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Transnational ivory traffickers continue to smuggle large shipments of elephant ivory out of Africa, yet prosecutions and convictions remain few. We identify trafficking networks on the basis of genetic matching of tusks from the same individual or close relatives in separate shipments. Analyses are drawn from 4,320 savannah (Loxodonta africana) and forest (L. cyclotis) elephant tusks, sampled from 49 large ivory seizures totalling 111 t, shipped out of Africa between 2002 and 2019. Network analyses reveal a repeating pattern wherein tusks from the same individual or close relatives are found in separate seizures that were containerized in, and transited through, common African ports. Results suggest that individual traffickers are exporting dozens of shipments, with considerable connectivity between traffickers operating in different ports. These tools provide a framework to combine evidence from multiple investigations, strengthen prosecutions and support indictment and prosecution of transnational ivory traffickers for the totality of their crimes., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Poaching of elephants is now occurring at rates that threaten African populations with extinction. Identifying the number and location of Africa's major poaching hotspots may assist efforts to end poaching and facilitate recovery of elephant populations. We genetically assign origin to 28 large ivory seizures (≥0.5 metric tons) made between 1996 and 2014, also testing assignment accuracy. Results suggest that the major poaching hotspots in Africa may be currently concentrated in as few as two areas. Increasing law enforcement in these two hotspots could help curtail future elephant losses across Africa and disrupt this organized transnational crime., (Copyright © 2015, American Association for the Advancement of Science.)

We propose a multilocus version of F(ST) and a measure of haplotype diversity using localized haplotype clusters. Specifically, we use haplotype clusters identified with BEAGLE, which is a program implementing a hidden Markov model for localized haplotype clustering and performing several functions including inference of haplotype phase. We apply this methodology to HapMap phase 3 data. With this haplotype-cluster approach, African populations have highest diversity and lowest divergence from the ancestral population, East Asian populations have lowest diversity and highest divergence, and other populations (European, Indian, and Mexican) have intermediate levels of diversity and divergence. These relationships accord with expectation based on other studies and accepted models of human history. In contrast, the population-specific F(ST) estimates obtained directly from single-nucleotide polymorphisms (SNPs) do not reflect such expected relationships. We show that ascertainment bias of SNPs has less impact on the proposed haplotype-cluster-based F(ST) than on the SNP-based version, which provides a potential explanation for these results. Thus, these new measures of F(ST) and haplotype-cluster diversity provide an important new tool for population genetic analysis of high-density SNP data.