
Having it all: hybridizing conventional and community science monitoring for enhanced data quality and cost savings
Author(s) -
Emily Owens,
Stephen B. Heard,
Rob C. Johns
Publication year - 2021
Publication title -
facets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.51
H-Index - 9
ISSN - 2371-1671
DOI - 10.1139/facets-2021-0013
Subject(s) - citizen science , wildlife , population , data quality , environmental resource management , geography , environmental science , environmental planning , ecology , engineering , operations management , sociology , biology , metric (unit) , botany , demography
Large-scale monitoring is used to track population trends for many ecologically and economically important wildlife species. Often, population monitoring involves professional staff travelling to collect data (i.e., conventional monitoring) or in efforts to reduce monitoring costs, by engaging volunteers (i.e., community science). Although many studies have discussed the advantages and disadvantages of conventional vs. community science monitoring, few have made direct, quantitative comparisons between these two approaches. We compared data quality and financial costs between contemporaneous and overlapping conventional and community science programs for monitoring a major forest pest, the spruce budworm ( Choristoneura fumiferanae Clem.). Although community science trapping sites were clumped around urban areas, abundance estimates from the programs were strongly spatially correlated. However, annual program expenditures were nearly four times lower in the community science versus the conventional program. We modelled a hypothetical hybrid model of the two programs, which provided full spatial coverage and potentially the same data, but at half the cost of the conventional program and with the added opportunity for public engagement. Our study provides a unique quantitative analysis of merits and costs of conventional versus community science monitoring. Our study offers insights on how to assess wildlife monitoring programs where multiple approaches exist.