Data from: Using citizen-collected wildlife sightings to predict traffic strike hotspots for threatened species: a case study on the southern cassowary

Assessing the causal factors underpinning the distribution and abundance
of wildlife road-induced mortality can be challenging. This is
particularly ubiquitous for rare or elusive species, because traffic
strikes occur infrequently for these populations and information about
localized abundance, distribution, and movements are generally lacking.
Here we assessed if citizen-collected sightings data may serve as a low
cost and efficient means of gathering long-term animal road-side presence
and road crossing information, which could then be used to assess the
causative factors and direct mitigation actions aimed at reducing wildlife
traffic strike frequency. We explored this principle using two decades of
traffic strike records and citizen-collected sightings of the southern
cassowary Casuarius casuarius johnsonii. Roads have bisected the
cassowaries’ rainforest habitat and despite considerable investment into
mitigation strategies for this species, road-induced mortality is
considered one of the primary threatening processes affecting the
population. Using a Bayesian approach and controlling for spatial
autocorrelation with conditional autoregressive (CAR) models, we
demonstrate that traffic strikes are primarily a density-dependent process
in the southern cassowary. That is, traffic strike clusters occurred along
stretches of road where cassowaries were most frequently sighted. There
were, however, road stretches where traffic strike frequency was greater
than predicted by the number of road-side sightings, illustrating when and
where density-independent processes increased the mortality potential for
a road-crossing cassowary. Synthesis and applications. This is the first
time that citizen-collected sightings data have been used to
systematically inform upon the abundance and distribution of wildlife
traffic strike. The technique not only predicts where incidents are likely
to occur but also helps us to understand the factors responsible for
strike clustering. While not a replacement for systematic surveys, we
highlight citizen-collected sightings data as a low-cost option when
assessing contributing factors to vehicle-induced mortality. Accounting
for density-dependent and independent processes will ensure the most
effective allocation of resources when implementing wildlife traffic
strike mitigation.