DEAR EDITOR,Big cats,such as Amur tigers(Panthera tigris altaica)and Amur leopards(P.pardus orientalis),are apex predator and have evolved specialized traits for hunting and carnivory(Moya et al.,2022),thus playing a ...DEAR EDITOR,Big cats,such as Amur tigers(Panthera tigris altaica)and Amur leopards(P.pardus orientalis),are apex predator and have evolved specialized traits for hunting and carnivory(Moya et al.,2022),thus playing a crucial role in maintaining biodiversity and ecosystem integrity by regulating prey-predator dynamics.However,human-induced pressures,habitat fragmentation,and environmental alterations have restricted these species in small and isolated populations.Currently,all extant big cats are categorized as endangered or threatened according to their conservation status.Amur tigers and Amur leopards share overlapping geographic ranges,habitats,and certain prey species in the forests of Northeast Asia(Jiang et al.,2015).To reduce interspecies conflict,these carnivores exhibit differentiated dietary and temporal niches.Amur tigers predominantly prey on large ungulates,while Amur leopards hunt small to medium-sized animals(Sugimoto et al.,2016).Additionally,they occupy different temporal niches,with tigers being active at night and leopards more active during the day.Despite spatial and temporal niche partitioning,interspecific competition between these two species is inevitable.Tigers,benefiting from their greater size,have a competitive advantage over leopards,which can manifest in occasional leopard predation by tigers and declines in leopard populations with increasing tiger density(Jiang et al.,2015).Tigers also displace leopards from marginal habitats in nature reserves where they coexist.展开更多
In modern wildlife ecological research,feces is the most common non-invasive source of DNA obtained in the field and polymerase chain reaction(PCR) technology based on microsatellite markers is used to mine genetic in...In modern wildlife ecological research,feces is the most common non-invasive source of DNA obtained in the field and polymerase chain reaction(PCR) technology based on microsatellite markers is used to mine genetic information contained within.This is especially the case for endangered species.However,there are risks associated with this genotyping method because of the poor quality of fecal DNA.In this study,we assessed genotyping risk across 12 microsatellite loci commonly used in previous tiger studies using blood and fecal DNA from captive Amur tigers(Panthera tigris altaica).To begin,we developed an index termed the accumulated matching rate of genotypes(R)between positive DNA(blood samples) and fecal DNA to explore the correct genotyping probability of a certain microsatellite locus.We found that different microsatelliteloci had different genotyping risks and required different PCR amplification protocols.The genotyping errors we detected altered population genetic parameters and potentially impact subsequent analyses.Based on these findings,we recommend that:(1) four loci(E7,Fca094,Pti007 and Pti010) of 12 loci are not suitable for Amur tiger genetic research because of a low Rand difficulty reaching a stable status;(2) the Rof the 12 microsatellite loci plateaued differently,and considering limited budgets,amplification times of some loci could be increased when using fecal samples; and(3) future genetic analysis of wild Amur tigers should be corrected by genotyping error rates(1-R).展开更多
Ecosystem engineers are organisms that alter the distribution of resources in the environment by creating,modifying,maintaining and/or destroying the habitat.They can affect the structure and function of the whole eco...Ecosystem engineers are organisms that alter the distribution of resources in the environment by creating,modifying,maintaining and/or destroying the habitat.They can affect the structure and function of the whole ecosystem furthermore.Burrowing engineers are an important group in ecosystem engineers as they play a critical role in soil translocation and habitat creation in various types of environment.However,few researchers have systematically summarized and analyzed the studies of burrowing engineers.We reviewing the existing ecological studies of burrowing engineer about their interaction with habitat through five directions:(1)soil turnover;(2)changing soil physicochemical properties;(3)changing plant community structure;(4)providing limited resources for commensal animals;and/or(5)affecting animal communities.The Chinese pangolin(Manis pentadactyla)is a typical example of burrowing mammals,in part(5),we focus on the interspecific relationships among burrow commensal species of Chinese pangolin.The engineering effects vary with environmental gradient,literature indicates that burrowing engineer play a stronger role in habitat