Unstructured citizen science data fail to detect long‐term population declines of common birds in Denmark

By Johannes Kamp, S. Oppel, H. Heldbjerg, T. Nyegaard, P. Donald. 2016

154 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/e381aea497374f7e3270aa3e2ec5274adbe73bd0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

1. G. Guillera‐Arroita
2. J. Lahoz‐Monfort
3. R. O’Hara
4. I. Ramírez
5. Daniel Fink
6. Steve Kelling
7. J. Horns
8. S. Butchart

In Ecology

1. G. Guillera‐Arroita
2. Ella Browning
3. J. Lahoz‐Monfort
4. R. O’Hara
5. I. Ramírez
6. Daniel Fink
7. Steve Kelling
8. J. Horns

In Nature and Landscape Conservation

1. G. Guillera‐Arroita
2. J. Lahoz‐Monfort
3. R. O’Hara
4. I. Ramírez
5. Daniel Fink
6. Steve Kelling
7. J. Horns
8. S. Butchart

Citations in the corpus

• Using opportunistic citizen science data to estimate avian population trends (2018, background): “Others, however, have cautioned against the use of opportunistic data, particularly when estimating population trends for common species (Kamp et al., 2016). eBird is a large citizen science database that contains a large and growing volume of bird count data (hereafter “checklists” or “lists”)…”
• Data-efficient weakly supervised learning for low-resource audio event detection using deep learning (2018, background): “ations that are rarely used. So far, monitoring of avian populations has been performed via manual surveying, sometimes even including the help of volunteers due to the challenging scales of the data [13, 14]. Early studies mainly focus on detecting bird species present in a recording. In order to p”
• Important Bird and Biodiversity Areas (IBAs): the development and characteristics of a global inventory of key sites for biodiversity (2018, background): “However, significant difficulties remain in deriving reliable population trend estimates from such unstructured data (e.g. Kamp et al. 2016).”
• Analytical guidelines to increase the value of community science data: An example using eBird data to estimate species distributions (2021, methodology): “For example, there may be a greater impact of spatial subsampling when estimating population trends or other processes that show spatial nonstationarity (Kamp et al., 2016; Zbinden et al., 2014).”
• Data Integration for Large-Scale Models of Species Distributions. (2020, background): “A common choice is between small quantities of structured data and large quantities of unstructured data [22].”