scholarly journals Integrating structured and unstructured citizen science data to improve wildlife population monitoring

2021 ◽  
Author(s):  
Philipp H Boersch-Supan ◽  
Robert A Robinson
Keyword(s):  
Data Integration ◽  
Citizen Science ◽  
Large Scale ◽  
Population Monitoring ◽  
Analytical Framework ◽  
Good Evidence ◽  
Population Trends ◽  
Data Sources ◽  
Science Data ◽  
Widespread Species

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.

scholarly journals Secretarybird Sagittarius serpentarius Population Trends and Ecology: Insights from South African Citizen Science Data

PLoS ONE ◽  
2014 ◽  
Vol 9 (5) ◽  
pp. e96772 ◽  
Author(s):  
Sally D. Hofmeyr ◽  
Craig T. Symes ◽  
Leslie G. Underhill
Keyword(s):  
South African ◽  
Citizen Science ◽  
Population Trends ◽  
Science Data

scholarly journals Estimating disease vector population size from citizen science data

2021 ◽  
Vol 18 (184) ◽  
Author(s):  
Tam Tran ◽  
W. Tanner Porter ◽  
Daniel J. Salkeld ◽  
Melissa A. Prusinski ◽  
Shane T. Jensen ◽  
...  
Keyword(s):  
Data Collection ◽  
Citizen Science ◽  
Large Scale ◽  
Species Abundance ◽  
Natural World ◽  
Tick Population ◽  
Science Data ◽  
Tick Abundance ◽  
Vector Population ◽  
Public Datasets

Citizen science projects have the potential to address hypotheses requiring extremely large datasets that cannot be collected with the financial and labour constraints of most scientific projects. Data collection by the general public could expand the scope of scientific enquiry if these data accurately capture the system under study. However, data collection inconsistencies by the untrained public may result in biased datasets that do not accurately represent the natural world. In this paper, we harness the availability of scientific and public datasets of the Lyme disease tick vector to identify and account for biases in citizen science tick collections. Estimates of tick abundance from the citizen science dataset correspond moderately with estimates from direct surveillance but exhibit consistent biases. These biases can be mitigated by including factors that may impact collector participation or effort in statistical models, which, in turn, result in more accurate estimates of tick population sizes. Accounting for collection biases within large-scale, public participation datasets could update species abundance maps and facilitate using the wealth of citizen science data to answer scientific questions at scales that are not feasible with traditional datasets.

scholarly journals Winners and losers over 35 years of dragonfly and damselfly distributional change in Germany

2020 ◽  
Author(s):  
D.E Bowler ◽  
D. Eichenberg ◽  
K.J. Conze ◽  
F. Suhling ◽  
K. Baumann ◽  
...  
Keyword(s):  
Citizen Science ◽  
Large Scale ◽  
Positive Trend ◽  
Science Data ◽  
Running Water ◽  
Distributional Change ◽  
Novel Approach ◽  
Occupancy Detection ◽  
Declining Species

AbstractRecent studies suggest insect declines in parts of Europe; however, the generality of these trends across different taxa and regions remains unclear. Standardized data are not available to assess large-scale, long-term changes for most insect groups but opportunistic citizen science data is widespread for some taxa. We compiled over 1 million occurrence records of Odonata (dragonflies and damselflies) from different regional databases across Germany. We used occupancy-detection models to estimate annual distributional changes between 1980 and 2016 for each species. We related species attributes to changes in the species’ distributions and inferred possible drivers of change. Species showing increases were generally warm-adapted species and/or running water species while species showing decreases were cold-adapted species using standing water habitats such as bogs. We developed a novel approach using time-series clustering to identify groups of species with similar patterns of temporal change. Using this method, we defined five typical patterns of change for Odonata – each associated with a specific combination of species attributes. Overall, trends in Odonata provide mixed news – improved water quality, coupled with positive impacts of climate change, could explain the positive trend status of many species. At the same time, declining species point to conservation challenges associated with habitat loss and degradation. Our study demonstrates the great value of citizen science data for assessing large-scale distributional change and conservation decision-making.

scholarly journals Latitudinal variation in arrival and breeding phenology of the pied flycatcher Ficedula hypoleuca using large‐scale citizen science data

2021 ◽  
Vol 52 (2) ◽  
Author(s):  
Pedro G. Nicolau ◽  
Malcolm D. Burgess ◽  
Tiago A. Marques ◽  
Stephen R. Baillie ◽  
Nick J. Moran ◽  
...  
Keyword(s):  
Citizen Science ◽  
Large Scale ◽  
Ficedula Hypoleuca ◽  
Pied Flycatcher ◽  
Latitudinal Variation ◽  
Breeding Phenology ◽  
Science Data

