A comprehensive understanding of how human disturbance affects tropical
forest ecosystems is critical for the mitigation of future losses in
global biodiversity. Although many genetic studies of tropical forest
fragmentation have been conducted to provide insight into this issue,
relatively few have incorporated landscape data to explicitly test the
effects of human disturbance on genetic differentiation among populations.
In this study, we use a newly developed landscape genetic approach that
relies on a genetic algorithm to simultaneously optimize resistance
surfaces to investigate the effects of human disturbance in the Udzungwa
Mountains of Tanzania, which is an important part of a universally
recognized biodiversity hotspot. Our study species is the endangered
Udzungwa red colobus monkey (Procolobus gordonorum), which is endemic to
the Udzungwa Mountains and a known indicator species that thrives in large
and well-protected blocks of old growth forest. Population genetic
analyses identified significant population structure among Udzungwa red
colobus inhabiting different forest blocks, and Bayesian cluster analyses
identified hierarchical structure. Our new method for creating composite
landscape resistance models found that the combination of fire density on
the landscape and distance to the nearest village best explains the
genetic structure observed. These results demonstrate the effects that
human activities are having in an area of high global conservation
priority and suggest that this ecosystem is in a precarious state. Our
study also illustrates the ability of our novel landscape genetic method
to detect the impacts of relatively recent landscape features on a
long-lived species. Genotype and spatial
data for Udzungwa red colobus monkeysThe data set includes
the genotypes and spatial data for the samples used in the study: "A
novel landscape genetics approach demonstrates the effects of human
disturbance on the Udzungwa red colobus monkey (Procolobus
gordonorum)". The data set includes: i) the genotypes for all the
unique individuals identified; ii) the subset of genotypes for the
individuals that were not related in first degree and were used for the
landscape analyses; iii) the pairwise Rousset matrix for the individuals
that were not related in first degree and were included in the landscape
analyses and iv) the spatial coordinates for the individuals that were not
related in first degree and were included in the landscape
analyses.RuizLopezetalgenotypesandspatialdata.xlsx