transformation in the tropical and subtropical areas.The most common experiment method is comparative measurements(include different spatial and temporal scale),manipulative experiment is relatively few.We found that most of the engineering effects had positive feedback to the local ecosystem,increased plant abundance and resilience,increased biodiversity and consequently improved ecosystem functioning.With the global background of dramatic climate change and biodiversity loss in recent decades,we recommend future studies should improving knowledge of long-term engineering effects on population scale and landscape scale,exploring ecological cascades through trophic and engineering pathways,to better understand the attribute of the burrowing behavior of engineers to restore ecosystems and habitat creation.The review is presented as an aid to systematically expound the engineering effect of burrowing animals in the ecosystem,and provided new ideas and advice for planning and implementing conservation management.展开更多
Optimal escape theory predicts that animals would balance the costs and benefits of flight. One cost of not fleeing is the ongoing cost of vigilance for upcoming environmental threats. Our results show that FID increa...Optimal escape theory predicts that animals would balance the costs and benefits of flight. One cost of not fleeing is the ongoing cost of vigilance for upcoming environmental threats. Our results show that FID increases for vigilant hares with predator starting distance, due to the costs acquired by continuing to scan for ecological dangers. The presence of conspecifics within proximity distance for social hare was reduced FID due to collective vigilance, while a solitary animal had greater FID, due to less cooperative defense for predator detection. In both seasons, detection and flight initiation distance of the focal hare increased in open habitat due to a higher probability of detection for upcoming danger, while dense cover provided concealment but reduced the probability of detecting an incoming threat, reducing FID. Moreover, proximity to roads and the nearest refuge significantly influenced anti-predator risk by compensation energy to cope with approaching stimuli. In a landscape with heavy human hunting in retaliation to plantations damage has modified the natural behavior of the hare in the Shigar valley. The findings are discussed in the context of hare FID by humans and the suggestions for management and mitigation of human-wildlife conflict are also considered.展开更多
As a research field which is blooming quickly in recent years,movement ecology has been a worldwide concern and interest.However,movement ecology is so comprehensive and complicated that many articles only focus on fe...As a research field which is blooming quickly in recent years,movement ecology has been a worldwide concern and interest.However,movement ecology is so comprehensive and complicated that many articles only focus on few aspects or species.As tracking technologies and methods of movement data analysis develop,the abundance of movement data becomes available for demonstrating more scientific facts about animal movement.This article is aimed to summarize the advances of terrestrial mammal movement ecology in the past years to show its critical and potential research fields,as well as trying to ascertain direction of these advances.展开更多
INTRODUCTION For a given population,only when the individual age is known can we understand the population age structure,evaluate the population stability,speculate on the future development trend of the population,an...INTRODUCTION For a given population,only when the individual age is known can we understand the population age structure,evaluate the population stability,speculate on the future development trend of the population,and formulate reasonable animal management approaches(Coulson et al.2001).The Amur tiger(Panthera tigris altaica)is the largest subspecies of tiger and is mainly distributed in the southeast of Russia at present,while there are also a small number of individuals living in the border region of China,Russia,and North Korea in the northeast of China(Qi et al.2020).Age determination of Amur tigers is required for conservation strategy design,prioritization,and allocation of resources,as well as for evaluating the success of conservation programs.It is very difficult to determine the age of tiger individuals in the wild.展开更多
