easy methods to determine the sex of an individual in the field is necessary for scientific studies.
Discriminant function analyses have been largely used as a tool for sexing species of birds that are sexually monochromatic but show sexual dimorphism in size (Brennan et al. 1991; Ferrer and de le Court 1992; Delgado and Penteriani 2004). External morphometric measurements are taken from individuals of known sex to develop discriminant functions and then test them using skins from museums and collections, individuals hunted/killed or depredated, and both captive and wild live animals (Amat et al. 1993; Lorentsen and Røv 1994). William (1983) and Titus et al. (1984) have noted the power and limitation of these discriminant techniques.
Discriminant functions have been widely used to sex birds, including albatrosses and related species (Hedd et al. 1998; Sagar et al. 1998; Copello et al. 2006; Polito et al. 2012), but no reliable criteria have been described to identify sex for the Black-browed Albatross (Thalassarche melanophrys), even though significant differences in morphological measurements have been found between sexes (Phillips et al. 2004). Therefore, an easy and accurate field method to sex this species would be helpful for studying conservation of the Black-browed Albatross. The aim of this study was to find a versatile and reliable morphometric criterion for sex determination of Black-browed Albatrosses in the field by means of discriminant models.
The Falkland Islands, a British overseas territory, lie in the southwest region of the South Atlantic Ocean, approximately 600 km east of the mainland of South America, between latitudes 51° S and 53° S, and longitudes 57° W and 62° W. The present study was carried out in the Saunders Island. Saunders Island (51° 20′ 34″ S, 60° 10′ 50″ W) is a 12,500-ha sized island off the north coast of West Falkland Island. It is home to four species of penguins: King (Aptenodytes patagonicus), Gentoo (Pygoscelis papua), Rockhopper (Eudyptes chrysocome), and Magellanic (Spheniscus magellanicus); two species of shags, Rock (Phalacrocorax magellanicus) and Imperial (P. atriceps); and several colonies of Black-browed Albatrosses (Thalassarche melanophrys). Upland (Chloephaga picta) and Ruddy-headed (C. rubidiceps) geese also occur on the island.
Body Measurements and Molecular Sex
During 17–26 February 2015, we trapped a total of 31 adult Black-browed Albatrosses. We weighed and measured adults when they arrived at their nests to provision their nestlings (Figs. 1, 2 and 3). Using digital calipers and a ruler, we measured: 1) bill length (to the nearest 0.1 mm); 2) upper bill depth (to the nearest 0.1 mm); and 3) diagonal tarsus and forearm length (to the nearest mm). We also used a spring balance to measure body mass (to the nearest 10 g).
We extracted DNA from feather bulb samples. Feathers (2–7 cm length) were taken from the neck or the back of the adults. The samples were placed in paper envelopes without touching their tips and then into new plastic bags containing silica gel. Silica gel absorbs moisture, which can degrade DNA. Sex identification was carried out by means of Polymerase Chain Reaction amplification of sections from CHD1 genes that are located on the avian sex chromosomes (Z in males and females and W in females only). We followed the protocol for primer sets using Griffiths et al. (1998), which provide the best amplification and the best fragment separation with Black-browed Albatross samples. Using this technique, we identified 11 females and 20 males from the 31 birds used in the discriminant analysis.
Mean and standard deviation for all measurements were calculated for each sex. All five variables were normally distributed and met the conditions for homogeneity of variance. To check for overall differences in size between sex classes, we performed a one-way analysis of variance (ANOVA) of all five morphometrics. We then used forward stepwise discriminant analysis procedures that build the best explanatory discriminant model between sexes with the minimum possible number of morphometric variables. Each variable was moved into the model in successive steps, with an F to enter set to 3.84 (0.95 probability) and an F to remove set to 2.71 (0.90 probability). Wilks's Lambda statistic was derived to quantify the discriminant power of each model. Finally, we used a Jackknife procedure as posterior crossvalidations of the predictive accuracy of the resulting functions (Manly 1986). We conducted analyses using STATISTICA software (StatSoft, Inc. 2007).
