Teasing apart the dilution effect by combining DNA metabarcoding and
statistical modeling
Abstract
How changes in biodiversity affect disease, particularly in the face of
large-scale land-use change, is a contentious topic in disease ecology
that has implications for public health and conservation policy. The
‘dilution effect’ hypothesis argues that declines in biodiversity are
associated with increased disease risk, but this can be challenging to
demonstrate because many pathogens have complex life cycles such that
changes to the species composition and abundance of hosts can influence
the density and infection prevalence of vectors via multiple mechanisms.
Key to addressing this debate is a quantification of interactions
between hosts, vectors, and pathogens. In their recent study published
in Molecular Ecology, Kocher et al. (2022) captured thousands of
sandflies, some species of which are vectors for the Leishmania
protozoan that causes Leishmaniasis, across a human footprint gradient
in French Guiana (Fig. 1). By implementing DNA metabarcoding of vectors
combined with an innovative modeling approach, they effectively
quantified the nuanced relationships between changes in land-use,
mammalian host diversity, vector abundance, and parasite prevalence. In
support of the dilution effect hypothesis, Kocher et al. found that
sites with higher mammal diversity were associated with lower relative
abundance of reservoir hosts and higher Leishmania infection prevalence
in sandflies. However, while infection prevalence was lower when mammal
diversity was high, the density of sandfly vectors was higher, which
resulted in a weak overall effect of mammal diversity on the density of
infected vectors, the most important indicator of Leishmania
transmission risk.