The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts

Stuber, Erica F.; Robinson, Orin J.; Bjerre, Emily R.; Otto, Mark C.; Millsap, Brian A.; Zimmerman, Guthrie S.; Brasher, Michael G.; Ringelman, Kevin M.; Fournier, Auriel M. V.; Yetter, Aaron P.; Isola, Jennifer E.; Ruiz‐Gutiérrez, Viviana

doi:10.1016/j.biocon.2022.109556

Cited by 11 publications

(13 citation statements)

References 20 publications

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“…Consequently, these species showed a lower biological invasion risk predicted by pooled models than by scientific survey models. non-substitutable information about species environmental preferences has been observed in several other studies (Galván et al, 2021;Grabow et al, 2022;Stuber et al, 2022). Moreover, it is in accordance with the evidence provided by Perret and Sax (2022) that both structured, scientifically driven sampling and even large collaborative databases capture the full spectrum of species' environmental niches only limitedly (i.e.…”

Section: Discussionsupporting

confidence: 86%

“…Niches generated from scientific survey and citizen science data of all the analysed species exhibited moderate to large non‐overlapping regions, indicating that alternative data sources captured different portions of the environmental gradients. This potentiality of scientific survey and citizen science data to provide complementary, non‐substitutable information about species environmental preferences has been observed in several other studies (Galván et al, 2021; Grabow et al, 2022; Stuber et al, 2022). Moreover, it is in accordance with the evidence provided by Perret and Sax (2022) that both structured, scientifically driven sampling and even large collaborative databases capture the full spectrum of species' environmental niches only limitedly (i.e.…”

Section: Discussionmentioning

confidence: 55%

“…This method proved effective and economical for gathering species occurrences where scientifically designed surveys would require time‐consuming field efforts (Johnson et al, 2020), with successful applications also on invasive alien species (Grez et al, 2022; Maistrello et al, 2016; Werenkraut et al, 2020). In recent years, citizen science initiatives have increasingly been used by researchers as a source of occurrence data to model the distribution of species in both native (Arenas‐Castro et al, 2022; Milanesi et al, 2020; Park et al, 2022; Stuber et al, 2022) and invaded ranges (Di Febbraro et al, 2019; Giuntini et al, 2022; Tran et al, 2022). The availability of abundant and widely distributed occurrence records represented a key characteristic behind the growing importance of citizen science initiatives in modelling studies, especially as providers of presence‐only data (Fletcher et al, 2019; Johnston et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Broennimann & Guisan, 2008; Gallien et al, 2012; Robinson et al, 2020), the most recent approaches focused on hierarchically combining big, unstructured citizen science data sets with small, scientifically structured data sets, often generated at different spatial resolution, extent and data type (i.e. presence‐only and presence/absence; Ahmad Suhaimi et al, 2021; Chevalier et al, 2021; Fletcher et al, 2019; Grabow et al, 2022; Ovaskainen et al, 2016; Stuber et al, 2022). Most of these studies explicitly compared the predictive performance of traditional versus integrated distribution models (Chevalier et al, 2021; Robinson et al, 2020; Zulian et al, 2021), without providing conclusive evidence to support the use of the latter (Ahmad Suhaimi et al, 2021; Simmonds et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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Different facets of the same niche: Integrating citizen science and scientific survey data to predict biological invasion risk under multiple global change drivers

Febbraro

Bosso

Fasola

et al. 2023

Global Change Biology

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Citizen science initiatives have been increasingly used by researchers as a source of occurrence data to model the distribution of alien species. Since citizen science presence‐only data suffer from some fundamental issues, efforts have been made to combine these data with those provided by scientifically structured surveys. Surprisingly, only a few studies proposing data integration evaluated the contribution of this process to the effective sampling of species' environmental niches and, consequently, its effect on model predictions on new time intervals. We relied on niche overlap analyses, machine learning classification algorithms and ecological niche models to compare the ability of data from citizen science and scientific surveys, along with their integration, in capturing the realized niche of 13 invasive alien species in Italy. Moreover, we assessed differences in current and future invasion risk predicted by each data set under multiple global change scenarios. We showed that data from citizen science and scientific surveys captured similar species niches though highlighting exclusive portions associated with clearly identifiable environmental conditions. In terrestrial species, citizen science data granted the highest gain in environmental space to the pooled niches, determining an increased future biological invasion risk. A few aquatic species modelled at the regional scale reported a net loss in the pooled niches compared to their scientific survey niches, suggesting that citizen science data may also lead to contraction in pooled niches. For these species, models predicted a lower future biological invasion risk. These findings indicate that citizen science data may represent a valuable contribution to predicting future spread of invasive alien species, especially within national‐scale programmes. At the same time, citizen science data collected on species poorly known to citizen scientists, or in strictly local contexts, may strongly affect the niche quantification of these taxa and the prediction of their future biological invasion risk.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 55%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Different facets of the same niche: Integrating citizen science and scientific survey data to predict biological invasion risk under multiple global change drivers

