The Role of Citizen Science in Conservation under the Telecoupling Framework

Yang, Di; Wan, Ho Yi; Huang, Ta-Ken; Liu, Jianguo

doi:10.3390/su11041108

Cited by 11 publications

(13 citation statements)

References 60 publications

(94 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…range maps and consequently help reduce uncertainty when identifying priority areas for conservation actions [65]. Citizen science data can also be used in telecoupling research to better understand large-scale people-nature interactions [66]. There is great potential to harness the same data to strengthen assessment of the impacts of human activities in space and time.…”

Section: Filling Information Gapsmentioning

confidence: 99%

Quantitative conservation geography

Minin

Correia

Toivonen

2022

Trends in Ecology & Evolution

View full text Add to dashboard Cite

Section: Filling Information Gapsmentioning

confidence: 99%

Quantitative conservation geography

Minin

Correia

Toivonen

2022

Trends in Ecology & Evolution

View full text Add to dashboard Cite

“…In this manner, a digital network of local volunteers, usually at the country level, can easily prepare their own bird distribution presence-only maps similar to our case-study demonstrated in Figure 13. This volunteered effort is prone to biases and limitations related to variability in species, time, locality, and volunteer skills [84,85]. However, spatial bias can be degraded to a certain degree using existing geospatial analytical methods [86] and consensus of the multiple automated point counts can be a natural validation method for the individual counts.…”

Section: Bird Mapping Discussionmentioning

confidence: 99%

Automated Bird Counting with Deep Learning for Regional Bird Distribution Mapping

Akçay

Kabasakal

Aksu

et al. 2020

Animals

View full text Add to dashboard Cite

A challenging problem in the field of avian ecology is deriving information on bird population movement trends. This necessitates the regular counting of birds which is usually not an easily-achievable task. A promising attempt towards solving the bird counting problem in a more consistent and fast way is to predict the number of birds in different regions from their photos. For this purpose, we exploit the ability of computers to learn from past data through deep learning which has been a leading sub-field of AI for image understanding. Our data source is a collection of on-ground photos taken during our long run of birding activity. We employ several state-of-the-art generic object-detection algorithms to learn to detect birds, each being a member of one of the 38 identified species, in natural scenes. The experiments revealed that computer-aided counting outperformed the manual counting with respect to both accuracy and time. As a real-world application of image-based bird counting, we prepared the spatial bird order distribution and species diversity maps of Turkey by utilizing the geographic information system (GIS) technology. Our results suggested that deep learning can assist humans in bird monitoring activities and increase citizen scientists’ participation in large-scale bird surveys.

show abstract

“…D. Yang, Wan, et al. (2019) studied the environmental drivers impacting Monarch butterflies by incorporating citizen science data with the earth observation data set. Fern and Morrison (2017) modeled the critical areas for migratory songbirds by combining eBird and Landsat 8 OLI database.…”

Section: Introductionmentioning

confidence: 99%

“…One of citizen science representations-Volunteered Geographic Information (VGI) has been widely used in species distribution mapping, which facilitates the enhancement, update, and completion of many spatial data sets for research (Goodchild, 2007). D. Yang, Wan, et al (2019) studied the environmental drivers impacting Monarch butterflies by incorporating citizen science data with the earth observation data set. Fern and Morrison (2017) modeled the critical areas for migratory songbirds by combining eBird and Landsat 8 OLI database.…”

mentioning

confidence: 99%

Unprecedented Migratory Bird Die‐Off: A Citizen‐Based Analysis on the Spatiotemporal Patterns of Mass Mortality Events in the Western United States

Yang

et al. 2021

GeoHealth

Self Cite

View full text Add to dashboard Cite

Extensive, severe wildfires, and wildfire‐induced smoke occurred across the western and central United States since August 2020. Wildfires resulting in the loss of habitats and emission of particulate matter and volatile organic compounds pose serious threatens to wildlife and human populations, especially for avian species, the respiratory system of which are sensitive to air pollutions. At the same time, the extreme weather (e.g., snowstorms) in late summer may also impact bird migration by cutting off their food supply and promoting their migration before they were physiologically ready. In this study, we investigated the environmental drivers of massive bird die‐offs by combining socioecological earth observations data sets with citizen science observations. We employed the geographically weighted regression models to quantitatively evaluate the effects of different environmental and climatic drivers, including wildfire, air quality, extreme weather, drought, and land cover types, on the spatial pattern of migratory bird mortality across the western and central US during August‐September 2020. We found that these drivers affected the death of migratory birds in different ways, among which air quality and distance to wildfire were two major drivers. Additionally, there were more bird mortality events found in urban areas and close to wildfire in early August. However, fewer bird deaths were detected closer to wildfires in California in late August and September. Our findings highlight the important impact of extreme weather and natural disasters on bird biology, survival, and migration, which can provide significant insights into bird biodiversity, conservation, and ecosystem sustainability.

show abstract

The Role of Citizen Science in Conservation under the Telecoupling Framework

Cited by 11 publications

References 60 publications

Quantitative conservation geography

Quantitative conservation geography

Automated Bird Counting with Deep Learning for Regional Bird Distribution Mapping

Unprecedented Migratory Bird Die‐Off: A Citizen‐Based Analysis on the Spatiotemporal Patterns of Mass Mortality Events in the Western United States

Contact Info

Product

Resources

About