Appropriate temporal and spatial scales are important prerequisites for obtaining reliable results in studies of wildlife activity patterns and interspecific interactions.The spread of camera-trap technology has incre...Appropriate temporal and spatial scales are important prerequisites for obtaining reliable results in studies of wildlife activity patterns and interspecific interactions.The spread of camera-trap technology has increased interest in and feasibility of studying the activity patterns and interspecific interactions of wildlife.However,such studies are often conducted at arbitrary spatial and temporal scales,and the methods used impose scale on the study rather than determining how activity and species interactions change with spatial scale.In this study,we used a waveletbased approach to determine the temporal and spatial scales for activity patterns and interspecific interactions on Amur leopard and their ungulate prey species that were recorded using camera traps in the main Amur leopard occurrence region in northeast China.Wavelets identified that Amur leopards were more active in spring and fall than summer,and fluctuated with periodicities of 9 and 17 days,respectively.Synchronous relationships between leopards and their prey commonly occurred in spring and fall,with a periodicity of about 20 days,indicating the appropriate seasons and temporal scales for interspecific interaction research.The influence of human activities on the activity patterns of Amur leopard or prey species often occurred over longer time periods(60–64 days).Twodimensional wavelet analyses showed that interactions between leopard and prey were more significant at spatial scales of 1 km2.Overall,our study provides a feasible approach to studying the temporal and spatial scales for wildlife activity patterns and interspecific interaction research using camera trap data.展开更多
Traditionally,wildlife habitat research mainly extracts two-dimensional habitat factors.However,they live in three-dimensional space,and the three-dimensional structure of the forest ecosystem is an important factor a...Traditionally,wildlife habitat research mainly extracts two-dimensional habitat factors.However,they live in three-dimensional space,and the three-dimensional structure of the forest ecosystem is an important factor affecting the composition of the mammal community(Fig.1a,b),and the three-dimensional structure of the forest also determines the behavior pattern of wildlife multidimensional habitat selection or use(Flaspohler et al.2010;Palminteri et al.2012;Müller et al.2014).For instance,forest structure determines the vertical distribution of annual edible shoots,fruits,or seed nuts resources in space,providing additional ecological niches for frugivores,rodents,and other species,and then leading to niche differentiation of wild animals in vertical space utilization,thus increasing species coexistence(e.g.Li et al.2023).展开更多
The automatic individual identification of Amur tigers(Panthera tigris altaica)is important for population monitoring and making effective conservation strategies.Most existing research primarily relies on manual iden...The automatic individual identification of Amur tigers(Panthera tigris altaica)is important for population monitoring and making effective conservation strategies.Most existing research primarily relies on manual identifi-cation,which does not scale well to large datasets.In this paper,the deep convolution neural networks algorithm is constructed to implement the automatic individual identification for large numbers of Amur tiger images.The experimental data were obtained from 40 Amur tigers in Tieling Guaipo Tiger Park,China.The number of images collected from each tiger was approximately 200,and a total of 8277 images were obtained.The experiments were carried out on both the left and right side of body.Our results suggested that the recognition accuracy rate of left and right sides are 90.48%and 93.5%,respectively.The accuracy of our network has achieved the similar level compared to other state of the art networks like LeNet,ResNet34,and ZF_Net.The running time is much shorter than that of other networks.Consequently,this study can provide a new approach on automatic individual identification technology in the case of the Amur tiger.展开更多
A small,isolated Amur tiger population ranges across the southwest Primorskii Krai region in Russia and Hunchun region in China.Many individuals,with“dual nationality,”cross the border frequently.Formulating effecti...A small,isolated Amur tiger population ranges across the southwest Primorskii Krai region in Russia and Hunchun region in China.Many individuals,with“dual nationality,”cross the border frequently.Formulating effective conservation strategies requires a clear understanding of tiger food requirements in both countries.While the diets of tigers ranging in Russia is clearly understood,little is known of the tigers’feeding habits in China..We used scat analysis combined with data on the abundance of 4 prey species to examine Amur tiger diet and prey preferences in Hunchun.We examined 53 tiger scat samples from 2011 to 2016 and found that tigers preyed on 12 species(11 species in winter),4 