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Methods for Monitoring Large Terrestrial Animals in the Wild


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Reliable information about wildlife is absolutely important for making informed management decisions. The issues with the effectiveness of the control and monitoring of both large and small wild animals are relevant to assess and protect the world’s biodiversity. Monitoring becomes part of the methods in wildlife ecology for observation, assessment, and forecasting of the human environment. World practice reveals the potential of the joint application of both proven traditional and modern technologies using specialized equipment to organize environmental control and management processes. Monitoring large terrestrial animals require an individual approach due to their low density and larger habitat. Elk/moose are such animals. This work aims to evaluate the methods for monitoring large wild animals, suitable for controlling the number of elk/moose in the framework of nature conservation activities. Using different models allows determining the population size without affecting the animals and without significant financial costs. Although, the accuracy of each model is determined by its postulates implementation and initial conditions that need statistical data. Depending on the geographical, climatic, and economic conditions in each territory, it is possible to use different tools and equipment (e.g., cameras, GPS sensors, and unmanned aerial vehicles), a flexible variation of which will allow reaching the golden mean between the desires and capabilities of researchers.
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Methods for Monitoring Large Terrestrial Animals in
the Wild
Alexander Prosekov 1, Alexander Kuznetsov 2, Artem Rada 2and Svetlana Ivanova 3, 4, *
1Laboratory of Biocatalysis, Kemerovo State University, Krasnaya Street 6, 650043 Kemerovo, Russia;
2Computer Engineering Center, Kemerovo State University, Krasnaya Street 6, 650043 Kemerovo, Russia; (A.K.); (A.R.)
3Natural Nutraceutical Biotesting Laboratory, Kemerovo State University, Krasnaya Street 6,
650043 Kemerovo, Russia
4Department of General Mathematics and Informatics, Kemerovo State University, Krasnaya Street 6,
650043 Kemerovo, Russia
*Correspondence:; Tel.: +7-384-239-6832
Received: 1 June 2020; Accepted: 23 July 2020; Published: 26 July 2020
Reliable information about wildlife is absolutely important for making informed
management decisions. The issues with the eectiveness of the control and monitoring of both
large and small wild animals are relevant to assess and protect the world’s biodiversity. Monitoring
becomes part of the methods in wildlife ecology for observation, assessment, and forecasting of the
human environment. World practice reveals the potential of the joint application of both proven
traditional and modern technologies using specialized equipment to organize environmental control
and management processes. Monitoring large terrestrial animals require an individual approach due
to their low density and larger habitat. Elk/moose are such animals. This work aims to evaluate
the methods for monitoring large wild animals, suitable for controlling the number of elk/moose
in the framework of nature conservation activities. Using dierent models allows determining the
population size without aecting the animals and without significant financial costs. Although,
the accuracy of each model is determined by its postulates implementation and initial conditions
that need statistical data. Depending on the geographical, climatic, and economic conditions in each
territory, it is possible to use dierent tools and equipment (e.g., cameras, GPS sensors, and unmanned
aerial vehicles), a flexible variation of which will allow reaching the golden mean between the desires
and capabilities of researchers.
monitoring methods; large wild animals; elk; moose; hunting; unmanned aerial vehicles
1. Introduction
It is dicult to overestimate the importance of monitoring animals in the wild as it is part of
the environmental control system. It includes monitoring, evaluating, and predicting the state of the
human environment. The problems of the control and monitoring eectiveness of both large and
small wild animals are relevant all over the world [
]. Today, modern monitoring methods are being
implemented. This is supported by the use of new monitoring technologies [2,3].
Wild animals are at risk during their co-existence with humans due to capture, extermination,
and anthropological impact on their habitat areas. Understanding the need to regulate the population
of dierent animals, including commercial species, partly solves the problem of preserving the fauna
diversity on our planet. Environmental monitoring issues concern the general public (ecologists,
biologists, hunters, statesmen, top managers, researchers, and ordinary citizens). Animal control
Forests 2020,11, 808; doi:10.3390/f11080808
Forests 2020,11, 808 2 of 12
takes into account various natural and man-made factors that aect the state of the environment.
Monitoring helps identify patterns of such changes and ensure proper environmental management.
In addition, it makes it possible to establish a correlation and find connections between biology, ecology,
and economics, e.g., hunting and eco-tourism.
Ideally, it is desirable to get an absolute estimate of wildlife populations [
]. However, in reality,
it is dicult to get data close to absolute. This problem is most acute for animals that live in hardly
accessible areas and vast territories, such as impenetrable taiga, jungles, and tropical forests.
Monitoring biodiversity on a large scale and with adequate representation requires significant
eort and resources, and presents a logistical challenge for researchers [
]. Monitoring schemes for
butterflies and birds [
] can be classified as successful projects of civil science, with the presentation of
a large amount of data on the occurrence of species as well as in terms of the number and distribution
of species. For animals, there are no such monitoring schemes; an attempt was made to initially
accumulate data for 21 candidates (genetic composition, species population, species characteristics,
community composition, ecosystem functioning, and ecosystem structure, [
Traditional wildlife counting methods (Table 1) are widely used throughout the world [
In the scientific context, dierent counting methods have been proposed for decades, and there is a
constant debate about their eectiveness.
Table 1. Traditional wildlife monitoring methods.
