scholarly journals Model‐based integration of citizen science data from disparate sources increases the precision of bird population trends

Author(s):  
Lionel R. Hertzog ◽  
Claudia Frank ◽  
Sebastian Klimek ◽  
Norbert Röder ◽  
Hannah G. S. Böhner ◽  
...  
PLoS ONE ◽  
2014 ◽  
Vol 9 (5) ◽  
pp. e96772 ◽  
Author(s):  
Sally D. Hofmeyr ◽  
Craig T. Symes ◽  
Leslie G. Underhill

2020 ◽  
Vol 30 (3) ◽  
Author(s):  
Daniel Fink ◽  
Tom Auer ◽  
Alison Johnston ◽  
Viviana Ruiz‐Gutierrez ◽  
Wesley M. Hochachka ◽  
...  

2021 ◽  
Author(s):  
Philipp H Boersch-Supan ◽  
Robert A Robinson

Accurate and robust population trend assessments are key to successful biodiversity conservation. Citizen science surveys have provided good evidence of biodiversity declines whilst engaging people with them. Citizen scientists are also collecting opportunistic biodiversity records at unprecedented scales, vastly outnumbering records gathered through structured surveys. Opportunistic records exhibit spatio-temporal biases and heterogeneity in observer effort and skill, but their quantity offers a rich source of information. Data integration, the combination of multiple information sources in a common analytical framework, can potentially improve inferences about populations compared to analysing either in isolation. We combine count data from a structured citizen science survey and detection-nondetection data from an opportunistic citizen science programme. Population trends were modelled using dynamic N-mixture models to integrate both data sources. We applied this approach to two different inferential challenges arising from sparse data: (i) the estimation of population trends for an area smaller than a structured survey stratum, and (ii) the estimation of national population trends for a rare but widespread species. In both cases, data integration yielded population trajectories similar to those estimated from structured survey data alone but had higher precision when the density of opportunistic records was high. In some cases this allowed inferences about population trends where indices derived from single data sources were too uncertain to assess change. However, there were differences in the trend magnitude between the integrated and the standard survey model. We show that data integration of large-scale structured and unstructured data is feasible and offers potential to improve national and regional wildlife trend estimates, although a need to independently validate trends remains. Smaller gains are achieved in areas where uptake of opportunistic recording is low. The integration of opportunistic records from volunteer-selected locations alone may therefore not adequately address monitoring gaps for management and policy applications. To achieve the latter, scheme organisers should consider providing incentives for achieving representative coverage of target areas in both structured and unstructured recording schemes.


2019 ◽  
Vol 21 (6) ◽  
pp. 2127-2141 ◽  
Author(s):  
Nuno César de Sá ◽  
Hélia Marchante ◽  
Elizabete Marchante ◽  
João Alexandre Cabral ◽  
João Pradinho Honrado ◽  
...  

2020 ◽  
Author(s):  
Lionel R Hertzog ◽  
Claudia Frank ◽  
Sebastian Klimek ◽  
Norbert Röder ◽  
Hannah GS Böhner ◽  
...  

AbstractAimTimely and accurate information on population trends is a prerequisite for effective biodiversity conservation. Structured biodiversity monitoring programs have been shown to track population trends reliably, but require large financial and time investment. The data assembled in a large and growing number of online databases are less structured and suffer from bias, but the number of observations is much higher compared to structured monitoring programs. Model-based integration of data from these disparate sources could capitalize on their respective strengths.LocationGermany.MethodsAbundance data for 26 farmland bird species were gathered from the standardized Common Breeding Bird Survey (CBBS) and three online databases that varied with regard to their degree of survey standardization. Population trends were estimated with a benchmark model that included only CBBS data, and five Bayesian hierarchical models integrating all data sources in different combinations. Across models, we compared consistency and precision of the predicted population trends, and the accuracy of the models. Bird species body mass, prevalence in the dataset and abundance were tested as potential predictors of the explored quantities.ResultsConsistency in predicted annual abundance indices was generally high especially when comparing the benchmark models to the integrated models without unstructured data. The accuracy of the estimated population changes was higher in the hierarchical models compared to the benchmark model but this was not related to data-integration. Precision of the predicted population trends increased as more data sources were integrated.Main conclusionsModel-based integration of data from different sources can lead to improved precision of bird population trend estimates. This opens up new opportunities for conservation managers to identify declining populations earlier. Integrating data from online databases could substantially increase sample size and thus allowing to derive trends for currently not well-monitored species, especially at sub-national scales.


2018 ◽  
Vol 221 ◽  
pp. 151-159 ◽  
Author(s):  
Joshua J. Horns ◽  
Frederick R. Adler ◽  
Çağan H. Şekercioğlu

Diversity ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 293
Author(s):  
Sara Souther ◽  
Vincent Randall ◽  
Nanebah Lyndon

Federal land management agencies in the US are tasked with maintaining the ecological integrity of over 2 million km2 of land for myriad public uses. Citizen science, operating at the nexus of science, education, and outreach, offers unique benefits to address socio-ecological questions and problems, and thus may offer novel opportunities to support the complex mission of public land managers. Here, we use a case study of an iNaturalist program, the Tribal Nations Botanical Research Collaborative (TNBRC), to examine the use of citizen science programs in public land management. The TNBRC collected 2030 observations of 34 plant species across the project area, while offering learning opportunities for participants. Using occurrence data, we examined observational trends through time and identified five species with 50 or fewer digital observations to investigate as species of possible conservation concern. We compared predictive outcomes of habitat suitability models built using citizen science data and Forest Inventory and Analysis (FIA) data. Models exhibited high agreement, identifying the same underlying predictors of species occurrence and, 95% of the time, identifying the same pixels as suitable habitat. Actions such as staff training on data use and interpretation could enhance integration of citizen science in Federal land management.


Insects ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 683
Author(s):  
Marc Herremans ◽  
Karin Gielen ◽  
Jos Van Kerckhoven ◽  
Pieter Vanormelingen ◽  
Wim Veraghtert ◽  
...  

The peacock butterfly is abundant and widespread in Europe. It is generally believed to be univoltine (one generation per year): adults born in summer overwinter and reappear again in spring to reproduce. However, recent flight patterns in western Europe mostly show three peaks during the year: a first one in spring (overwintering butterflies), a second one in early summer (offspring of the spring generation), and a third one in autumn. It was thus far unclear whether this autumn flight peak was a second new generation or consisted of butterflies flying again in autumn after a summer rest (aestivation). The life cycle of one of Europe’s most common butterflies is therefore still surprisingly inadequately understood. We used hundreds of thousands of observations and thousands of pictures submitted by naturalists from the public to the online portal observation.orgin Belgium and analyzed relations between flight patterns, condition (wear), reproductive cycles, peak abundances, and phenology to clarify the current life history. We demonstrate that peacocks have shifted towards two new generations per year in recent decades. Mass citizen science data in online portals has become increasingly important in tracking the response of biodiversity to rapid environmental changes such as climate change.


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