of which were domestic animals with 33.58%biomass contribution;this was the first record of Amur tigers eating lynx in this area.Tigers showed a strong preference for wild boar(Jacobs index:+0.849),which were also the most frequently consumed prey,and a strong avoidance of roe deer(Jacobs index:–0.693).On the Russian side,domestic animals(just dog)were rarely found in tiger scat,and tigers did not show strong avoidance of roe deer,but of sika deer.We also found red deer footprints during winter surveys and that tigers ate red deer on the Chinese side,while there was no record of red deer feeding on the Russian side.Reducing or eliminating human disturbance,such as grazing,is essential to recovering tiger prey and habitat in this area and the Sino–Russian joint ungulate annual survey is indispensable for prey estimates of this small,isolated Amur tiger population.展开更多
Unmanned aerial vehicle(UAV)technology,artificial intelligence,and the relevant hardware can be used for monitoring wild animals.However,existing methods have several limitations.Therefore,this study explored the monit...Unmanned aerial vehicle(UAV)technology,artificial intelligence,and the relevant hardware can be used for monitoring wild animals.However,existing methods have several limitations.Therefore,this study explored the monitoring and protection of Amur tigers and their main prey species using images from UAVs by optimizing the algorithm models with respect to accuracy,model size,recognition speed,and elimination of environmental inter-ference.Thermal imaging data were collected from 2000 pictures with a thermal imaging lens on a DJI M300RTK UAV at the Hanma National Nature Reserve in the Greater Khingan Mountains in Inner Mongolia,Wangqing National Nature Reserve in Jilin Province,and Siberian Tiger Park in Heilongjiang Province.The YOLO V5s al-gorithm was applied to recognize the animals in the pictures.The accuracy rate was 94.1%,and the size of the model weight(total weight of each model layer trained with the training set)was 14.8 MB.The authors improved the structures and parameters of the YOLO V5s algorithm.As a result,the recognition accuracy rate became 96%,and the model weight was 9.3 MB.The accuracy rate increased by 1.9%,the model weight decreased by 37.2%from 14.8 MB to 9.3 MB,and the recognition time of a single picture was shortened by 34.4%from 0.032 to 0.021 s.This not only increases the recognition accuracy but also effectively lowers the hardware requirements that the algorithm relies on,which provides a lightweight fast recognition method for UAV-based edge computing and online investigation of wild animals.展开更多
The development of facial recognition technology has become an increasingly powerful tool in wild animal indi-vidual recognition.In this paper,we develop an automatic detection and recognition method with the combinat...The development of facial recognition technology has become an increasingly powerful tool in wild animal indi-vidual recognition.In this paper,we develop an automatic detection and recognition method with the combinations of body features of big cats based on the deep convolutional neural network(CNN).We collected dataset including 12244 images from 47 individual Amur tigers(Panthera tigris altaica)at the Siberian Tiger Park by mobile phones and digital camera and 1940 images and videos of 12 individual wild Amur leopard(Panthera pardus orientalis)by infrared cameras.First,the single shot multibox detector algorithm is used to perform the automatic detection process of feature regions in each image.For the different feature regions of the image,like face stripe or spots,CNNs and multi-layer perceptron models were applied to automatically identify tiger and leopard individuals,in-dependently.Our results show that the identification accuracy of Amur tiger can reach up to 93.27%for face front,93.33%for right body stripe,and 93.46%for left body stripe.Furthermore,the combination of right face,left body stripe,and right body stripe achieves the highest accuracy rate,up to 95.55%.Consequently,the combination of different body parts can improve the individual identification accuracy.However,it is not the higher the number of body parts,the higher the accuracy rate.The combination model with 3 body parts has the highest accuracy.The identification accuracy of Amur leopard can reach up to 86.90%for face front,89.13%for left body spots,and 88.33%for right body spots.The accuracy of different body parts combination is lower than the independent part.For wild Amur leopard,the combination of face with body spot part is not helpful for the improvement of identification accuracy.The most effective identification part is still the independent left or right body spot part.It can be applied in long-term monitoring of big cats,including big data analysis for animal behavior,and be helpful for the individual identification of other wildlife species.展开更多