Method Animals Sources
Survey and questionnaire Large and medium-sized animals [1215]
Counting by traces of vital activity (counting
indirect signs-the number of burrows, claw
marks, the number of feces, etc.)
Large and medium-sized
mammals [1621]
Sampling and marking All animal species [2227]
Winter route tracking
Large, medium, and small animals,
birds [28,29]
The use of traps, pens, and nets Large and medium-sized
mammals [11,3033]
Remote tracking using specialized equipment
(camera traps, sensor nets, acoustic sensors,
and GPS sensors)
All animal, bird, and insect species
Aerial survey (counting, photo, and video
shooting from aerial devices and systems) Large animals [1,4952]
Researchers face an acute problem of choosing a method of control and observation for all animal
species, both small and large. Among other things, it depends on the habitat. Individual monitoring
methods have been developed for marine animals [
], insects [
], and terrestrial animals [
The size of the studied animals is also important for choosing the monitoring method. This review is
limited to considering only large terrestrial animals. Large animals are usually those with the highest
quantitative parameters of ontogenesis (weight, length, height, etc.) in their classes. Large forest
animals include elephant, rhinoceros, hippo, girae, bear, crocodile, tiger, etc.
The habitat of large terrestrial animals is assumed to be land. Russia occupies the first place in
terms of the area among the countries (almost half of its territory consists of forests with a rich variety
of flora and fauna). Bear (brown and polar), elk, and bison are considered to be the large animals of
Russian forests [61].
Elk are widely distributed throughout the world, including the Scandinavian Peninsula, Alaska,
the European part of Russia, and Western Siberia (including Kemerovo oblast—Kuzbass) [
An important commercial animal, elk is an object of sport hunting, wildlife watching, and a
protected species.
Forests 2020,11, 808 3 of 12
Elks inhabit forests, willows on the shores of steppe lakes, and river floodplains in forest-steppe;
they also love cool coniferous forests, where there is swampy soil. Elks do not usually actively use their
entire territory, but only a part of it, mainly where there are sucient stocks of the main seasonal feed
and good protective conditions throughout the year. Elks correspond to a high degree of settledness;
some individuals can adhere to a small area of the territory for a long time. They look for a new
place of residence when the amount of food decreases, for example, in the winter with a significant
height of snow cover; however, in the spring they return to their original place. A group of elk is
quite grouped—in winter they try not to scatter far from each other, but in spring they show more
independence. These animals adapt well to changing environmental conditions.
Some methods make it possible to estimate the population size based on relative counts, one of
which is distance sampling [
]. However, they do not apply to large animals for various reasons.
Populations of rare or elusive large mammals are dicult to control because they are usually secretive,
lone, occur at low densities, and have large domestic ranges, which poses significant methodological
problems for population estimation [
]. The elk population is rather small, so it is important to
assess the eectiveness of monitoring in the field of hunting as an environmental protection measure
for biological diversity support and endangered species preservation.
The purpose of this work is to assess methods for monitoring large wild animals that are suitable
for controlling elk within the Kuzbass nature protection measures. The need for this review is based
on the diversity of methods, the disparity of information about them, and the lack of a comprehensive
methodology for counting large wild animals and the prospect of combining dierent survey methods,
including the use of unmanned aerial systems in order to obtain the most reliable information.
2. Methods
Undertaken in November 2019 and updated in July 2020, the literature search considered the
articles published from 1 January 2015 until the present. Article databases from Scopus, Web of Sciences,
and Google Scholar were used for cross-checking. We used a search strategy based on multiple queries.
The final ones were selected after several search passes by qualitative evaluation of the number of
results obtained and their relevance.
Table 2lists the queries used and the number of articles identified by each query. The entire
bibliography of the included studies was manually checked for compliance with the search subject by
title and abstract. Articles whose titles and/or abstracts contained “moose/elk monitoring methods”
were passed to the full-text selection stage by default. To narrow the scope of the “Animal monitoring
methods” search, both the Scopus and Web of Science databases excluded publications from the
fields unrelated to the search topic (such as Medicine, Pharmacology, Immunology and Microbiology,
Neuroscience, Engineering, Chemistry, Computer Science, Physics and Astronomy, Social Science, etc.).
Due to the number of publications of the query in Google Scholar, sources from the year 2019 were
put under review. After excluding intersections across all search databases, 1205 sources remained
under review.
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Table 2. Strategies for searching the literature sources for the review.
Database Search Query Number of Articles Matching Search
Moose monitoring methods
[title/abstract/keywords] 19 8
Elk monitoring methods
[title/abstract/keywords] 20 2
Animal monitoring methods
[title/abstract/keywords] 1976 827
Moose monitoring methods 17 8
Elk monitoring methods 19 5
Animal monitoring methods
499 322
Google Scholar Moose monitoring methods 11,800 468
Elk monitoring methods 16,300 231
* Even indirect matching was taken into account
3. Results and Discussion
The global experience of wildlife monitoring is represented by the use of various traditional
counting methods. These include observation, trapping, experiments, collection, analysis of
demographic data, and surveys of reserve employees [1214,17,25,66].