Febbraro

Bosso

Fasola

et al. 2023

Global Change Biology

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“…One pathway forward involves coupling semistructured citizen science data with additional sources of information from targeted monitoring programmes. Recent efforts to accomplish this using the eBird citizen science project have demonstrated the ability of this pathway to determine whether, where and when citizen science information can complement targeted monitoring programmes to help inform decisions and supplement data deficiencies (Howell et al, 2022;Stuber et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Leveraging the strengths of citizen science and structured surveys to achieve scalable inference on population size

Stillman,

Howell,

Zimmerman

et al. 2023

Journal of Applied Ecology

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Population size is a key metric for management and policy decisions, yet wildlife monitoring programmes are often limited by the spatial and temporal scope of surveys. In these cases, citizen science data may provide complementary information at higher resolution and greater extent. We present a case study demonstrating how data from the eBird citizen science programme can be combined with regional monitoring efforts by the US Fish and Wildlife Service to produce high‐resolution estimates of golden eagle abundance. We developed a model that uses aerial survey data from the western United States to calibrate high‐resolution annual estimates of relative abundance from eBird. Using this model, we compared regional population size estimates based on the calibrated eBird information with those based on aerial survey data alone. Population size estimates based on the calibrated eBird information had strong correspondence to estimates from aerial survey data in two out of four regions, and population trajectories based on the two approaches showed high correlations. We demonstrate how the combination of citizen science data and targeted surveys can be used to (a) increase the spatial resolution of population size estimates, (b) extend the spatial extent of inference and (c) predict population size beyond the temporal period of surveys. Findings based on this case study can be used to refine policy metrics used by the US Fish and Wildlife Service and inform permitting regulations (e.g. mortality/harm associated with wind energy development). Policy implications: Our results demonstrate the ability of citizen science data to complement targeted monitoring programmes and improve the efficacy of decision frameworks that require information on population size or trajectory. After validating citizen science data against survey‐based benchmarks, agencies can harness strengths of citizen science data to supplement information needs and increase the resolution and extent of population size predictions.

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Assessing trade‐offs in developing a landscape‐scale nest monitoring programme for a threatened shorebird

Ellis,

Anteau,

MacDonald

et al. 2024

Ecol Sol and Evidence

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Effective monitoring of wildlife species requires thorough planning and development of survey programmes that can address management and conservation objectives. Decisions about monitoring programmes include where to survey, survey design and how much effort to allocate at survey sites are typically predicated on limited budgets and available resources. When the scope of inference requires monitoring on a broad spatial scale, predictions of habitat distribution or suitability may be useful for identifying potential survey sites. We focused on a threatened but widely distributed shorebird, the piping plover (Charadrius melodus), which is actively monitored across some, but not all of its range. Our objective was to use piping plover habitat distribution maps, which vary annually, to assess the effectiveness of multiple monitoring programme scenarios and their associated costs. In the breeding range, efforts to improve productivity for species of conservation concern often focus on improving probabilities of nest survival. Consequently, collecting adequate nesting data is crucial for obtaining accurate and precise estimates of nest survival and for evaluating the effectiveness of management actions. By simulating the nest monitoring process, we evaluated how much area, where and how often to survey each site when estimating nest survival and detecting effects of potential management actions. As expected, precision increased and bias decreased around nest survival estimates with greater survey coverage and nest visit frequency. We also identified monitoring programmes with negative net values where survey costs outweighed statistical benefits. Although we applied our simulation framework to evaluate nest monitoring designs for piping plovers, it could be extended to assess whether different monitoring programmes can detect changes in the distribution of other species or occupancy of habitats over time.

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The potential of semi-structured citizen science data as a supplement for conservation decision-making: Validating the performance of eBird against targeted avian monitoring efforts

Cited by 11 publications

References 20 publications

Different facets of the same niche: Integrating citizen science and scientific survey data to predict biological invasion risk under multiple global change drivers

Different facets of the same niche: Integrating citizen science and scientific survey data to predict biological invasion risk under multiple global change drivers

Leveraging the strengths of citizen science and structured surveys to achieve scalable inference on population size

Assessing trade‐offs in developing a landscape‐scale nest monitoring programme for a threatened shorebird

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