A healthy population of captive Amur tigers might assist recovery of the wild population in Northeast China if individuals were properly prepared and considered suitable for release in the wild.We analyzed the breedin...A healthy population of captive Amur tigers might assist recovery of the wild population in Northeast China if individuals were properly prepared and considered suitable for release in the wild.We analyzed the breeding records of 68 female Amur tigers from 1995 to 2010 in the Hengdaohezi Felid Breeding Center of China and compared the reproductive parameters of this population to wild female Amur tigers.We found that the reproductive parameters of the captive population(the age of first parturition,length of gestation and litter survival rate)were not significantly different from those of wild Amur tigers.Differences in birth date and litter size between wild and captive populations may be caused by management protocols for the captive population or insufficient field data from the wild population.Reproductive parameters of females giving birth after losing a litter were similar to parameters of females that did not lose a litter,except for birth date.These results provide no indication of major problems in using captive females for a breeding program for release of cubs into the wild,but additional information is still needed to assess their suitability.展开更多
So far,there has been no safe and convenient method to weigh the largefierce animals,like Amur tigers.To address this problem,we built models to predict the body weight of Amur tigers based on the fact that body weight...So far,there has been no safe and convenient method to weigh the largefierce animals,like Amur tigers.To address this problem,we built models to predict the body weight of Amur tigers based on the fact that body weight is proportional to body measurements or age.Using the method of body measurements,we extracted the body measurements from 4 different kinds of the lateral body image of tigers,that is,total lateral image,central lateral image,ellipsefitting image,and rectanglefitting image,and then we respectively used artificial neural network(ANN)and power regression model to analyze the predictive relationships between body weight and body measurements.Our results demonstrated that,among all ANN models,the model built with rectanglefitting image had the smallest mean square error.Comparatively,we screened power regression models which had the smallest Akakai information criteria(AIC).In addition,using the method of age,wefitted nonlinear regression models for the relationship between body weight and age and found that,for male tigers,logistic model had the smallest AIC.For female tigers,Gompertz model had the smallest AIC.Consequently,this study could be applied to estimate body weight of captive,or even wild,Amur tigers safely and conveniently,helping to monitor individual health and growth of the Amur tiger populations.展开更多
基金supported by the Fundamental Research Funds for the Central Universities of China(2572022DQ03)National Natural Science Foundation of China(32170517)+1 种基金Guangdong Provincial Key Laboratory of Genome Read and Write(2017B030301011)supported by China National GeneBank(CNGB)。
文摘DEAR EDITOR,Big cats,such as Amur tigers(Panthera tigris altaica)and Amur leopards(P.pardus orientalis),are apex predator and have evolved specialized traits for hunting and carnivory(Moya et al.,2022),thus playing a crucial role in maintaining biodiversity and ecosystem integrity by regulating prey-predator dynamics.However,human-induced pressures,habitat fragmentation,and environmental alterations have restricted these species in small and isolated populations.Currently,all extant big cats are categorized as endangered or threatened according to their conservation status.Amur tigers and Amur leopards share overlapping geographic ranges,habitats,and certain prey species in the forests of Northeast Asia(Jiang et al.,2015).To reduce interspecies conflict,these carnivores exhibit differentiated dietary and temporal niches.Amur tigers predominantly prey on large ungulates,while Amur leopards hunt small to medium-sized animals(Sugimoto et al.,2016).Additionally,they occupy different temporal niches,with tigers being active at night and leopards more active during the day.Despite spatial and temporal niche partitioning,interspecific competition between these two species is inevitable.Tigers,benefiting from their greater size,have a competitive advantage over leopards,which can manifest in occasional leopard predation by tigers and declines in leopard populations with increasing tiger density(Jiang et al.,2015).Tigers also displace leopards from marginal habitats in nature reserves where they coexist.
