Long-term changes in the numbers of waterbirds at an important European wintering site

Marchowski, Dominik; Ławicki, Łukasz; Guentzel, Sebastian; Kaliciuk, Jacek; Kajzer, Z.

doi:10.18276/ab.2018.25-09

Cited by 10 publications

(8 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The observations were made in areas known for their importance for waterbirds, during the breeding season, migration, and the wintering period. (Ławicki et al, 2010 ; Marchowski et al, 2018 ).…”

Section: Methodsmentioning

confidence: 99%

Drones, automatic counting tools, and artificial neural networks in wildlife population censusing

Marchowski

2021

Ecology and Evolution

Self Cite

View full text Add to dashboard Cite

The use of a drone to count the flock sizes of 33 species of waterbirds during the breeding and non‐breeding periods was investigated. In 96% of 343 cases, drone counting was successful. 18.8% of non‐breeding birds and 3.6% of breeding birds exhibited adverse reactions: the former birds were flushed, whereas the latter attempted to attack the drone. The automatic counting of birds was best done with ImageJ/Fiji microbiology software – the average counting rate was 100 birds in 64 s. Machine learning using neural network algorithms proved to be an effective and quick way of counting birds – 100 birds in 7 s. However, the preparation of images and machine learning time is time‐consuming, so this method is recommended only for large data sets and large bird assemblages. The responsible study of wildlife using a drone should only be carried out by persons experienced in the biology and behavior of the target animals.

show abstract

Section: Methodsmentioning

confidence: 99%

Drones, automatic counting tools, and artificial neural networks in wildlife population censusing

Marchowski

2021

Ecology and Evolution

Self Cite

View full text Add to dashboard Cite

show abstract

“…The observations were made in areas known for their importance for waterbirds, during the breeding season, migration, and the wintering period. ( Lawicki et al 2010, Marchowski et al 2018).…”

Section: Study Area and Speciesmentioning

confidence: 99%

“…A drone flight was performed over sites where birds were known to be regularly present ( Lawicki et al 2010;Marchowski et al 2018). The distance from the observer to these sites was usually several hundred metres, but never less than 100 m. This precluded any influence on the part of the observer on the birds' behaviour.…”

Section: Inventory Using a Dronementioning

confidence: 99%

Drones, automatic counting tools and artificial neural networks in wildlife population censusing

Marchowski

2021

Preprint

Self Cite

View full text Add to dashboard Cite

1. The use of a drone to count the flock sizes of 33 species of waterbirds during the breeding and non-breeding periods was investigated. 2. In 96% of 343 cases, drone counting was successful. 18.8% of non-breeding birds and 3.6% of breeding birds exhibited adverse reactions: in the former, the birds were flushed, whereas the latter attempted to attack the drone. 3. The automatic counting birds was best done with the microbiology software - ImageJ / Fiji: the average bird counting rate was 100 birds in 82 seconds. 4. Machine learning using neural network algorithms proved to be an effective and fast way of counting birds – 100 birds in 23 seconds. However, as the preparation of images and machine learning time are time-consuming, this method is recommended only for large data sets and large bird assemblages. 5. The responsible study of wildlife using a drone should only be carried out by persons experienced in the biology and behaviour of the animals concerned.

show abstract

“…The density of the species in the inner part of the island was similar to reported densities in the inland areas on the mainland, where it varied from 0.3 to 1.5 ind./km 2 in the Malozemelskaya tundra (Mineev and Mineev, 2009) and from 0.2 to 3.4 ind./km 2 in the Bolshezemelskaya tundra (Mineev and Mineev, 2012). A trend towards an increase in the wintering population of Greater Scaup was observed in the eastern parts of the Baltic Sea: in Poland in 2002 -18 (Marchowski et al, 2018) and in Germany in 2004 -16 (Gerlach et al, 2019). A similar trend was found in Sweden, where the number of wintering Greater Scaup increased between 1971 and 2015 (Nilsson and Haas, 2016).…”

Section: Greater Scaupmentioning

confidence: 99%

The Long-Term Monitoring of Bird Populations on Kolguev Island in the Barents Sea

Глазов¹,

Loshchagina²,

Kondratyev³

et al. 2021

ARCTIC

View full text Add to dashboard Cite

Kolguev Island (69˚05′ N 49˚15′ E) is located in the Pechora Sea, the southeastern part of the Barents Sea. The island’s ecosystem is unusual due to the total absence of rodents and specialized predators such as weasels, while non-specialized predators such as Arctic (Vulpes lagopus) and red (V. vulpes) foxes and Rough-legged Hawk (Buteo lagopus) are common. Currently, 111 bird species have been registered here, of which 58 are nesting. The absence of rodents and the relatively stable predation pressure have resulted in the high abundance of many bird species: Willow Ptarmigan (Lagopus lagopus), several goose species, some waders, and passerines. Over the 125-year history of ornithological studies on Kolguev, the island avifauna has changed significantly. The trend of an increase in the proportion of widespread and Siberian species together with a decrease in the proportion of Arctic species was observed. Since 2006, a thorough monitoring of Kolguev avifauna has been carried out, during which the dynamics of the bird population densities have been traced. The abundance of Black-bellied Plover (Pluvialis squatarola) and Dunlin (Calidris alpina) decreased, while the numbers of Barnacle Goose (Branta leucopsis) have increased sharply since the 1980s. The breeding density of Rough-legged Hawk has also increased in recent years. The long-term monitoring of Kolguev ecosystems has indicated the high international conservation value of the island due to the high breeding density of many bird species. Our study, covering more than a century of avifaunal studies with almost annual monitoring over the past three decades, provides an unusually long and detailed time-series for an Arctic island.

show abstract

Long-term changes in the numbers of waterbirds at an important European wintering site

Abstract: Waterbirds were regularly monitored in north-

Cited by 10 publications

References 10 publications

Drones, automatic counting tools, and artificial neural networks in wildlife population censusing

Drones, automatic counting tools, and artificial neural networks in wildlife population censusing

Drones, automatic counting tools and artificial neural networks in wildlife population censusing

The Long-Term Monitoring of Bird Populations on Kolguev Island in the Barents Sea

Contact Info

Product

Resources

About