Ranging behaviour and habitat preferences of the Martial Eagle: Implications for the conservation of a declining apex predator

Abstract

Understanding the ranging behaviours of species can be helpful in effective conservation planning. However, for many species that are rare, occur at low densities, or occupy challenging environments, this information is often lacking. The Martial Eagle (Polemaetus bellicosus) is a low density apex predator declining in both non-protected and protected areas in southern Africa, and little is known about its ranging behaviour. We use GPS tags fitted to Martial Eagles (n = 8) in Kruger National Park (KNP), South Africa to describe their ranging behaviour and habitat preference. This represents the first time that such movements have been quantified in adult Martial Eagles. Territorial eagles (n = 6) held home ranges averaging ca. 108 km2. Home range estimates were similar to expectations based on inter-nest distances, and these large home range sizes could constrain the carrying capacity of even the largest conservation areas. Two tagged individuals classed as adults on plumage apparently did not hold a territory, and accordingly ranged more widely (ca. 44,000 km2), and beyond KNP boundaries as floaters. Another two territorial individuals abandoned their territories and joined the 'floater' population, and so ranged widely after leaving their territories. These unexpected movements after territory abandonment could indicate underlying environmental degradation. Relatively high mortality of these wide-ranging 'floaters' due to anthropogenic causes (three of four) raises further concerns for the species' persistence. Habitat preference models suggested Martial Eagles used areas preferentially that were closer to rivers, had higher tree cover, and were classed as dense bush rather than open bush or grassland. These results can be used by conservation managers to help guide actions to preserve breeding Martial Eagles at an appropriate spatial scale.

Fig 1. Home range estimators (50, 75, 95% Kernel Density Estimates) for six of eight adult Martial Eagles that were classed as territorial.

Eagles were GPS tracked in KNP, South Africa (top left). Home ranges are shown in relation to KNP borders. Expanded plots of home ranges are shown (right) in relation to the KNP boundary (thick black line), main rivers (blue lines e.g. Timbavati), roads (thin parallel black lines e.g. S39, nest sites (green trees), and capture locations (red stars). Panels on the right showing home ranges are set to the same scale as given in the upper right panel.

Fig 2. The 95% kernel density estimate (KDE) home range sizes for each individual by month.

Missing bars indicate no data due to cessation of tag transmission. Coloured bars indicate months in which the individual bird was recorded to incubate (red), raise a fledgling (blue) or provision a fledged chick in post fledging dependency (green). Horizontal dashed lines indicate the 95% KDE for the entire dataset of each individual. Vertical lines indicate the proportion of days per month that a nest site was visited by the individual. * 1493 km²; ** 2319 km²

Fig 3. Movements of floater adult Martial Eagles (G32551 and G32516), and those that were territorial but vacated their territories (PTT 72154 and G32553) from KNP, showing the area covered during tracking.

GPS locations are coloured by month to visualize movements through time (see bottom legend). The location of each bird’s death, or last known location, is also indicated.

Fig 4. Frequency of step lengths in 1 km (0–10 km) and 15 km (10–100 km) intervals (left), and fixed effects plots from a generalised linear mixed model investigating step lengths between the breeding and non-breeding period (centre) and between months to assess seasonality (right).

Fig 5. Generalized linear mixed model (GLMM) predictive fixed-effects plots showing the modelled habitat utilization of territorial Martial Eagles tracked after their capture in KNP according to several habitat features: tree cover, elevation, topographic slope, distance to nearest river, distance to nearest road, and land cover.

Solid lines show the predicted relationships, with 95% CL captured within grey shaded areas. The bottom right panel shows the predicted probability for the categorical factor, land cover, with 95% confidence limits represented by vertical lines.