3.1. Active Observation Methods
The method of trapping using box traps, trap pens, drip nets, independently or in combination
with indirect indicators, allows assessing the impact of traps on the population of wild animals to
determine their density and identify the risk of disease. This method is a traditional one, and using
several methods together can improve its accuracy. However, the quality of its application is directly
dependent on the number of qualified professionals engaged; any attempt to save finances leads
to errors in monitoring and external negative impact on the studied animal population with all the
resulting negative consequences [
]. It is possible to improve the monitoring accuracy by identifying
individual species, but in this case, it is necessary to physically impact the animals, which can be
invasive, expensive, and dicult from the point of view of logistics [67].
3.2. Passive Observation Methods
The authors of [
] used surveys of hunters in the Northeastern and upper Midwestern regions
of the United States (approximately 11,000 hunters annually between 2012 and 2014) to monitor the
number of elk (Alces alces) and collect information. The study [
] presents the results of testing a
smartphone application for interviewing hunters (Alberta, Canada, during 2012–2014) for reporting
the number of elk (Alces alces). The potential of the developed application Loose Survey and its
cost-eectiveness in comparison with more expensive methods of the aerial survey are underlined.
However, the human factor should be taken into account as it can significantly reduce the accuracy of
this approach.
Observation of winter routes [
] from ungulate tracks is one of the oldest large animal
monitoring methods, which are used to track changes in an animal’s moving path, habitat, winter
shelters, breeding grounds, and to determine the population size. The main advantages of this method
are long-term usage possibility, low financial costs, and feasibility. While, the list of disadvantages
includes the occurrence of errors and unreliability of the data obtained, whose value is not stable, as
well as the presence of a human factor. Obermoller et al. used the method of observing the movement
dynamics of female species to estimate the number of elk calves, and the data obtained were extended
to the population size by applying modeling [
]. Migration appears to be an eective behavioral
strategy for extending access to seasonal resources and can be a sustainable strategy of industrial
Forests 2020,11, 808 5 of 12
centers or settlements for ungulates experiencing climate change [
]. If the snow cover is not high
enough, it is either not possible to collect data on the number of animals or they have significant
distortions [73].
The method of monitoring ungulates based on counting the number of fecal pellets is among the
traditional ones [
]. It is used both as the main and complementary methods [
]. Blåhed et al.
optimized the SNP (single nucleotide polymorphism) genotyping of fecal samples from elk (Alces alces)
for identification of a species and its gender (489 fecal samples) [
]. Together with other traditional
methods, genetic methods allow specifying the number of animals and complete information about
the sex ratio, settlement, reproduction, and genetic variability. Pfeer et al. compared the results of the
obtained numbers of elk (Alces alces) and roe deer (Capreolus capreolus) in Northern Sweden after using
fecal count and camera traps together with the random encounter model (REM), which can estimate
the density without having to recognize individual species [
]. The authors found that, compared to
density estimates from camera traps, fecal counts appear to underestimate the population density for
roe deer. For elk, the data obtained from the two methods were comparable. In comparison with other
methods, the method of counting groups of pellets has the main advantage—cost eectiveness—and
can be used in areas that are not impenetrable forests.
3.3. Remote Monitoring
Remote monitoring involves the use of specialized equipment (photo and video equipment,
acoustic devices, and sensors), usually providing not only data collection, but also almost real-time
data transmission. The most reliable data can be obtained by organizing constant automatic
monitoring—continuous automatic tracking of animals in real-time [
]. There are enough advantages
of this control method, although it is dicult to implement it in remote wild areas (lack of a steady
connection, inability to ensure uninterrupted operation of batteries, maintenance of equipment,
and sensors used). Therefore, the scope of application is limited to small hunting farms or reserves
located not too far away from industrial centers.
Tracking methods using a wireless sensor network (WSN) can achieve similar goals. Zhang and
team [
] used simulation modeling based on the collected data to obtain a more reliable picture of the
sika deer population.
There is a relatively new group of visual and acoustic wild animal monitoring methods using
automatic recorders. Tracking technologies allow researchers to study the life of nature with huge
spatial and temporal resolution. They have been developed relatively recently to assess biodiversity
by measuring the acoustic heterogeneity created by animals in natural habitats [36].
Monitoring methods using camera traps and acoustic sensors are considered cost-eective [
The list of advantages includes the ability to simultaneously evaluate various indicators.
The eectiveness and adequacy of these methods determine the potential for their use in the long
term. With the development of technologies to produce widely available hardware and software,
the methods will be extensively applied.
Night photography, telemetering, and camera traps in combination with the search and calculation
of indirect indicators (traces of vital activities) were simultaneously used to determine the number of
elk (Cervus canadensis) [81].
Visual observation methods using GPS location and digital visualization (3D) images are among
the relatively new monitoring methods, that have already proven their eectiveness for environmental
activities. Remote sensing methods (GPS or geolocation) present a comprehensive analysis of various
data. Monitoring methods using 2D and 3D cameras create a “presence eect” in the process of
detecting an animal. They provide an automated, non-contact, and cost-eective way to study animal
behavior. Digital technologies and Big Data allow us to approach wildlife monitoring in a dierent way
considering its versatility. The integrated use of aerial photography methods with the interpretation
of indirect signs (the number of tracks) contributes to the overall eectiveness of the monitoring.
Forests 2020,11, 808 6 of 12
The significant cost of visual observation methods using digital technologies does not expand the
possibilities of their application [34,35,38].
