Our purpose in this study was to: (1) demonstrate the use of public domain image analysis software ImageJ ( Schneider, Rasband & Eliceiri, 2012 ) to extract patterns from image data and quantify multiple aspects of the complex coat patterns of wild Masai giraffes; (2) use quantitative genetics methods (parent–offspring regression) to quantify the proportion of observed phenotypic variation of a trait that is shared between mother and offspring; and (3) determine whether variation in complex coat pattern traits was related to a measure of fitness (survival) and thereby infer the effect of natural selection (viability selection) on giraffe coat patterns ( Lande & Arnold, 1983 ; Falconer & Mackay, 1996 ).

The coat patterns of Masai giraffes ( Giraffa camelopardalis tippelskirchii ) are complex and show a high degree of individual variation ( Dagg, 1968 ; Fig. 1 ). Masai giraffes’ spots vary in color and shape from those that are nearly round with very smooth edges (low tortuousness), to extremely elliptical with incised or lobate edges (high tortuousness). Giraffe skin pigmentation is uniformly dark grey ( Dimond & Montagna, 1976 ), but the spots that make up their coat markings are highly variable in traits such as color, roundness, and perimeter tortuousness. This variation has been used to classify subspecies ( Lydekker, 1904 ), and to reliably identify individuals because patterns do not change with age ( Foster, 1966 ; Bolger et al., 2012 ; Dagg, 2014 ). Dagg (1968) first presented evidence from a small zoo population that the shape, number, area, and color of spots in giraffe coat patterns may be heritable, but analysis of spot traits in wild giraffes, and objective measurements of spot characteristics in general have been lacking.

Materials & Methods

As a general overview, our methods were to: (1) collect field data in one area of Tanzania as digital images of giraffes to be used for spot pattern and survival analyses; (2) extract patterns from images; (3) quantify giraffe patterns by measuring 11 spot traits; (4) use principal components analysis (PCA) to reduce the dimensionality of the spot traits; (5) use mother-offspring regressions to estimate the phenotypic similarity between mother and offspring of the 11 spot traits and the 1st two dimensions of the PCA; (6) use k-means clustering to assign giraffe calves into phenotypic groups according to their spot pattern traits; (7) use capture-mark-recapture analysis to estimate survival and determine whether there are fitness differences among the phenotypic groups; (8) use capture-mark-recapture analysis to determine whether there are fitness effects from any particular spot traits.

This research was carried out with permission from the Tanzania Commission for Science and Technology (COSTECH), Tanzania National Parks (TANAPA), the Tanzania Wildlife Research Institute (TAWIRI), African Wildlife Foundation, and Manyara Ranch Conservancy.

Field Data Collection This study used data from individually identified, wild, free-ranging Masai giraffes in a 1,700 km2 sampled area within a 4,400 km2 region of the Tarangire Ecosystem, northern Tanzania, East Africa. Data were collected as previously described in Lee et al. (2016a). We collected data during systematic road transect sampling for photographic capture-mark-recapture (PCMR). We conducted 26 daytime surveys for giraffe PCMR data between January 2012 and February 2016. We sampled giraffes three times per year around 1 February, 1 June, and 1 October near the end of every precipitation season (short rains, long rains, and dry, respectively) by driving a network of fixed-route transects on single-lane dirt tracks in the study area. We surveyed according to Pollock’s robust design sampling framework (Pollock, 1982; Kendall, Pollock & Brownie, 1995), with three occasions per year. Each sampling occasion was composed of two sampling events during which we surveyed all transects in the study area with only a few days interval between events. Each sampling occasion was separated by a 4-month interval (4.3 years × 3 occasions year−1 × 2 events occasion−1 = 26 survey events). During PCMR sampling events, a sample of individuals were encountered and either ‘sighted’ or ‘resighted’ by slowly approaching and photographing the animal’s right side from approximately 150 m at a perpendicular angle (Canon 40D and Rebel T2i cameras with Canon Ultrasonic IS 100–400 mm lens; Canon USA, Inc., One Canon Park, Melville, New York, USA). We identified individual giraffes using their unique and unchanging coat patterns (Foster, 1966; Dagg, 2014) with the aid of pattern-recognition software Wild-ID (Bolger et al., 2012). We attempted to photograph every giraffe encountered, and recorded sex and age class based on physical characteristics. We assigned giraffes to one of four age classes for each observation based on the species’ life history characteristics and our sampling design: neonate calf (0–3 months old), older calf (4–11 months old), subadult (1–3 years old for females, 1 –6 years old for males), or adult (>3 years for females, >6 years for males) using a suite of physical characteristics (Strauss et al., 2015), and size measured with photogrammetry (Lee et al., 2016a). In this analysis, we used only adult females and animals first sighted as neonate calves. All animal work was conducted according to relevant national and international guidelines. This research was carried out with permission from the Tanzania Commission for Science and Technology (COSTECH) Research Permit numbers 2017-163-ER-90-172, 2016-146-ER-2001-31, 2015-22-ER-90-172, 2014-53-ER-90-172, 2013-103-ER-90-172, 2012-175-ER-90-172, 2011-106-NA-90-172, Tanzania National Parks (TANAPA), the Tanzania Wildlife Research Institute (TAWIRI). No Institutional Animal Care and Use Committee (IACUC) approval was necessary because animal subjects were observed without disturbance or physical contact of any kind.