There were significant difference in overall size between sex classes of adult Blackbrowed Albatrosses (ANOVA, F = 8.91, df = 5, P < 0.001). Results showed that females were significantly smaller than males for all the morphometric measures, with upper bill depth, weight and forearm length as the most dimorphic characters (Table 1). The stepwise discriminant analysis performed retained upper bill depth and weight as the best predictor variables in the discriminant model and excluded the other variables. The discriminant function was:
Values of D > 0 identified males, and values of D < 0 identified females. This model correctly classified 95.0% of the males and 81.8% of the females (overall success was 90.3%; two females and one male were misclassified) with a low value for Wilks's Lambda statistic (Wilks's Lambda = 0.388, F = 22.03, P < 0.001). The Jackknife procedure also correctly classified 90.3% of the whole sample. Because a discriminant function with only one measurement might be more useful for sex identification, when you find only a skull or a fragment of wing for instance, we conducted the analysis using only upper bill depth. This analysis correctly classified 87.5% of the birds (90% of males and 83.3% of females) with a low value of Wilks's Lambda close to the first selected model (Wilks's Lambda = 0.461, F = 35.03, P < 0.001).
Because Ferrer and de le Court (1992) demonstrated that forearm length is an easier measurement to take than diagonal tarsus length and repeated measurements taken by different observers showed less variance, we ran the discriminant function using only forearm length measurements. This model correctly classified 85% of cases, with a low value of Wilks's Lambda (Wilks's Lambda = 0.719, F = 11, 64, P < 0.001). The discriminant function D2 (upper bill depth) was
Mean and SD of morphometric measures of the Black-browed Albatross.
By solving the function for D2 = 0, we obtained a threshold upper bill depth of 29.87 mm, with values above this point being males and values below it being females. Similarly, solving D3 = 0, the threshold value for forearm length was 286.25 mm, with values above this point being males and values below it being females.
Our results indicate significant size dimorphism between female and male Blackbrowed Albatrosses, and sexes may be separated by means of external morphometric measurements in an easy and reliable way. Since there was considerable overlap in the ranges of some of these measurements, discriminant functions using morphometrics as predictor variables are more accurate tools for sex identification.
Even sexing birds using DNA amplification on sex chromosomes can falsely classify an individual due to sample contamination, experimental error and observer error (Palma et al. 2001). The best model obtained in our discriminant analysis showed a high level of overall correct classification of sex (95%), supported by several statistics and cross-validations. Measures like weight, wing length, tail length, length of wing feathers, and length of claws or foot pad length are widely used in sex determination of birds (Amat et al. 1993; Hedd et al. 1998; Sagar et al. 1998; Copello et al. 2006), although these types of morphometric characters are quite variable and dependent on other factors. Weight has high variation, even within the same day, and is dependent on food eaten, stage of growth and environmental conditions, and wing feathers keep growing after the first flight and are subject to loss and molt. Morphometric variables derived from hard body structures like bills and bones (e.g., upper bill depth or forearm) are preferable as stable predictors (Counsilman et al. 1994).
Identification of sexes in dead birds (e.g., from skeletal material, specimens from museums or depredated birds) can only be determined from measurements of bones or bills. Although it has not been used traditionally in sex determination studies in birds, the forearm has become more widely used due to the accuracy that it provides (Ferrer and de le Court 1992). Furthermore, it has been shown to be an easier and more reliable measure with lower variance in measurements among different observers than has the diagonal tarsus (Ferrer and de le Court 1992). The model constructed only with this measurement provides a forearm length threshold of 286.25 mm between males and females, and the predictive power was 85%.
For a predictive model using just one measurement, the upper bill depth was found to be an easy, immediate, low-cost and accurate explanatory reference for sex determination in the Black-browed Albatross. The forearm length would be the next most valid predictor to separate sexes. These morphometric measurements should be considered standard work tools for future scientific studies and population management of this species.
Fundacion Migres supported the present study. We thank Micky Reeves, N. Huin, the Falkland Government, and David and Suzan Pole-Evans for their support of this project. Procedures used in this study comply with the current laws for working in the Falklands. Permits to work in the study area and for albatross handling were granted by the Falkland Government as well as the owners of Saunders Island.