Smith et al. determined the migration routes and numbers of elk by observing and collecting
data from global positioning system (GPS) collars [
]. The authors modeled the seasonal selection of
habitat-related resources. Phillips et al. determined the number of elk using a probabilistic model
combined with GPS collar detection data [
]. The reliability of the obtained population size estimates
was recognized as an advantage. The risks include the use of this model in territories with dierent
characteristics. It is important to consider the factors under which this model is valid. Bergman et al.
jointly analyzed the data obtained from field route observations of elk and GPS collars and came to the
conclusion about the economic eciency and benefits of their joint use [84].
3.4. Methods of Aerial Survey
Many problems with the previously described methods can be avoided with the help of an
aerial survey. Bristow et al. used several approaches to estimate the number of elk in Arizona: the
eciency of the hybrid model (double-counting and double-observer methods) was compared to the
traditional tracking by tagging and recording individual animals during helicopter flights [
]. In terms
of economy, the hybrid model is preferable, while in terms of precision, an aerial survey is better.
The development of the hybrid model was more expensive than using traditional counting methods.
The development of unmanned aerial vehicles has opened up new opportunities for using them
to solve civil tasks. Unmanned aerial vehicles (UAVs) and continuous shooting (photo, video, and IR)
are a sustainable and eective group of modern methods of wildlife recording. Monitoring methods
using UAVs can determine the number of animals in a given area. This method can be used for one or
several types of species.
The authors [
] used unmanned aerial vehicles with consumer-level digital cameras to
count the number of elk. Havens and Sharp used a modified drone “Predator” for this purpose [
Patterson et al. used small unmanned aerial systems (UAS) for aerial photography of caribou (reindeer
of North America, Labrador, Canada) and recognized the advantages and capabilities of a small
electric-powered fixed-wing UAS Brican TD100E [92].
Xu et al. [
] used aerial photography from a quadrocopter to estimate the number of large horned
animals, including elk, in combination with a system for processing RGB images. To detect and count
large horned individuals, the RGB image obtained by the drone was processed with a modern machine
learning algorithm.
The authors underlined the performance and eciency of this model. Shao et al. [
] used the
method of aerial photography using UAVs to count large horned animals, including elk. A system based
on convolutional neural networks (CNNs) using aerial photographs was applied. Witczuk et al. [
used drones with thermal infrared imaging to count ungulates. Dziki-Michalska et al. [
] analyzed
data collected by volunteers, hunters, and foresters in combination with aerial photography. Data on
the abundance of large animals, including moose, collected from various sources, were used to construct
regression models. The authors note that the use of aerial photography increases the accuracy of the
modeling, but significant financial costs do not allow its use on an ongoing basis.
UAV aerial photography is very promising with regard to the development of geospatial data
collection methods. They are justified in cases where it is necessary to get accurate information about
the area at a certain time. The main advantages of UAVs are the following: the ability to automatically
detect almost all animals, both in semi-arid savannas and areas with significant vegetation; the
accuracy of the results obtained; high-quality images; and fast data processing. Despite its eectiveness,
the latter method is not often used as it is quite costly, even though they are cheaper to operate
than helicopters and manned fixed-wing aerial vehicles. UAVs require special piloting skills, have
limitations on their use over large spatial and temporal scales, including regulations, and depend on
weather conditions [51,8691].
Forests 2020,11, 808 7 of 12
4. Conclusions
Eective monitoring issues are problematic within the framework of foreign and domestic science.
In many territories (Alaska, Canada, Scandinavian countries, and Siberia), biologists, researchers,
and hunting farm employees traditionally walk around the property and count the tracks of animals
(elk, deer, roe, etc.), making an absolute (counting all individuals of the territory) or relative (counting
a part of the animals and obtaining an idea of the entire population using the appropriate conversion
factors) census [
]. The size of the territories, their inaccessibility, a lack of funding for hunting
farms and natural territories, as well as adverse weather conditions impede the spread of modern
wildlife control and monitoring methods. World practice confirms the need to modernize monitoring
technologies and the readiness to use new methods, if they take into account most of the disadvantages
of the traditional methods (full snow cover, low accuracy, and non-dependence on weather conditions
and vegetation cover), if there is technical support or instructions, and in case they do not exceed the
cost of existing methods.
It has already been proven eective to use several methods simultaneously with specialized
equipment, such as photo traps, video-, or IR cameras. If the observation area is accessible and limited,
and the number of animals is insignificant, to obtain reliable information about the population size,
it is sucient to mark them, as described in [
], with GPS collars [
]. If the terrain conditions allow,
a stationary camera with a GPS sensor will allow getting almost complete information at a fairly low
cost. However, there are areas with vegetation that does not allow free movement, while there is no
other way to monitor elk or other large animals with UAVs. It is known that the eectiveness of animal
detection by UAVs significantly increases with the use of infrared detectors in low-altitude flights [
The use of these technologies to detect and enumerate groups of wild animals in wildlife monitoring
is superior to conventional remote sensing technologies [
], but improvements in detection and
identification technology are needed to exceed the accuracy of traditional aerial photography of
animals [102,103].
Author Contributions:
Conceptualization, A.P., A.K. and A.R.; methodology, A.K.; analyzed and interpreted the
data, S.I.; formal analysis, A.R.; resources, A.K.; data curation, A.K. and S.I.; writing—review and editing, S.I. and
A.P.; project administration, A.P. All authors have read and agreed to the published version of the manuscript.
