El encuestador o la necesidad de entender

Using animal population indicators to evaluate conservation achievement is widely practised, yet seldom empirically tested (Hoare et al. 2013). Measuring conservation goals for black rhino recovery is a prime example of this tendency. As already mentioned, several authors have concluded that HiP’s black rhino population is in rapid decline i.e., exceeded its carrying capacity (i.e., ‘crashing’: e.g., Emslie 1999, 2001; Reid et al. 2007; Adcock 2009; Slotow et al. 2010). The term carrying capacity (hereafter CC), however, is widely used yet frequently misunderstood (Morgan et al. 2009). Originally adopted by agricultural scientists (e.g., sheep, Ovis aries) the CC was equated to optimal stocking rate, the

population density giving maximum yield of animal products for money. For ecologists, in contrast, it is the zero growth density (i.e., births match deaths). Moreover, the density level at which births match deaths is limited by any

factor(s) changing birth or death rates. Predation can thus affect the density level attained, as can harvests. For black rhino in reserves like HiP with high densities of large predators and ongoing annual harvesting makes it inherently difficult to be confident of CC levels (e.g., Morgan et al. 2009).

Further complicating the matter is that for large mammals, density dependence arising largely from exploitative competition may not become effective until population density exceeds some threshold level. In other words the vital rates, defined as the overall change in births and deaths per 1000 individuals, are density vague for black rhinoceros (Owen-Smith 2001).

Therefore, vital rates of animal populations relative to increasing density, rather than being a linear relation projected by a simple logistic model are convex (e.g., human populations: slow decline in vital rates that increases at high densities) or concave downwards (e.g., small mammals: rapid decline in vital rates as soon as densities increase). Black rhino do not reach the same high vital rates that small and even large mammal populations at low densities are able to and for this reason crash quickly after an unknown density threshold is reached (Fig. 1).

177 Thus, the relationship between black rhino populations’ vital rates and its

density and subsequent range size may be ramp-like with no obvious indication that vital rates and habitat are deteriorating along with increasing range sizes until the threshold is reached. For this reason caution is advised when trying to use my or other studies findings as evidence of population status and

performance. Although, I discovered that range sizes have not changed (Chapter 2), calf predation does occur (Chapter 3), lesion severity is temporally linked with black rhino body condition (Chapter 4) and oxpeckers are conditional parasites that target lesions over tick sites in periods of low tick density (Chapter 5) but that black rhino might tolerate this due to increased vigilance benefits (Chapter 6). This study’s major conservation application therefore is that it is the first systematic monitoring of HiP’s black rhino population in over forty years. Being confident in the meaning of my findings and detecting changes in this population’s status and ongoing performance will require similar studies to be repeated in the future. Nevertheless, knowing that radio-triangulation home range studies are reliable and home range size does not appear to have increased significantly over the last forty years (Chapter 2) ought to encourage conservation managers and researchers to be more discerning when using historical black rhino home range studies to infer reductions in CC (e.g., Reid et al. 2007). Further, research into how black rhino respond spatially to habitat changes would benefit our understanding of Chapter 2’s results and basic black rhino spatial dynamics.

Another concern for apparent population decline has been predators (Fanayo et al. 2006). Research has shown that overall lion: prey ratio within HiP around the time of this study (i.e., 2010) had actually increased markedly from historically low densities (Grange et al. 2012). Thus, the black rhino calf depredation attempt I recorded (Chapter 3) might be a reflection of recent increases in predator density. A concurrent decline in alternative prey such as kudu and buffalo (Grange et al. 2012) might be driving lion to seek unusual prey such as black rhino calves. Conservation managers, however, rarely factor predation in their management plans or projections but perhaps they ought to regularly monitor predator/ prey densities when managing black rhino for improved performance.

178 Body condition is above average (i.e., average score > 3.0; Reuter and Adcock 1998) for black rhino in HiP (Chapter 4). The severity of the

management challenge at hand and the danger of misleading conservation policy requires the systematic monitoring of unbiased sample of individuals and their habitat through time (Linklater et al. 2010). Despite the remarkably severe filarial lesions observed on HiP black rhino, lesions themselves do not appear to drive poor body condition that might impact on rhino fecundity. Discerning whether this is likely has significant implications as it will allow us to determine if HiP’s below desired population performance might be due to the occurrence of filarial parasites. Black rhino’s exposure to human overkill and greater than realised calf depredation might have made them unusually tolerant towards overt lesion feeding by oxpeckers. To be certain future studies ought to conduct concurrent measures of tick densities that are repeated in other black rhino- oxpecker sympatric populations with filarial lesions of varying severity (e.g., southern and east Africa; Stutterheim and Brooke 1981; Stutterheim 1982a; Craig 2009) and different human exposure histories. Chapter 4 also provides a map of locations that enables such comparisons in future. Therefore, the results of this thesis can be applied toward improving our understanding of black rhino welfare in several ways (also see Linklater et al. 2010) and act as preliminary baseline studies for additional conditional parasitism-mutualism investigations in future.