National bat monitoring programme roost counts dataset

Many long-term wildlife population monitoring programmes rely on citizen
scientists for data collection. This can offer several benefits over
traditional monitoring practices as it is a cost-effective, large-scale
approach capable of providing long time series data and raising public
environmental awareness. Whilst there is a debate about the quality of
citizen science data, a standardised sampling design can allow citizen
science data to be of a similar quality to those collected by
professionals. However, many programmes use subjective, opportunistic
selection of monitoring sites and this introduces several types of bias,
which are not well understood. Using bat roost counts as a case study, we
took a ‘virtual ecologist’ approach to simulate the effect of
opportunistic site selection and uneven observer retention on our ability
to accurately detect abundance trends. We simulated populations with
different levels of temporal variability and site fidelity. Our
simulations reveal that opportunistic site selection and low observer
retention can result in biased trends and that these biases are magnified
when monitored populations exhibit high levels of inter-annual variation
and low site fidelity. These results show that the synergistic effects of
observer behaviour, site selection, and population dynamics lead to biased
abundance trends in monitoring programmes. This study highlights the value
of engaging and retaining citizen science observers, a standardised
sampling design, and the collection of meta-data. We conclude that
monitoring programmes need to be aware of their focal species’ temporal
variability and site fidelity to adequately assess the potential bias
caused by opportunistic site selection and low observer retention.
Synthesis and applications. Accurate data on population changes are key
for conservation success. Therefore, it is important that citizen science
monitoring programmes assess and potentially quantify the biases present
in their data. We demonstrate the applicability of an established
simulation framework to assess the effect of biases on our ability to
correctly detect abundance trends. Our findings highlight that monitoring
programmes need to be aware of their study species’ temporal variability
and site fidelity to assess and account for the effects of biased site
selection and observer retention. The National Bat Monitoring Programme
(NBMP) is run by Bat Conservation Trust, in partnership with the Joint
Nature Conservation Committee, and supported and steered by Natural
England, Natural Resources Wales, Northern Ireland Environment Agency, and
Scottish Natural Heritage. The NBMP is indebted to all observers who
contribute data to the programme.