Individual-based studies where animals are monitored through space and time enable explorations of ecology, demography, evolutionary biology, movements, and behavior. Here, we review 70 years of research on an endangered African herbivore, the giraffe, based on individual spot pattern recognition, and profile an example of a long-term photographic mark-recapture study of Masai giraffes in Tanzania.We illustrate how individual-based data can be used to examine the fitness consequences (variation in survival and reproduction) of extrinsic environmental factors or intrinsic traits in an evolutionary ecology framework. These data also allow the study of social structure, space use, life histories, and health. The giraffe offers an excellent opportunity to study dynamics of an ungulate species with a highly fissionfusion social system using spot pattern recognition.

Increasing human population growth, exurban development, and associated habitat fragmentation is accelerating the isolation of many natural areas and wildlife populations across the planet. In Tanzania, rapid and ongoing habitat conversion to agriculture has severed many of the country's former wildlife corridors between protected areas. To identify historically linked protected areas, we investigated the genetic structure and gene flow of African savanna elephants in Tanzania using microsatellite and mitochondrial DNA markers in 688 individuals sampled in 2015 and 2017. Our results indicate distinct population genetic structure within and between ecosystems across Tanzania, and reveal important priority areas for connectivity conservation. In northern Tanzania, elephants sampled from the Tarangire‐Manyara ecosystem appear marginally, yet significantly isolated from elephants sampled from the greater Serengeti ecosystem (mean F ST = 0.03), where two distinct subpopulations were identified.Unexpectedly, elephants in the Lake Manyara region appear to be more closely related to those across the East African Rift wall in the Ngorongoro Conservation Area than they are to the neighboring Tarangire subpopulations. We concluded that the Rift wall has had a negligible influence on genetic differentiation up to this point, but differentiation may accelerate in the future because of ongoing loss of corridors in the area. Interestingly, relatively high genetic similarity was found between elephants in Tarangire and Ruaha although they are separated by >400 km. In southern Tanzania, there was little evidence of female‐mediated gene flow between Ruaha and Selous, probably due to the presence of the Udzungwa Mountains between them. Despite observing evidence of significant isolation, the populations of elephants we examined generally exhibited robust levels of allelic richness (mean A R = 9.96), heterozygosity (mean µH E = 0.73), and effective population sizes (mean N e = 148). Our results may inform efforts to restore wildlife corridors between protected areas in Tanzania in order to facilitate gene flow for long‐term survival of elephants and other species.

A population of Masai giraffes (Giraffa camelopardalis tippelskirchi) occurs in Arusha National Park (ANP), which is not part of the regular Tanzanian national wildlife monitoring scheme. Urban development of Arusha city and agricultural expansion have contributed to the increasing isolation of ANP from other protected areas in northern Tanzania. The only published data on the Masai giraffe population of ANP were individual-based data collected in 1979 and 1980. Here, we used individual-based data from 2021 to 2022 to provide an update on the current population size, population sex and age structure, movements and genetic connectivity of giraffes in ANP.We documented a 49% population decline and changes in the age distribution, adult sex ratio, reproductive rate and movement patterns relative to the previous study.Mitochondrial DNA analysis revealed genetic connectivity between ANP and other populations east of the Gregory Rift Escarpments in northern Tanzania and southeastern Kenya, evidence that Masai giraffe once moved widely across the landscape.

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The use of molecular methods to identify the sex of elephants from non-invasive samples is essential for studies of population dynamics and population genetics. We designed a new technique for sex identification in elephants using Amelogenin (AMEL) genes. The X-Y homologs of AMEL genes are suitable for sex determination in pigs and some species in the family Bovidae. The use of AMEL genes was more successful than previous methods that relied on genes found exclusively on Y-chromosomes, such as SRY, to distinguish males from females. We designed a common forward primer and two reverse primers for X-and Y-specific AMEL genes to obtain 262bp and 196bp PCR amplicons from Y and X genes, respectively. We tested the primers for the identification of the sex of 132 elephants. Using our approach, the sex of 126 individuals (95.45%) matched the reference samples, while 6 (4.54%) did not match. This discrepancy observed was due to high grass content in which reduces the ability to accurately sex young individuals in the field. Through our stool samples results, we have shown that the use of only three primers for AMELX/Y provides a highly accurate PCR-based method for sex identification in elephants. The method is fast and shows more success than the SRY system by avoiding the inherent ambiguities of the previous PCR-based methods that made it difficult to distinguish between female samples and failed amplification reactions. Our sex identification method is non-invasive, and can be applied in population genetic studies and forensics tests with elephant species.