This research was financial supported MINISTRY OF SCIENCE AND HIGHER EDUCATION OF
THE RUSSIAN FEDERATION, project number 075-15-2020-540 (unique project identifier RFMEFI62120X0037),
and partially financial supported by theCOUNCIL ON GRANTS OF THE PRESIDENT OF THE RUSSIAN
FEDERATION,grant number[SS-2694.2020.4].
Conflicts of Interest: The authors declare no conflict of interest.
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... In the conditions of limited natural resources, the effectiveness of environmental management decisions depends on an accurate and timely analysis of environmental data. Therefore, improved methods of information collecting and processing can lower the environmental impact of managerial actions in the sphere of rational exploitation of natural resources and natural balance [7][8][9][10][11]. A consistent approach to environmental management requires new systems of effective environmental monitoring. ...
... Animal surveys contribute to the rational conservation of biodiversity. A proper analysis of statistics on migration, fertility and mortality can reveal cases of poaching and assess its real scale [3,4,6,10,11,14]. A competent approach provides basic data for informed managerial decisions on the matters of animal population as an integral part of national wealth [15][16][17][18][19]. Animal survey is an important control factor that helps to balance socio-economic and natural interests. ...
... A competent approach provides basic data for informed managerial decisions on the matters of animal population as an integral part of national wealth [15][16][17][18][19]. Animal survey is an important control factor that helps to balance socio-economic and natural interests. The existing methods are based on direct counting or indirect evidence, e.g., footprints, feces, etc., as their results often prove unreliable [10,14,17,20,21]. Based on old databases, these methods are expensive and time-consuming [22]. ...
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... Effective management of threatened and invasive species requires regular and reliable population estimates, which in turn depend on accurate detection of individual animals [1][2][3][4][5][6][7]. Traditional methods of monitoring, such as conducting surveys along transects using ground-based experts, can be expensive and logistically challenging [3,[8][9][10][11][12]. Surveying the large areas required for robust abundance estimates in a cost-effective way is also problematic [3,10]. ...
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Effective management of threatened and invasive species requires regular and reliable population estimates. Drones are increasingly utilised by ecologists for this purpose as they are relatively inexpensive. They enable larger areas to be surveyed than traditional methods for many species, particularly cryptic species such as koalas, with less disturbance. The development of robust and accurate methods for species detection is required to effectively use the large volumes of data generated by this survey method. The enhanced predictive and computational power of deep learning ensembles represents a considerable opportunity to the ecological community. In this study, we investigate the potential of deep learning ensembles built from multiple convolutional neural networks (CNNs) to detect koalas from low-altitude, drone-derived thermal data. The approach uses ensembles of detectors built from combinations of YOLOv5 and models from Detectron2. The ensembles achieved a strong balance between probability of detection and precision when tested on ground-truth data from radio-collared koalas. Our results also showed that greater diversity in ensemble composition can enhance overall performance. We found the main impediment to higher precision was false positives but expect these will continue to reduce as tools for geolocating detections are improved. The ability to construct ensembles of different sizes will allow for improved alignment between the algorithms used and the characteristics of different ecological problems. Ensembles are efficient and accurate and can be scaled to suit different settings, platforms and hardware availability, making them capable of adaption for novel applications.
... Elephant conflict monitoring has been an integral part of wildlife tracking systems accompanied by other methods in wildlife ecology for observation, assessment, and forecasting of the human environment [12], implementation and identification by means of the Wi-Fi-based wireless controller, consuming transmitter node, pillars consisting of a vibration sensor, an electronic unit with buzzer, laser diode, and laser detector [33], accompanied by global positioning system (GPS) technologies. Wireless sensor network (WSN). ...
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... • Censuses: authorities need to periodically obtain animal counts to monitor the health of the animals in wildlife parks, game centers, hunting grounds, etc. [1,2]; ...
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... But the development of unmanned aircraft has accelerated dramatically due to the widespread use of global positioning systems such as GPS. In the 2010s, unmanned aerial vehicles began to be widely used for civilian purposes -in agriculture, mining, for monitoring power lines, observing natural disasters, etc. [2,3]. Usually, unmanned aircraft are understood as unmanned aerial vehicles heavier than air, similar to an ordinary plane or helicopter, only smaller. ...
Conference Paper
The purpose of the study is to determine the state and strategic alternatives for the development of the Russian market for aerostats on the basis of marketing research. The work used the methods of primary analysis and systematization of commercial information, SWOT analysis, the method of expert assessments, and determination of the degree of consistency by the Kendall coefficient of concordance. The initial analysis of commercial offers, materials of manufacturers' websites showed that a wide range of lighter-than-air aircraft is presented on the national market for solving various tasks. To assess the strategic prospects of the market, a SWOT analysis was carried out. Its factors were ranked based on peer review. As a result, two most promising strategic alternatives were identified: the use of airships for transporting goods in poorly developed regions of the North of Russia, the use of aerostats as stationary observation posts. In these areas, the competitive advantages of aerostats correspond to the prospects for economic development. The main problem in the development of the Russian aerostat market is overcoming the QWERTY effect (absolute dominance of aircraft heavier than air) in conditions of low investment activity.