基金financially supported by Fundamental Research Funds for the Central Universities of China(2572014EA06)National Natural Science Foundation of China(NSFC 31572285)Study on Resource Survey Technology for Tiger and Amur Leopard Population(State Forestry Administration)
文摘In modern wildlife ecological research,feces is the most common non-invasive source of DNA obtained in the field and polymerase chain reaction(PCR) technology based on microsatellite markers is used to mine genetic information contained within.This is especially the case for endangered species.However,there are risks associated with this genotyping method because of the poor quality of fecal DNA.In this study,we assessed genotyping risk across 12 microsatellite loci commonly used in previous tiger studies using blood and fecal DNA from captive Amur tigers(Panthera tigris altaica).To begin,we developed an index termed the accumulated matching rate of genotypes(R)between positive DNA(blood samples) and fecal DNA to explore the correct genotyping probability of a certain microsatellite locus.We found that different microsatelliteloci had different genotyping risks and required different PCR amplification protocols.The genotyping errors we detected altered population genetic parameters and potentially impact subsequent analyses.Based on these findings,we recommend that:(1) four loci(E7,Fca094,Pti007 and Pti010) of 12 loci are not suitable for Amur tiger genetic research because of a low Rand difficulty reaching a stable status;(2) the Rof the 12 microsatellite loci plateaued differently,and considering limited budgets,amplification times of some loci could be increased when using fecal samples; and(3) future genetic analysis of wild Amur tigers should be corrected by genotyping error rates(1-R).
基金This article is supported by Rare and endangered Species Investigation supervision and industry standard project of State Forestry and Grassland Administration(2020070215)This article is supported by Rare and endangered Species Investigation supervision and industry standard project of State Forestry and Grassland Administration(2020070215).
文摘Ecosystem engineers are organisms that alter the distribution of resources in the environment by creating,modifying,maintaining and/or destroying the habitat.They can affect the structure and function of the whole ecosystem furthermore.Burrowing engineers are an important group in ecosystem engineers as they play a critical role in soil translocation and habitat creation in various types of environment.However,few researchers have systematically summarized and analyzed the studies of burrowing engineers.We reviewing the existing ecological studies of burrowing engineer about their interaction with habitat through five directions:(1)soil turnover;(2)changing soil physicochemical properties;(3)changing plant community structure;(4)providing limited resources for commensal animals;and/or(5)affecting animal communities.The Chinese pangolin(Manis pentadactyla)is a typical example of burrowing mammals,in part(5),we focus on the interspecific relationships among burrow commensal species of Chinese pangolin.The engineering effects vary with environmental gradient,literature indicates that burrowing engineer play a stronger role in habitat transformation in the tropical and subtropical areas.The most common experiment method is comparative measurements(include different spatial and temporal scale),manipulative experiment is relatively few.We found that most of the engineering effects had positive feedback to the local ecosystem,increased plant abundance and resilience,increased biodiversity and consequently improved ecosystem functioning.With the global background of dramatic climate change and biodiversity loss in recent decades,we recommend future studies should improving knowledge of long-term engineering effects on population scale and landscape scale,exploring ecological cascades through trophic and engineering pathways,to better understand the attribute of the burrowing behavior of engineers to restore ecosystems and habitat creation.The review is presented as an aid to systematically expound the engineering effect of burrowing animals in the ecosystem,and provided new ideas and advice for planning and implementing conservation management.
文摘Optimal escape theory predicts that animals would balance the costs and benefits of flight. One cost of not fleeing is the ongoing cost of vigilance for upcoming environmental threats. Our results show that FID increases for vigilant hares with predator starting distance, due to the costs acquired by continuing to scan for ecological dangers. The presence of conspecifics within proximity distance for social hare was reduced FID due to collective vigilance, while a solitary animal had greater FID, due to less cooperative defense for predator detection. In both seasons, detection and flight initiation distance of the focal hare increased in open habitat due to a higher probability of detection for upcoming danger, while dense cover provided concealment but reduced the probability of detecting an incoming threat, reducing FID. Moreover, proximity to roads and the nearest refuge significantly influenced anti-predator risk by compensation energy to cope with approaching stimuli. In a landscape with heavy human hunting in retaliation to plantations damage has modified the natural behavior of the hare in the Shigar valley. The findings are discussed in the context of hare FID by humans and the suggestions for management and mitigation of human-wildlife conflict are also considered.
