scholarly journals FROM A BREEDING BIRD ATLAS TO A COMMON BIRD MONITORING SCHEME IN EUROPEAN RUSSIA

Author(s):  
P. Vořišek ◽  
◽  
M.V. Kalyakin ◽  
O.V. Voltzit ◽  
S. Herrando ◽  
...  
2015 ◽  
Vol 21 (6) ◽  
pp. 686-697 ◽  
Author(s):  
Yntze van der Hoek ◽  
Andrew M. Wilson ◽  
Rosalind Renfrew ◽  
Joan Walsh ◽  
Paul G. Rodewald ◽  
...  

Author(s):  
Natalya Ivanova ◽  
Maxim Shashkov

Currently Russia doesn't have a national biodiversity information system, and is still not a GBIF (Global Biodiversity Information Facility) member. Nevertheless, GBIF is the largest source of biodiversity data for Russia. As of August 2020, >5M species occurrences were available through the GBIF portal, of which 54% were published by Russian organisations. There are 107 institutions from Russia that have become GBIF publishers and 357 datasets have been published. The important trend of data mobilization in Russia is driven by the considerable contribution of citizen science. The most popular platform is iNaturalist. This year, the related GBIF dataset (Ueda 2020) became the largest one for Russia (793,049 species occurrences as of 2020-08-11). The first observation for Russia was posted in 2011, but iNaturalist started becoming popular in 2017. That year, 88 observers added >4500 observations that represented 1390 new species for Russia, 7- and 2-fold more respectively, than for the previous 6 years. Now we have nearly 12,000 observers, about 15,000 observed species and >1M research-grade observations. The ratio of observations for Tracheophyta, Chordata, and Arthropoda in Russia is different compared to the global scale. There are almost an equal amount of observations in the global iNaturalist GBIF dataset for these groups. At the same time in Russia, vascular plants make up 2/3rds of the observations. That is due to the "Flora of Russia" project, which attracted many professional botanists both as observers and experts. Thanks to their activity, Russia has a high proportion of research-grade observations in iNaturalist, 78% versus 60% globally. Another consequence of wide participation by professional researchers is the high rate of species accumulation. For some taxonomic groups conspicuous species were already revealed. There are about 850 bird species in Russia of which 398 species were observed in 2018, and only 83 new species in 2019. Currently, the number of new species recorded over time is decreasing despite the increase in observers and overall user activity. Russian iNaturalist observers have shared a lot of archive photos (taken during past years). In 2018, it was nearly 1/4 of the total number of observations and about 3/4 of new species for the year, with similar trends observed during 2019. Usually archive photos are posted from December until April, but the 2020 pandemic lockdown spurred a new wave of archive photo mobilisation in April and May. There are many iNaturalist projects for protected areas in Russia: 27 for strict nature reserves and national parks, and about 300 for others. About 100,000 observations (7.5% of all Russian observations) from the umbrella project "Protected areas of Russia" represent >34% of the species diversity observed in Russia. For some regions, e.g., Novosibirsk, Nizhniy Novgorod and Vladimir Oblasts, almost all protected areas are covered by iNaturalist projects, and are often their only source of available biodiversity data. There are also other popular citizen science platforms developed by Russian researchers. The first one is the Russian birdwatching network RU-BIRDS.RU. The related GBIF dataset (Ukolov et al. 2019) is the third largest dataset for Russia (>370,000 species occurrences). Another Russian citizen science system is wildlifemonitoring.ru, which includes thematic resources for different taxonomic groups of vertebrates. This is the crowd-sourced web-GIS maintained by the Siberian Environmental Center NGO in Novosibirsk. It is noteworthy that iNaturalist activities in Russia are developed more as a social network than as a way to attract volunteers to participate in scientific research. Of 746 citations in the iNaturalist dataset, only 18 articles include co-authors from Russia. iNaturalist data are used for the management of regional red lists (in the Republic of Bashkortostan, Novosibirsk Oblast and others), and as an additional information source for regional inventories. RU-BIRDS data were used in the European Russia Breeding Bird Atlas and the new edition of the European Breeding Bird Atlas. In Russia, citizen science activities significantly contribute to filling gaps in the global biodiversity map. However, Russian iNaturalist observations available through GBIF originate from the USA. It is not ideal, because the iNaturalist GBIF dataset is growing rapidly, and in the future it will represent more than all other datasets for Russia combined. In our opinion, iNaturalist data should be repatriated during the process of publishing through GBIF, as it is implemented for the eBird dataset (Levatich and Ligocki 2020).


Blue Jay ◽  
2018 ◽  
Vol 76 (1) ◽  
pp. 26-27
Author(s):  
LeeAnn Latremouille ◽  
Kiel Drake

Saskatchewan Breeding Bird Atlas: 2017 Season Highlights


2021 ◽  
Vol 25 (sp9) ◽  
Author(s):  
Carol Lynn Trocki ◽  
Aaron S. Weed ◽  
Adam Kozlowski ◽  
Kristin Broms

The Auk ◽  
1995 ◽  
Vol 112 (4) ◽  
pp. 1083-1084
Author(s):  
David W. Johnston

The Condor ◽  
2000 ◽  
Vol 102 (1) ◽  
pp. 241-242
Author(s):  
John W. Prather

2017 ◽  
Author(s):  
Mitchell Lyons ◽  
Kate Brandis ◽  
Corey Callaghan ◽  
Justin McCann ◽  
Charlotte Mills ◽  
...  

AbstractDrones are rapidly becoming a key part of the toolkit for a range of scientific disciplines, as well as a range of management and commercial applications. This presents a number of challenges in context of how drone use might impact nearby wildlife. Interactions between birds and drones naturally come to mind, since they share the airspace. This paper details initial findings on the interactions between drones and birds for a range of waterbird, passerine and raptor species, across of a range of scientific applications and natural environments. The primary aims of this paper are to provide guidance for those planning or undertaking drone monitoring exercises, as well as provide direction for future research into safe and effective monitoring with drones. Our study sites we all located within Australia and spanned a range of arid, semi-arid, dunefield, floodplain, wetland, woodland, forest, coastal heath and urban environments. We particularly focus on behavioral changes towards drones during breeding season, interactions with raptors, and effects on nesting birds in large colonies – three areas yet to be explored in published literature. In over 70 hours of flight, there were no incidents with birds. Although some aggressive behavior was encountered from solitary breeding birds. Several large breeding bird colonies were surveyed, and included in our observations is monitoring and counting of nests in a colony of over 200,000 Straw-necked Ibis, the largest drone-based bird monitoring exercise to date. In addition to providing observations of interactions with specific bird species, we recommend procedures for flight planning, safe flying and avoidance. This paper also provides a basis for a number of critical and emerging areas of research into bird-drone interactions, most notably, territorial breeding birds, safety around large raptors, and the effect of drones on the behaviour of birds in large breeding colonies.


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