... Post-release monitoring is a very useful tool to evaluate animals' fitness and further strengthen wildlife management practices (Myers and Young 2018;Mandlate et al. 2019;Prosekov et al. 2020). The effective monitoring of an endangered population, and associated conservation planning, requires detailed information relating to behavioral and demographic information (Bhattarai and Kindlmann 2018). ...
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Sukmasuang R, Bhumpakphan N, McShea WJ, Wajjwalku W, Siriaroonrat B, Kamolnoranart S, Yindee M, Nipanan T, Maleehuan B, Khanthathongsakuldee K, Pongcharoen C, Sutummawong N, Thomas W. 2022. Review: The status of the endangered Eld’s deer (Rucervus eldii) and conservation actions in Thailand. Biodiversitas 23: 5020-5034. The endangered Eld’s deer (Rucervus eldii) once roamed throughout the plains and dry forests of South and Southeast Asia. However, due to heavy poaching and habitat loss, the population has declined drastically and has disappeared from many of its historical ranges. They are presently found in some natural areas of India, Myanmar, Cambodia, Lao PDR, and Hainan Island, China. Thailand used to be the distribution center of the species, where two subspecies, the R.e. thamin and R.e. siamensis, were found. However, both subspecies have disappeared from the natural resources of Thailand since the early 1990s. Many conservation programs have been conducted to save this species in Thailand, such as captive breeding and reintroduction. Our literature review revealed that currently, more than a thousand R.e. thamin are housed in over 20 wildlife breeding facilities and 109 R.e. siamensis in 8 breeding facilities. Based on the workshops on conservation and restoration of the species, suitable genetic selection can create populations suitable for return to protected forest areas in Thailand. At present, more than 554 R.e. thamin have been released back into the wild in 8 wildlife sanctuaries, 3 national parks and 1 non-hunting area and 27 R.e. siamensis were released in 2 wildlife sanctuaries in Thailand. The follow-up of the deer in the release areas was flawed. Major knowledge gaps include recent trends in the population dynamics, habitat selection, diet items and threats. Identifying and restoring suitable dry forest habitats for reintroduction are also keys for species conservation.
... Aerial surveys and drone-mounted infrared cameras are able to solve a wide range of tasks, e.g. maintaining linear infrastructure facilities, tracking forest fires, monitoring construction and mining operations, counting game population, looking for missing people, developing smart city projects, etc. [23][24][25][26][27][28]. UAVbased aerial surveys are cheap and require no physical presence on location, thus preventing subjective and objective human errors [29]. ...
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Cadastral and geodetic land works are expensive, which makes aerial photography extremely valuable for land traceability and inventory. The present research objective was to develop a new digital survey technology for registration of agricultural lands. We assessed the accuracy of the new method and evaluated its decision support options. The study featured the case of the Kemerovo Region (Kuzbass), Russia. The aerial survey took place in 2021 and involved 17 municipalities of the Kemerovo Region. The software and hardware complex included an unmanned aerial vehicle (UAV) and a module for aerial photography. Photogrammetric, cartometric, and satellite methods were used to define the coordinates of feature points. We developed new software (Sovhoz.avi) to perform the land inventory. The photogrammetric and cartographic methods proved efficient in determining the feature points and boundaries of land plots. They also appeared accurate enough for land inventory and decision support. The study updated the available land inventory data. About 30% of all land plots were recorded incorrectly; some plots marked as agricultural appeared to belong to the local forest reserves or urban territories. Incorrect data (1.64%) were excluded from the official inventory. The survey covered a total area of 41 000 ha and revealed 1700 illegally used land plots. The updated inventory of unused lands included 3825 new plots (163 400 ha), which can attract prospective investors. The results can be used by the local authorities to make land management decisions and identify illegal land use.
... The notable scarcity of robust, long-term studies is likely due to the expense and logistical challenges associated with monitoring ungulate populations at the appropriate scale of the landscape or region [55,56]. Technical advances and the decreasing cost of remote sensing technologies, such as motion-activated cameras and unmanned aerial vehicles, provide new opportunities for ungulate population monitoring, which can be used to overcome this deficit in the current evidence-base [57,58]. ...
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Introduction: Over recent decades, the abundance and geographic ranges of wild ungulate species have expanded in many parts of Europe, including the UK. Populations are managed to mitigate their ecological impacts using interventions, such as shooting, fencing and administering contraception. Predicting how target species will respond to interventions is critical for developing sustainable, effective and efficient management strategies. However, the quantity and quality of evidence of the effects of interventions on ungulate species is unclear. To address this, we systematically mapped research on the effects of population management on wild ungulate species resident in the UK. Methods: We searched four bibliographic databases, Google Scholar and nine organisational websites using search terms tested with a library of 30 relevant articles. Worldwide published peer-reviewed articles were considered, supplemented by 'grey' literature from UK-based sources. Three reviewers identified and screened articles for eligibility at title, abstract and full-text levels, based on predefined criteria. Data and metadata were extracted and summarised in a narrative synthesis supported by structured graphical matrices. Results: A total of 123 articles were included in the systematic map. Lethal interventions were better represented (85%, n = 105) than non-lethal interventions (25%, n = 25). Outcomes related to demography and behaviour were reported in 95% of articles (n = 117), whereas effects on health, physiology and morphology were studied in only 11% of articles (n = 14). Well-studied species included wild pigs (n = 58), red deer (n = 28) and roe deer (n = 23). Conclusions: Evidence for the effects of population management on wild ungulate species is growing but currently limited and unevenly distributed across intervention types, outcomes and species. Priorities for primary research include: species responses to non-lethal interventions, the side-effects of shooting and studies on sika deer and Chinese muntjac. Shooting is the only intervention for which sufficient evidence exists for systematic review or meta-analysis.
