Abstract:
Biodiversity monitoring is a global need due to environmental degradation and climate change. Birds are
often monitored indicators for environmental health because they are easy assessable, fast reacting species,
which supply important ecosystem services. But conventional biodiversity monitoring can be timeconsuming,
invasive
and
it
often
needs
trained
specialists,
thus
appropriate
alternatives,
especially
for
largescale
assessments,
like
acoustic
monitoring
are
needed.
While
numerous
acoustic
indices
were
generated
no
studies
occur
about
their
ability
to
reflect
conventional
alpha-diversity
measures
such
as
species
richness,
abundance,
diversity or evenness under complex conditions like a gradient of elevation and degradation.
We choose bird communities along an elevation gradient in natural and degraded rainforests in a highdiverse
region in the Ecuadorian Andes to investigate the association among five conventional (total
abundance, species richness, Shannon Index, evenness, Gini Index) and three acoustic (Acoustic Diversity
Index [ADI], Bioacoustic Index [BI], Acoustic Evenness Index [AEI]) alpha-diversity measures. Furthermore,
we investigated the influence of higher resolutions (FFT window size, frequency band size) on the acoustic
indices. Further, we tested a new acoustic beta-diversity measure. With help of multivariate analyzes we
found acoustic diversity measures were not significantly correlated with conventional diversity measures in
high-diverse rainforests. The acoustic indices were correlated between another. The values of the acoustic
indices increased with higher resolutions and were strongly positively correlated with their next higher
resolution. The NMDS of the conventionally assessed bird communities resulted an elevation gradient and a
distinct separation between degraded and natural forest communities. The NMDS of the acoustically
assessed bird communities resulted no distinct gradients. The conventional and acoustic alpha-diversity
measures were not significantly associated with the elevation or habitat type. ADI, BI and AEI seem not
appropriate to reflect conventional diversity measures in high-diverse ecosystems, but BI can reflect avian
abundance in less diverse ecosystems. Avian acoustic activity was driven by noisy species and not by
species richness or abundance. Higher resolutions of the acoustic indices did not resolute acoustic activity
more exactly in this case, thus for communities where birds with long or complex calls (relevant for BI) or
narrow frequency ranges (relevant for ADI/AEI) are not dominating the acoustic activity the default resolutions of the acoustic indices seem sufficient. Acoustic beta-diversity assessment seems problematic
because the analyzes of frequencies does not reflect species turnover among communities due to the
reason that several species can occupy the same frequencies with their calls.