Integrated population monitoring of breeding birds in Britain and Ireland

Ibis ◽  
2008 ◽  
Vol 132 (2) ◽  
pp. 151-166 ◽  
Author(s):  
STEPHEN R. BAILLIE
2019 ◽  
Vol 39 (2) ◽  
pp. 169 ◽  
Author(s):  
Holly L. Bernardo ◽  
Pati Vitt ◽  
Rachel Goad ◽  
Susanne Masi ◽  
Tiffany M. Knight

Ecology ◽  
1987 ◽  
Vol 68 (6) ◽  
pp. 1724-1734 ◽  
Author(s):  
John G. Blake ◽  
James R. Karr
Keyword(s):  

Drones ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 9
Author(s):  
Adrien Michez ◽  
Stéphane Broset ◽  
Philippe Lejeune

In the context of global biodiversity loss, wildlife population monitoring is a major challenge. Some innovative techniques such as the use of drones—also called unmanned aerial vehicle/system (UAV/UAS)—offer promising opportunities. The potential of UAS-based wildlife census using high-resolution imagery is now well established for terrestrial mammals or birds that can be seen on images. Nevertheless, the ability of UASs to detect non-conspicuous species, such as small birds below the forest canopy, remains an open question. This issue can be solved with bioacoustics for acoustically active species such as bats and birds. In this context, UASs represent an interesting solution that could be deployed on a larger scale, at lower risk for the operator, and over hard-to-reach locations, such as forest canopies or complex topographies, when compared with traditional protocols (fixed location recorders placed or handled by human operators). In this context, this study proposes a methodological framework to assess the potential of UASs in bioacoustic surveys for birds and bats, using low-cost audible and ultrasound recorders mounted on a low-cost quadcopter UAS (DJI Phantom 3 Pro). The proposed methodological workflow can be straightforwardly replicated in other contexts to test the impact of other UAS bioacoustic recording platforms in relation to the targeted species and the specific UAS design. This protocol allows one to evaluate the sensitivity of UAS approaches through the estimate of the effective detection radius for the different species investigated at several flight heights. The results of this study suggest a strong potential for the bioacoustic monitoring of birds but are more contrasted for bat recordings, mainly due to quadcopter noise (i.e., electronic speed controller (ESC) noise) but also, in a certain manner, to the experimental design (use of a directional speaker with limited call intensity). Technical developments, such as the use of a winch to safely extent the distance between the UAS and the recorder during UAS sound recordings or the development of an innovative platform, such as a plane–blimp hybrid UAS, should make it possible to solve these issues.


Author(s):  
John M. Mola ◽  
Clara Stuligross ◽  
Maureen L. Page ◽  
Danielle Rutkowski ◽  
Neal M. Williams

Abstract Recent bumble bee declines have prompted the development of novel population monitoring tools, including the use of putatively non-lethal tarsal clipping to obtain genetic material. However, the potential side effects of tarsal clipping have only been tested in the worker caste of a single domesticated species, prompting the need to more broadly test whether tarsal clipping negatively affects sampled individuals. To determine if tarsal clipping reduces queen survivorship and colony establishment, we collected wild queens of Bombus vosnesenskii and clipped tarsi from a single leg of half the individuals. We reared captive queens and estimated survivorship and nest establishment success. We also clipped tarsi of workers from a subset of colonies across a range of body sizes. We found no consistent negative effect of clipping on queen survival. In the first year, clipped nest-searching queens suffered heavy mortality, but there was no effect on foraging queens. The following year, we found no effect of clipping on queen survival or establishment. Clipping did not reduce overall worker survival but reduced survivorship for those in the smallest size quartile. Implications for insect conservation Our findings suggest tarsal clipping does not have consistent negative effects on individual survival. However, our results varied with queen behavioral state, year, and worker size, suggesting differences within and among species and interactions with landscape stressors warrant further study. In the interim, we recommend researchers and conservationists minimize the use of tarsal clipping for sensitive species, populations, or small workers except in cases of exceptional scientific need.


Work ◽  
2020 ◽  
Vol 67 (3) ◽  
pp. 557-572
Author(s):  
Said Tkatek ◽  
Amine Belmzoukia ◽  
Said Nafai ◽  
Jaafar Abouchabaka ◽  
Youssef Ibnou-ratib

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the world are turning to data collection and population monitoring for analysis and prediction. The massive data generated through the use of big data and artificial intelligence can play an important role in addressing this unprecedented global health and economic crisis. OBJECTIVES: The objective of this work is to develop an expert system that combines several solutions to combat COVID-19. The main solution is based on a new developed software called General Guide (GG) application. This expert system allows us to explore, monitor, forecast, and optimize the data collected in order to take an efficient decision to ensure the safety of citizens, forecast, and slow down the spread’s rate of COVID-19. It will also facilitate countries’ interventions and optimize resources. Moreover, other solutions can be integrated into this expert system, such as the automatic vehicle and passenger sanitizing system equipped with a thermal and smart High Definition (HD) cameras and multi-purpose drones which offer many services. All of these solutions will facilitate lifting COVID-19 restrictions and minimize the impact of this pandemic. METHODS: The methods used in this expert system will assist in designing and analyzing the model based on big data and artificial intelligence (machine learning). This can enhance countries’ abilities and tools in monitoring, combating, and predicting the spread of COVID-19. RESULTS: The results obtained by this prediction process and the use of the above mentioned solutions will help monitor, predict, generate indicators, and make operational decisions to stop the spread of COVID-19. CONCLUSIONS: This developed expert system can assist in stopping the spread of COVID-19 globally and putting the world back to work.


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