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Hunting is a complex type of nature management. In its process, objects of the animal world and the earth are used. Obviously, the relationship between hunters and other land users should be clearly regulated by legislation. The purpose of this work was to identify common and specific problems for different systems of interaction between hunters and land owners and to assess the possibility of spreading the existing experience of solving problems faced by the hunting sector to different countries. Three main models of the relationship between hunters and land users (direct interaction, cooperation, and division of rights) are considered. Each of the models performs its tasks and has its own degree of efficiency. The interaction organization model adopted in a country depends on the specifics of the conditions in which the hunting farm develops including economic, property, legal, social, and state aspects. It is established that the availability of hunting is best ensured within the framework of the cooperation model, the observation of the rights of owners—within the direct interaction model, the convenience of management within large territories of wild animal habitats—within the division of rights model. At the same time, it is incorrect to single out the best model by all criteria or to designate a model that is universally suitable for different conditions. In the hunting farms of Russia, the described problems of interactions are not related to the potential of the division of rights model as such, but to a lack of understanding that this particular model requires increased attention of the state. The proposals aimed at improving the practice of developing and applying models of relationships between hunters and land users are represented.
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Direct monitoring of wild animals' behavior is challenging and data tampering. Instrument the animals with collars that embeds sensors, such as tri-axial accelerometer and GPS, allows obtaining sufficient information for remotely classifying the performed activities. In this work is presented an accurate and human intelligible framework, designed leveraging the authors' skills in machine-learning and data analysis. The system covers all the steps required to accurately map the raw signals to the activities carried out, grouped in pre- processing, features extraction and selection, and classification phases. A case of study consists of a dataset collected by the Crofoot Lab at the Mpala Centre, in Kenya, instrumenting free-ranging Olive Baboons. This dataset provides both sensors time-series paired with respective activity labels and unlabeled ones. Labeled data was used to tune the parameters of the framework phases and to train and test the employed boosted- trees classifiers, while unlabeled ones were used for further system validations. The average accuracy obtained on a single activity is 94.5%. At best of the authors' knowledge, this is the first work that aims to solve the problem of direct human monitoring with such high accuracy, outperforming the state of the art by a lift about 10%. The main contribution of the proposed systems consists of the attention paid to the ethologist's needs. Together with the predictions, the framework also returns a ranking for the features considered, based on their importance in the decision-making process of the classifier. Therefore, the extracted features are consistent with the logical human path that the ethologist follows in performing direct monitoring. The produced framework has also been designed consistently with the ethogram structure to be easily interpretable and to allow activities classification at different aggregation levels.
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Camera trap technology has galvanized the study of predator‐prey ecology in wild animal communities by expanding the scale and diversity of predator‐prey interactions that can be analyzed. While observational data from systematic camera arrays have informed inferences on the spatiotemporal outcomes of predator‐prey interactions, the capacity for observational studies to identify mechanistic drivers of species interactions is limited. Experimental study designs that utilize camera traps uniquely allow for testing hypothesized mechanisms that drive predator and prey behavior, incorporating environmental realism not possible in the lab while benefiting from the distinct capacity of camera traps to generate large data sets from multiple species with minimal observer interference. However, such pairings of camera traps with experimental methods remain underutilized. We review recent advances in the experimental application of camera traps to investigate fundamental mechanisms underlying predator‐prey ecology and present a conceptual guide for designing experimental camera trap studies. Only 9% of camera trap studies on predator‐prey ecology in our review mention experimental methods, but the application of experimental approaches is increasing. To illustrate the utility of camera trap‐based experiments using a case study, we propose a study design that integrates observational and experimental techniques to test a perennial question in predator‐prey ecology: how prey balance foraging and safety, as formalized by the risk allocation hypothesis. We discuss applications of camera trap‐based experiments to evaluate the diversity of anthropogenic influences on wildlife communities globally. Finally, we review challenges to conducting experimental camera trap studies. Experimental camera trap studies have already begun to play an important role in understanding the predator‐prey ecology of free‐living animals, and such methods will become increasingly critical to quantifying drivers of community interactions in a rapidly changing world. We recommend increased application of experimental methods in the study of predator and prey responses to humans, synanthropic and invasive species, and other anthropogenic disturbances.
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[This corrects the article DOI: 10.1371/journal.pbio.3000193.].
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A decade after environmental scientists integrated high‐throughput sequencing technologies in their toolbox, the genomics‐based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end‐users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or “in development”, hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics‐based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (A) Taxonomy‐based analyses focused on identification of known bioindicators or described taxa; (B) De novo bioindicator analyses; (C) Structural community metrics including inferred ecological networks; and (D) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programs that leverage recent analytical advancements, while pointing out current limitations and future research needs.