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

2020 ◽  
Vol 30 (3) ◽  
Author(s):  
Daniel Fink ◽  
Tom Auer ◽  
Alison Johnston ◽  
Viviana Ruiz‐Gutierrez ◽  
Wesley M. Hochachka ◽  
...  
Keyword(s):  
Citizen Science ◽  
Annual Cycle ◽  
Population Trends ◽  
Science Data

scholarly journals Comparison of large‐scale citizen science data and long‐term study data for phenology modeling

Ecology ◽  
2018 ◽  
Vol 100 (2) ◽  
pp. e02568 ◽  
Author(s):  
Shawn D. Taylor ◽  
Joan M. Meiners ◽  
Kristina Riemer ◽  
Michael C. Orr ◽  
Ethan P. White
Keyword(s):  
Citizen Science ◽  
Large Scale ◽  
Study Data ◽  
Science Data ◽  
Term Study ◽  
Long Term Study

scholarly journals Mapping Paddy Rice with Satellite Remote Sensing: A Review

2021 ◽  
Vol 13 (2) ◽  
pp. 503
Author(s):  
Rongkun Zhao ◽  
Yuechen Li ◽  
Mingguo Ma
Keyword(s):  
Remote Sensing ◽  
Data Integration ◽  
Large Scale ◽  
Microwave Remote Sensing ◽  
Paddy Rice ◽  
Data Sources ◽  
Accurate Estimation ◽  
Global Changes ◽  
Optical Remote Sensing ◽  
Advantages And Disadvantages

Paddy rice is a staple food of three billion people in the world. Timely and accurate estimation of the paddy rice planting area and paddy rice yield can provide valuable information for the government, planners and decision makers to formulate policies. This article reviews the existing paddy rice mapping methods presented in the literature since 2010, classifies these methods, and analyzes and summarizes the basic principles, advantages and disadvantages of these methods. According to the data sources used, the methods are divided into three categories: (I) Optical mapping methods based on remote sensing; (II) Mapping methods based on microwave remote sensing; and (III) Mapping methods based on the integration of optical and microwave remote sensing. We found that the optical remote sensing data sources are mainly MODIS, Landsat, and Sentinel-2, and the emergence of Sentinel-1 data has promoted research on radar mapping methods for paddy rice. Multisource data integration further enhances the accuracy of paddy rice mapping. The best methods are phenology algorithms, paddy rice mapping combined with machine learning, and multisource data integration. Innovative methods include the time series similarity method, threshold method combined with mathematical models, and object-oriented image classification. With the development of computer technology and the establishment of cloud computing platforms, opportunities are provided for obtaining large-scale high-resolution rice maps. Multisource data integration, paddy rice mapping under different planting systems and the connection with global changes are the focus of future development priorities.

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

2021 ◽  
Author(s):  
Lionel R. Hertzog ◽  
Claudia Frank ◽  
Sebastian Klimek ◽  
Norbert Röder ◽  
Hannah G. S. Böhner ◽  
...  
Keyword(s):  
Citizen Science ◽  
Population Trends ◽  
Science Data ◽  
Bird Population ◽  
Model Based

Estimating conservation metrics from atlas data: the case of southern African endemic birds

2017 ◽  
Vol 27 (3) ◽  
pp. 323-336 ◽  
Author(s):  
ALAN T. K. LEE ◽  
RES ALTWEGG ◽  
PHOEBE BARNARD
Keyword(s):  
Citizen Science ◽  
Large Scale ◽  
Population Change ◽  
Conservation Status ◽  
Bird Species ◽  
Science Data ◽  
Atlas Data ◽  
Endemic Birds ◽  
Change Metrics ◽  
Threatened Status

SummaryThe robust assessment of conservation status increasingly requires population metrics for species that may be little-researched, with no prospect of immediate improvement, but for which citizen science atlas data may exist. We explore the potential for bird atlas data to generate population metrics of use in red data assessment, using the endemic and near-endemic birds of southern Africa. This region, defined here as South Africa, Lesotho and Swaziland, is home to a large number of endemic bird species and an active atlas project. The Southern African Bird Atlas Projects (SABAP) 1 and 2 are large-scale citizen science data sets, consisting of hundreds of thousands of bird checklists and > 10 million bird occurrence records on a grid across the subcontinent. These data contain detailed information on species’ distributions and population change. For conservationists, metrics that guide decisions on the conservation status of a species for red listing can be obtained from SABAP, including range size, range change, population change, and range connectivity (fragmentation). We present a range of conservation metrics for these bird species, focusing on population change metrics together with an associated statistical confidence metric. Population change metrics correlate with change metrics calculated from dynamic occupancy modelling for a set of 191 common species. We identify four species with neither international nor local threatened status, yet for which bird atlas data suggest alarming declines, and two species with threatened status for which our metrics suggest could be reconsidered. A standardised approach to deciding the conservation status of a species is useful so that charismatic or flagship species do not receive disproportionate attention, although ultimately conservation status of any species must always be a consultative process.

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