Using citizen science butterfly counts to predict species population trends

Dennis, Emily B.; Morgan, Byron J. T.; Brereton, Tom; Roy, David B.; Fox, Richard

doi:10.1111/cobi.12956

Cited by 76 publications

(64 citation statements)

References 45 publications

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“…For butterflies, large amounts of data are collected by skilled volunteers on UKBMS sites or WCBS squares across the wider countryside. Unlike UKBMS or WCBS transects, the Big Butterfly Count (BBC) encourages data collection by members of the general public in short 15‐min surveys over a one‐month period in summer (Dennis, Morgan, Brereton, Roy, & Fox, ). As a result, the survey is a better measure of the species that members of the public see most often in their local environment.…”

Section: Methodsmentioning

confidence: 99%

“…As a result, the survey is a better measure of the species that members of the public see most often in their local environment. Using published results from the BBC described in Dennis et al (), the mean average number of recordings for the 18 most recorded UK butterfly species between 2011 and 2017 was calculated. Relative cultural function scores were calculated using Equation , where C = relative cultural function score, Y = individual species average score from the BBC survey, and Y max = highest species average BBC score (gatekeeper Pyronia tithonus ).…”

Section: Methodsmentioning

confidence: 99%

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Predicting resilience of ecosystem functioning from co‐varying species' responses to environmental change

Greenwell

Brereton

Day

et al. 2019

Ecology and Evolution

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Understanding how environmental change affects ecosystem function delivery is of primary importance for fundamental and applied ecology. Current approaches focus on single environmental driver effects on communities, mediated by individual response traits. Data limitations present constraints in scaling up this approach to predict the impacts of multivariate environmental change on ecosystem functioning.We present a more holistic approach to determine ecosystem function resilience, using long‐term monitoring data to analyze the aggregate impact of multiple historic environmental drivers on species' population dynamics. By assessing covariation in population dynamics between pairs of species, we identify which species respond most synchronously to environmental change and allocate species into “response guilds.” We then use “production functions” combining trait data to estimate the relative roles of species to ecosystem functions. We quantify the correlation between response guilds and production functions, assessing the resilience of ecosystem functioning to environmental change, with asynchronous dynamics of species in the same functional guild expected to lead to more stable ecosystem functioning.Testing this method using data for butterflies collected over four decades in the United Kingdom, we find three ecosystem functions (resource provisioning, wildflower pollination, and aesthetic cultural value) appear relatively robust, with functionally important species dispersed across response guilds, suggesting more stable ecosystem functioning. Additionally, by relating genetic distances to response guilds we assess the heritability of responses to environmental change. Our results suggest it may be feasible to infer population responses of butterflies to environmental change based on phylogeny—a useful insight for conservation management of rare species with limited population monitoring data.Our approach holds promise for overcoming the impasse in predicting the responses of ecosystem functions to environmental change. Quantifying co‐varying species' responses to multivariate environmental change should enable us to significantly advance our predictions of ecosystem function resilience and enable proactive ecosystem management.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Predicting resilience of ecosystem functioning from co‐varying species' responses to environmental change

Greenwell

Brereton

Day

et al. 2019

Ecology and Evolution

Self Cite

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“…), and butterflies (Dennis et al. ), will make various aspects of this framework useful in future efforts to map and monitor species populations.…”

Section: Introductionmentioning

confidence: 99%

Modeling avian full annual cycle distribution and population trends with citizen science data

Fink

Auer

Johnston

et al. 2020

Ecological Applications

149

176

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Information on species’ distributions, abundances, and how they change over time is central to the study of the ecology and conservation of animal populations. This information is challenging to obtain at landscape scales across range‐wide extents for two main reasons. First, landscape‐scale processes that affect populations vary throughout the year and across species’ ranges, requiring high‐resolution, year‐round data across broad, sometimes hemispheric, spatial extents. Second, while citizen science projects can collect data at these resolutions and extents, using these data requires appropriate analysis to address known sources of bias. Here, we present an analytical framework to address these challenges and generate year‐round, range‐wide distributional information using citizen science data. To illustrate this approach, we apply the framework to Wood Thrush (Hylocichla mustelina), a long‐distance Neotropical migrant and species of conservation concern, using data from the citizen science project eBird. We estimate occurrence and abundance across a range of spatial scales throughout the annual cycle. Additionally, we generate intra‐annual estimates of the range, intra‐annual estimates of the associations between species and characteristics of the landscape, and interannual trends in abundance for breeding and non‐breeding seasons. The range‐wide population trajectories for Wood Thrush show a close correspondence between breeding and non‐breeding seasons with steep declines between 2010 and 2013 followed by shallower rates of decline from 2013 to 2016. The breeding season range‐wide population trajectory based on the independently collected and analyzed North American Breeding Bird Survey data also shows this pattern. The information provided here fills important knowledge gaps for Wood Thrush, especially during the less studied migration and non‐breeding periods. More generally, the modeling framework presented here can be used to accurately capture landscape scale intra‐ and interannual distributional dynamics for broadly distributed, highly mobile species.

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“…Despite taxonomic biases, there are examples of citizen science approaches on non‐charismatic taxa such as spiders (Campbell & Engelbrecht, ; Hart et al ., ; Wang et al ., ) and beetles (Zapponi et al ., ), and producing valid ecological insights (Pocock et al ., ; Hart et al ., ). Overall, it is not always straightforward to assess the validity of citizen science data since high‐quality data sets for direct comparison are rarely available (Kamp et al ., ; Dennis et al ., ). Of course, the lack of high‐quality data sets is one of the principal motivating factors for professional scientists to work with citizens (Silvertown, ; van Strien et al ., ).…”

Section: Introductionmentioning

confidence: 99%

Mapping species distributions in 2 weeks using citizen science

Sumner

Bevan

Hart

et al. 2019

Insect Conserv Diversity

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Ecological citizen science initiatives are growing in popularity with the increasing realisation of the potential for occurrence records to contribute information on biodiversity. Citizen science data are, however, justifiably criticised for misidentification, uneven sampling, incomplete detection or selective reporting. Here, we test the accuracy of citizen science data for UK social wasp (Vespinae) species’ distributions. We compared data collected over 2 weeks by members of the public setting out baited traps across the UK and sending captured specimens for expert identification [1294 locations; 6680 wasps; three dominant species Vespula vulgaris (44%), Vespula germanica (44%) and Vespa crabro (6%)], with a four‐decade long‐term data set established by the Bees, Wasps and Ants Recording Society (BWARS). The citizen science data were significantly less spatially biased than the long‐term data, but they were more urban‐biased. Species distribution modelling showed that, for Vespa crabro, just 2 weeks of citizen science generated coverage comparable to more than four decades of expert recording. Overall, we show that citizen science can be an extremely powerful and robust method for mapping insect diversity and distributions. We suggest that cautious combination of citizen science data with long‐term expert surveying could be a highly reliable method for monitoring biodiversity.

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Using citizen science butterfly counts to predict species population trends

Cited by 76 publications

References 45 publications

Predicting resilience of ecosystem functioning from co‐varying species' responses to environmental change

Predicting resilience of ecosystem functioning from co‐varying species' responses to environmental change

Modeling avian full annual cycle distribution and population trends with citizen science data

Mapping species distributions in 2 weeks using citizen science

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