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Monitoring biodiversity characteristics at large scales and with adequate resolution requires considerable effort and resources. Overall, there is clearly a huge scope for European hunters, a special and often overlooked group of citizen scientist, to contribute even more to biodiversity monitoring, especially because of their presence across the entire European landscape. Using the Essential Biodiversity Variables (EBVs) framework we reviewed the published and grey literature and contacted experts to provide a comprehensive overview of hunters’ contributions to biodiversity monitoring. We examined the methods used to collect data in hunter-based monitoring, the geographic and taxonomic extent of such contributions and the scientific output stemming from hunter-based monitoring data. Our study suggests that hunter-based monitoring is widely distributed across Europe and across taxa as 32 out of the 36 European countries included in our analysis involve hunters in the monitoring of at least one species group with ungulates and small game species groups which have the widest hunter-based monitoring coverage. We found that it is possible to infer characteristics on Genetic composition, Species population, Species traits and Community composition with data that are being routinely collected by hunters in at least some countries. The main types of data provided are hunting bags data, biological samples including carcasses of shot animals and non-invasive samplings and Observations for counts and indices. Hunters collect data on biodiversity in its key dimensions. Collaborations between hunters and scientists are fruitful and should be considered a standard partnership for biodiversity conservation. To overcome the challenges in the use of hunters’ data, more rigorous protocols for sampling data should be implemented and improvements made in data integration methods.
In this research, we suggest a framework for the detail wildlife monitoring based on video surveillance. Camera traps are located on the remote territories of natural parks in the habitats of wild animals and birds. In spite of the dominant connectivity and sensing technology for wildlife monitoring are based on the wireless sensor networks, such technology cannot be applied in some cases due to vast impassable territories, especially in Siberian part of Russia. Based on our previous investigations in this research topic, we propose the main approaches and methods for big data collection, processing, and analysis useful for the management of natural parks and any wildlife habitat.
The ecological monitoring in Marine Protected Areas (MPAs) needs technological implementation to achieve the standard required for an advanced ecosystem management. This paper describes the use, and provide the initial results of a continuous time-lapse image monitoring system, cabled with underwater cameras located in a Natura 2000 site: Šibenik (Croatia, 43°44′9.85″N and 15°52′37.62″E, in the Adriatic Sea). The images of the mobile megafauna recorded during daylight hours from January 10 to the end of April 2018 were analysed. Overall, 13,808 images were analysed and a total of 136,195 animals were identified. A total of 16,216 fish specimens, belonging to 35 species, were identified from 10,026 images. These included 24 species of commercial interest, including the billfish Thunnus thynnus (Atlantic bluefin tuna) and animals of conservation interest such as the loggerhead turtle, Caretta caretta. The data collected in the time series showed an increase of fish biodiversity from winter to spring. Permutational Multivariate Analysis of Variance (PERMANOVA) revealed significant daily and seasonal changes in the assemblage structure. Canonical Analysis of Principal Coordinates and Principal Component Analysis indicated that fish assemblages were characterized by significant temporal changes at the mean Trophic Level and in the presence of different Functional Groups. Advantages and constraints of an image-based monitoring approach by cabled camera are discussed in relation the potential applications within the frame of international management programs, including the Marine Strategy Framework Directive (MSFD).
The wild boar (Sus scrofa) is a problematic invasive species which has colonized the threatened Brazilian Atlantic Forest. Our objective was to evaluate if population control and seasonality affect the circadian rhythm of wild boar activity. Wild boar activity was monitored by camera-traps for 1 year without population-control methods and 1 year with population-control methods implemented in the area. Before population control was implemented, wild boar activity was uniform across 24 h, with animals being active at any given time (cathemeral). After the population control, wild boars concentrated their activities on the daylight period. Also, wild boars were more active during the wet season, possibly influenced by the presence of seeds of Araucaria angustifolia trees. Based on these results, control measures should be conducted during the wet season and different management strategies, such as the use of rifles with telescopic sights and silencers, should be tested.
The rapid improvement of camera traps in recent decades has revolutionized biodiversity monitoring. Despite clear applications in conservation biology, camera traps have seldom been used to model the abundance of unmarked animal populations. The goals of this review are to summarize the challenges facing abundance estimation of unmarked animals, present an overview of existing analytical frameworks, and provide guidance for practitioners seeking a suitable method. When a camera records multiple detections of an unmarked animal, one cannot distinguish whether the images represent multiple mobile individuals or a single individual repeatedly entering the camera viewshed. Furthermore, animal movement obfuscates any clear definition of the sampling area, and as a result, the area to which an abundance estimate corresponds. Recognizing these challenges, we identify six analytical approaches and review 927 camera trap studies published between 2014 and 2019 to assess the use and prevalence of each method. Only about 5% of the studies use any of the abundance estimation methods we identify. Of these, most studies estimate local abundance or covariate relationships rather than using models to predict abundance or density over broader areas. Next, we provide a primer on the data requirements, assumptions, advantages, and disadvantages of each analytical approach. Finally, we provide a series of considerations to help practitioners select a suitable method for their particular applications and call for a broad-scope simulation study to compare the performance of the methods under common conditions. The challenge of estimating abundance of unmarked animal populations persists despite multiple potential methodologies, as no one method appears to be the best solution for use with camera traps. As analytical frameworks continue to evolve and abundance estimation of unmarked animals becomes increasingly common, camera traps will become even more important for informing conservation decision-making. Article impact statement: Camera traps have yet to meet their potential to model abundance of unmarked animals, but methods are emerging to meet the need. This article is protected by copyright. All rights reserved.