- Amat, J. A., J. Vinuela and M. Ferrer. 1993. Sexing Chinstrap Penguins (Pygoscelis antarctica) by morphological measurements. Colonial Waterbirds 16: 213–215. Google Scholar
- Brennan, A. L., J. B. Buchanan, C. T. Schick and S. G. Herman. 1991. Estimating sex ratios with discriminant function analysis: the influence of probability cutpoints and sample size. Journal of Field Ornithology 62: 357–366. Google Scholar
- Clutton-Brock, T. H. 1986. Sex ratio variation in birds. Ibis 128: 317–329. Google Scholar
- Copello, S., F. Quintana and G. Somoza. 2006. Sex determination and sexual size-dimorphism in Southern Giant-Petrels (Macronectes giganteus) from Patagonia, Argentina. Emu 106: 141–146. Google Scholar
- Counsilman, J. J., K. Nee, A. K. Jalil and W. L. Keng. 1994. Discriminant analysis of morphometric characters as a means of sexing mynas. Journal of Field Ornithology 65: 1–7. Google Scholar
- Delgado, M. and V. Penteriani. 2004. Gender determination of Eurasian Eagle-Owls (Bubo bubo) by morphology. Journal Raptor Research 38: 375–377. Google Scholar
- Ferrer, M. and C. de le Court. 1992. Sex determination in the Spanish Imperial Eagle. Journal of Field Ornithology 62: 359–364. Google Scholar
- Griffiths, R., M. C. Double, K. Orr and R. J. G. Dawson. 1998. A DNA test to sex most birds. Molecular Ecology 7: 1071–1075. Google Scholar
- Hedd, A., R. Gales, and N. Brothers. 1998. Reliability of morphometric measures for determining the sex of adult and fledgling Shy Albatrosses, Diomedea cauta cauta, in Australia. Wildlife Research 25: 69–79. Google Scholar
- Lorentsen, S.-H. and N. Røv. 1994. Sex determination of Antarctic Petrels Thalassoica antarctica by discriminant analysis of morphometric characters. Polar Biology 14: 143–145. Google Scholar
- Manly, B. F. J. 1986. Multivariate statistical methods: a primer. Chapman and Hall, London, U.K. Google Scholar
- Newton, I. 1998. Population limitation in birds. Academic Press, San Diego, California. Google Scholar
- Palma, L., S. Mira, P. Cardia, P. Beja, T. Guillemaud, N. Ferrand, M. L. Cancela and L. C. Da Fonseca. 2001. Sexing Bonelli's Eagle nestlings: morphometrics versus molecular techniques. Journal of Raptor Research 35: 187–193. Google Scholar
- Phillips, R. A., J. R. D. Silk, B. Phalan, P. Catry and J. P. Croxall. 2004. Seasonal sexual segregation in two Thalassarche albatross species: competitive exclusion, reproductive role specialization or foraging niche divergence? Proceedings of the Royal Society of London B 271: 1283–1291. Google Scholar
- Polito, M. J., G. V. Clucas, T. Hart and W. Z. Trivelpiece. 2012. A simplified method of determining the sex of pygoscelis penguins using bill measurements. Marine Ornithology 40: 89–94. Google Scholar
- Sagar, P. M., J. C. Stahl and J. Mollof. 1998. Sex determination and natal philopatry of Southern Buller's Mollymawks (Diomedea bulleri bulleri). Notornis 45: 271–278. Google Scholar
- Sarrazin, F. and R. Barbault. 1996. Reintroduction: challenges and lessons for basic ecology. Trends in Ecology and Evolution 11: 474–477. Google Scholar
- Titus, K., J. A. Mosher and B. K. Williams. 1984. Chancecorrect classification for use in discriminant analysis: ecological applications. American Midland Naturalist 111: 1–7. Google Scholar
- William, B. K. 1983. Some observations on the use of discriminant analysis in ecology. Ecology 64: 1283–1291. Google Scholar