Descriptive inference using large, unrepresentative nonprobability samples: An introduction for ecologists

\ua9 2023 The Authors. Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.Biodiversity monitoring usually involves drawing inferences about some variable of interest across a defined landscape from observations made at a sample of locations within that landscape. If the variable of interest differs between sampled and nonsampled locations, and no mitigating action is taken, then the sample is unrepresentative and inferences drawn from it will be biased. It is possible to adjust unrepresentative samples so that they more closely resemble the wider landscape in terms of “auxiliary variables.” A good auxiliary variable is a common cause of sample inclusion and the variable of interest, and if it explains an appreciable portion of the variance in both, then inferences drawn from the adjusted sample will be closer to the truth. We applied six types of survey sample adjustment—subsampling, quasirandomization, poststratification, superpopulation modeling, a “doubly robust” procedure, and multilevel regression and poststratification—to a simple two-part biodiversity monitoring problem. The first part was to estimate the mean occupancy of the plant Calluna vulgaris in Great Britain in two time periods (1987–1999 and 2010–2019); the second was to estimate the difference between the two (i.e., the trend). We estimated the means and trend using large, but (originally) unrepresentative, samples from a citizen science dataset. Compared with the unadjusted estimates, the means and trends estimated using most adjustment methods were more accurate, although standard uncertainty intervals generally did not cover the true values. Completely unbiased inference is not possible from an unrepresentative sample without knowing and having data on all relevant auxiliary variables. Adjustments can reduce the bias if auxiliary variables are available and selected carefully, but the potential for residual bias should be acknowledged and reported

Exploring the role of smartphone technology for citizen science in agriculture

Citizen science is the involvement of citizens, such as farmers, in the research process. Citizen science has become increasingly popular recently, supported by the proliferation of mobile communication technologies such as smartphones. However, citizen science methodologies have not yet been widely adopted in agricultural research. Here, we conducted an online survey with 57 British and French farmers in 2014. We investigated (1) farmer ownership and use of smartphone technologies, (2) farmer use of farm-specific management apps, and (3) farmer interest and willingness to participate in agricultural citizen science projects. Our results show that 89 % respondents owned a smartphone, 84 % used it for farm management, and 72 % used it on a daily basis. Fifty-nine percent engaged with farm-specific apps, using on average four apps. Ninety-three percent respondents agreed that citizen science was a useful methodology for data collection, 93 % for real-time monitoring, 83 % for identification of research questions, 72 % for experimental work, and 72 % for wildlife recording. Farmers also showed strong interest to participate in citizen science projects, often willing to commit substantial amounts of time. For example, 54 % of British respondents were willing to participate in farmland wildlife recording once a week or monthly. Although financial support was not always regarded as necessary, experimental work was the most likely activity for which respondents thought financial support would be essential. Overall, this is the first study to quantify and explore farmers' use of smartphones for farm management, and document strong support for farm-based citizen science projects. (Résumé d'auteur

Moth biomass increases and decreases over 50 years in Britain

Steep insect biomass declines ('insectageddon') have been widely reported, despite a lack of continuously collected biomass data from replicated long-term monitoring sites. Such severe declines are not supported by the world’s longest running insect population database: annual moth biomass estimates from British fixed monitoring sites revealed increasing biomass between 1967 and 1982, followed by gradual decline from 1982 to 2017, with a 2.2-fold net gain in mean biomass between the first (1967–1976) and last decades (2008–2017) of monitoring. High between-year variability and multi-year periodicity in biomass emphasize the need for long-term data to detect trends and identify their causes robustly

Evaluating Promotional Approaches for Citizen Science Biological Recording: Bumblebees as a Group Versus Harmonia axyridis as a Flagship for Ladybirds

Over the past decade, the number of biological records submitted by members of the public have increased dramatically. However, this may result in reduced record quality, depending on how species are promoted in the media. Here we examined the two main promotional approaches for citizen science recording schemes: flagship-species, using one charismatic species as an umbrella for the entire group (here, Harmonia axyridis (Pallas) for Coleoptera: Coccinellidae), and general-group, where the group is promoted as a whole and no particular prominence is given to any one species (here, bumblebees, genus Bombus (Hymenoptera: Apidae)). Of the two approaches, the general-group approach produced data that was not biased towards any one species, but far fewer records per year overall. In contrast, the flagship-species approach generated a much larger annual dataset, but heavily biased towards the flagship itself. Therefore, we recommend that the approach for species promotion is fitted to the result desired

Horizon Scanning to Predict and Prioritize Invasive Alien Species With the Potential to Threaten Human Health and Economies on Cyprus

Invasive alien species (IAS) are known to be a major threat to biodiversity and ecosystem function and there is increasing evidence of their impacts on human health and economies globally. We undertook horizon scanning using expert-elicitation to predict arrivals of IAS that could have adverse human health or economic impacts on the island of Cyprus. Three hundred and twenty five IAS comprising 89 plants, 37 freshwater animals, 61 terrestrial invertebrates, 93 terrestrial vertebrates, and 45 marine species, were assessed during a two-day workshop involving 39 participants to derive two ranked lists: (1) IAS with potential human health impacts (20 species ranked within two bands: 1–10 species or 11–20 species); and, (2) IAS with potential economic impacts (50 species ranked in three bands of 1–10, 11–20, and 21–50). Five species of mosquitoes (Aedes aegypti, Aedes albopictus, Aedes flavopictus, Aedes japonicus, and Culex quinquefasciatus) were considered a potential threat to both human health and economies. It was evident that the IAS identified through this process could potentially arrive through many pathways (25 and 23 pathways were noted for the top 20 IAS on the human health and economic impact lists respectively). The Convention on Biological Diversity Level II (subcategory) pathways Contaminant on plants, pet/aquarium/terrarium species (including live food for such species), hitchhikers in or on aeroplanes, hitchhikers in or on ship/boats, and vehicles were the main pathways that arose across both lists. We discuss the potential of horizon scanning lists to inform biosecurity policies and communication around IAS, highlighting the importance of increasing understanding amongst all stakeholders, including the public, to reduce the risks associated with predicted IAS arrivals

Using expert-elicitation to deliver biodiversity monitoring priorities on a Mediterranean island.

Biodiversity monitoring plays an essential role in tracking changes in ecosystems, species distributions and abundances across the globe. Data collected through both structured and unstructured biodiversity recording can inform conservation measures designed to reduce, prevent, and reverse declines in valued biodiversity of many types. However, given that resources for biodiversity monitoring are limited, it is important that funding bodies prioritise investments relative to the requirements in any given region. We addressed this prioritisation requirement for a biodiverse Mediterranean island (Cyprus) using a three-stage process of expert-elicitation. This resulted in a structured list of twenty biodiversity monitoring needs; specifically, a hierarchy of three groups of these needs was created using a consensus approach. The most highly prioritised biodiversity monitoring needs were those related to the development of robust survey methodologies, and those ensuring that sufficiently skilled citizens are available to contribute. We discuss ways that the results of our expert-elicitation process could be used to support current and future biodiversity monitoring in Cyprus