Drivers of spatio-temporal variation in mosquito submissions to the citizen science project ‘Mückenatlas’

Abstract

Intensified travel activities of humans and the ever growing global trade create opportunities of arthropod-borne disease agents and their vectors, such as mosquitoes, to establish in new regions. To update the knowledge of mosquito occurrence and distribution, a national mosquito monitoring programme was initiated in Germany in 2011, which has been complemented by a citizen science project, the ‘Mückenatlas’ since 2012. We analysed the ‘Mückenatlas’ dataset to (1) investigate causes of variation in submission numbers from the start of the project until 2017 and to (2) reveal biases induced by opportunistic data collection. Our results show that the temporal variation of submissions over the years is driven by fluctuating topicality of mosquito-borne diseases in the media and large-scale climate conditions. Hurdle models suggest a positive association of submission numbers with human population, catch location in the former political East Germany and the presence of water bodies, whereas precipitation and wind speed are negative predictors. We conclude that most anthropogenic and environmental effects on submission patterns are associated with the participants’ (recording) behaviour. Understanding how the citizen scientists’ behaviour shape opportunistic datasets help to take full advantage of the available information.

Buzzing Homes: Using Citizen Science Data to Explore the Effects of Urbanization on Indoor Mosquito Communities

“…Distribution of submissions over years and urbanization levels varied greatly ( Figure 1 and Supplementary Materials, Table S2 ). Most submissions were recorded in 2016 and 2017, a phenomenon based on media topicality and recorder bias that has already been investigated in previous studies [ 30 , 69 ]. In general, a higher number of submissions came from lower to medium levels of urbanization than from very densely populated areas.…”

“…However, while the flexibility of the protocol leads to a high number of participants, it also induces data bias [ 31 ]. In the case of the ‘Mückenatlas’ scheme, differences in sample size by urbanization level reflects a spatial bias, predominantly caused by population density, a phenomenon well-known from opportunistic citizen science data [ 29 , 30 , 33 , 72 ]. In this study, the huge differences in sample sizes within years and between the groups of urbanization level were counteracted with rather simple methods to demonstrate the general interpretability and usefulness of the opportunistic data collection for addressing ecological questions.…”

“…However, total species richness independent from level of urbanization varies greatly over time ( Supplementary Materials, Figure S2 ), suggesting that fluctuating factors other than soil sealing and human population density shape the recordable diversity of species. Climatic conditions greatly influence the development and composition of mosquito communities [ 74 , 75 , 76 ] and can lead to higher densities, nuisance, and media topicality, thus increasing the probability of a submission by a ‘Mückenatlas’ participant [ 30 ]. In addition, the opportunistic data collection is not only biased by human population and climatic variability but also by taxonomic preferences [ 32 ].…”

“…Among its many benefits for society, it facilitates data collection on a spatial and temporal scale that scientists alone are barely able to cover [ 28 ]. However, there are doubts about the explanatory power of data gathered by non-professionals, as they tend to contain observation biases such as uneven spatial coverage [ 29 , 30 , 31 ], inconsistent sampling behavior [ 32 , 33 ], or uncertainties in object identification by the participants [ 34 ]. On the other hand, advanced methods have been developed in recent years for each stage of the scientific process, including avoidance of bias through adapted protocols [ 35 , 36 ], verification of data using artificial intelligence [ 34 , 37 , 38 ], detection and statistical compensation of biases [ 33 , 39 , 40 , 41 , 42 ], and data integration [ 43 ].…”

How media presence triggers participation in citizen science—The case of the mosquito monitoring project ‘Mückenatlas‘

“…Another interesting pattern was that, similarly to Baden-Wuerttemberg, the federal states of Mecklenburg-Western Pomerania (MV) and Brandenburg (BB) showed high submission frequencies despite low numbers of media reports ( Fig 4 , see also [ 84 ]). This pattern resulted from a headquarter effect , meaning that local communities tend to support their local projects, also known as place-based effects [ 85 ].…”