Camera Trapping at Harpy Eagle Nests: Interspecies Interactions Under Predation Risk

Aguiar‐Silva, Francisca Helena; Jaudoin, Olivier; Sanaiotti, Tânia Margarete; Seixas, Gláucia Helena Fernandes; Duleba, Samuel; Martins, Frederico Drummond

doi:10.3356/jrr-15-58.1

Cited by 13 publications

(9 citation statements)

References 19 publications

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“…Carrion is known to result in intense interspecific competition, and this form of interaction has been shown to occur at harpy eagle nests 22 . This mechanism of carrion deposition is widespread in raptors, even if the magnitude of carcass deposition by smaller raptors that consume smaller prey is more modest.…”

Section: Discussionmentioning

confidence: 99%

Long-term concentration of tropical forest nutrient hotspots is generated by a central-place apex predator

Miranda

Peres

Oliveira‐Santos

et al. 2023

Sci Rep

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Apex predators typically affect the distribution of key soil and vegetation nutrients through the heterogeneous deposition of prey carcasses and excreta, leading to a nutrient concentration in a hotspot. The exact role of central-place foragers, such as tropical raptors, in nutrient deposition and cycling, is not yet known. We investigated whether harpy eagles (Harpia harpyja) in Amazonian Forests—a typically low soil fertility ecosystem—affect soil nutrient profiles and the phytochemistry around their nest-trees through cumulative deposition of prey carcasses and excreta. Nest-trees occurred at densities of 1.5–5.0/100 km2, and each nest received ~ 102.3 kg of undressed carcasses each year. Effects of nests were surprisingly negative over local soil nutrient profiles, with soils underneath nest-trees showing reductions in nutrients compared with controls. Conversely, canopy tree leaves around nests showed significant 99%, 154% and 50% increases in nitrogen, phosphorus and potassium, respectively. Harpy eagles have experienced a 41% decline in their range, and many raptor species are becoming locally extirpated. These are general examples of disruption in biogeochemical cycles and nutrient heterogeneity caused by population declines in a central-place apex predator. This form of carrion deposition is by no means an exception since several large raptors have similar habits.

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Section: Discussionmentioning

confidence: 99%

Long-term concentration of tropical forest nutrient hotspots is generated by a central-place apex predator

Miranda

Peres

Oliveira‐Santos

et al. 2023

Sci Rep

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“…Another strategy which has the same idea as radiotags, is attaching a camera to the animal itself. For example, Brockman et al (2017) used neck-mounted cameras on brown bears to determine kill rates of moose and caribou in south-central Alaska. The results showed higher kill rates than previous estimates via other methods and gives insight to the diet of the species as well.…”

Section: Animal Activity Patternsmentioning

confidence: 99%

A narrative review on the use of camera traps and machine learning in wildlife research

Bijl¹,

Heltai²

2022

Columella

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Camera trapping has become an important tool in wildlife research in the past few decades. However, one of its main limiting factors is the processing of data, which is labour-intensive and time-consuming. Consequently, to aid this process, the use of machine learning has increased. A summary is provided on the use of both camera traps and machine learning and the main challenges that come with it by performing a general literature review. Remote cameras can be used in a variety of field applications, including investigating species distribution, disease transmission and vaccination, population estimation, nest predation, animal activity patterns, wildlife crossings, and diet analysis. Camera trapping has many benefits, including being less invasive, allowing for consistent monitoring and simultaneous observation (especially of secretive or aggressive animals even in dangerous or remote areas), providing photo/video evidence, reducing observer bias, and being cost effective. The main issues are that they are subject to their environment, dependent on human placements, can disrupt animal behaviour, need maintenance and repair, have limitations on photographic data, and are sensitive to theft and vandalism. When it comes to machine learning, the main aim is to identify species in camera (trap) images, although emerging technologies can provide individual recognition as well. The downsides in- clude the large amount of annotated data, computer power, and programming and machine learning expertise needed. Nonetheless, camera trapping and machine learning can greatly assist ecologists and conservationists in wildlife research, even more so as technology further develops.

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“…Goldingay et al., 2013; Linden et al., 2020; Teixeira et al., 2013) and for monitoring nests and nest boxes (e.g. Aguiar‐Silva et al., 2017; Kettel et al., 2016; Stojanovic et al., 2014). Studies evaluating the effectiveness of arboreal camera traps show that they are an effective tool for (a) inventorying arboreal communities, (b) providing accurate estimates of species richness in the canopy and (c) detecting species not identified by other survey methods (Bowler et al., 2017; Moore et al., 2020; Whitworth et al., 2016).…”

Section: The What Where and Why Of Arboreal Camera Trappingmentioning

confidence: 99%

The potential and practice of arboreal camera trapping

et al. 2021

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1. Arboreal camera trapping is a burgeoning method providing a novel and effective technique to answer research questions across a variety of ecosystems, and it has the capacity to improve our understanding of a wide range of taxa. However, while terrestrial camera trapping has received much attention, there is little guidance for dealing with the unique challenges of working in the arboreal realm.2. Our review draws on the expertise of researchers from six continents and the broader literature to investigate the advantages and disadvantages of arboreal camera trapping, and challenges to consider when using this technology. We also include mini-guides with detailed information on the current arboreal camera trap literature, mounts used to install arboreal cameras, tree climbing pointers and safety tips, methods for deploying cameras without climbing, and tips for managing interference with camera function.3. We find that arboreal camera traps have been most commonly used in the study of mammals in forests; however, there is potential for this method to be applied to a broad range of habitats including urban areas, and taxa such as birds, amphibians, invertebrates, and plants. Methods in arboreal camera trapping could be improved by developing a greater understanding of the factors affecting detection of species. The most common challenges of arboreal camera trapping are camera placement and camera site access. These can be overcome by understanding correct camera orientation, managing potential sources of interference in front of cameras, utilizing appropriate cameras mounts and training researchers properly. | 1769Methods in Ecology and Evoluঞon MOORE Et al.

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Camera Trapping at Harpy Eagle Nests: Interspecies Interactions Under Predation Risk

Cited by 13 publications

References 19 publications

Long-term concentration of tropical forest nutrient hotspots is generated by a central-place apex predator

Long-term concentration of tropical forest nutrient hotspots is generated by a central-place apex predator

A narrative review on the use of camera traps and machine learning in wildlife research

The potential and practice of arboreal camera trapping

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