基金This article is funded by National Natural Science Foundation of China(NSFC31872241)Fundamental Research Funds for the Central Universities(2572017PZ14)+2 种基金National Key Programme of Research and Development,Ministry of Science and Technology(2016YFC0503200)Biodiversity Survey,Monitoring and Assessment Project of Ministry of Ecology and Environment,China(2019HB2096001006)Heilongjiang Touyan Innovation Team Program for Forest Ecology and Conservation.The advice and revisions by Professor Guangshun Jiang have guided this article,and I further acknowledge the help of colleague Nathan J.Roberts for English editing,assistance and advice.
文摘As a research field which is blooming quickly in recent years,movement ecology has been a worldwide concern and interest.However,movement ecology is so comprehensive and complicated that many articles only focus on few aspects or species.As tracking technologies and methods of movement data analysis develop,the abundance of movement data becomes available for demonstrating more scientific facts about animal movement.This article is aimed to summarize the advances of terrestrial mammal movement ecology in the past years to show its critical and potential research fields,as well as trying to ascertain direction of these advances.
文摘INTRODUCTION For a given population,only when the individual age is known can we understand the population age structure,evaluate the population stability,speculate on the future development trend of the population,and formulate reasonable animal management approaches(Coulson et al.2001).The Amur tiger(Panthera tigris altaica)is the largest subspecies of tiger and is mainly distributed in the southeast of Russia at present,while there are also a small number of individuals living in the border region of China,Russia,and North Korea in the northeast of China(Qi et al.2020).Age determination of Amur tigers is required for conservation strategy design,prioritization,and allocation of resources,as well as for evaluating the success of conservation programs.It is very difficult to determine the age of tiger individuals in the wild.
基金funded by the Fundamental Research Funds for the Central Universities(2572017PZ14)the National Key Programme of Research and Development,Ministry of Science and Technology(2016YFC0503200)+1 种基金NSFC(31872241,31572285)to G.J.full-time postdoctoral support program of Northeast Forestry University(60201103)to J.Q.
文摘Appropriate temporal and spatial scales are important prerequisites for obtaining reliable results in studies of wildlife activity patterns and interspecific interactions.The spread of camera-trap technology has increased interest in and feasibility of studying the activity patterns and interspecific interactions of wildlife.However,such studies are often conducted at arbitrary spatial and temporal scales,and the methods used impose scale on the study rather than determining how activity and species interactions change with spatial scale.In this study,we used a waveletbased approach to determine the temporal and spatial scales for activity patterns and interspecific interactions on Amur leopard and their ungulate prey species that were recorded using camera traps in the main Amur leopard occurrence region in northeast China.Wavelets identified that Amur leopards were more active in spring and fall than summer,and fluctuated with periodicities of 9 and 17 days,respectively.Synchronous relationships between leopards and their prey commonly occurred in spring and fall,with a periodicity of about 20 days,indicating the appropriate seasons and temporal scales for interspecific interaction research.The influence of human activities on the activity patterns of Amur leopard or prey species often occurred over longer time periods(60–64 days).Twodimensional wavelet analyses showed that interactions between leopard and prey were more significant at spatial scales of 1 km2.Overall,our study provides a feasible approach to studying the temporal and spatial scales for wildlife activity patterns and interspecific interaction research using camera trap data.
文摘Traditionally,wildlife habitat research mainly extracts two-dimensional habitat factors.However,they live in three-dimensional space,and the three-dimensional structure of the forest ecosystem is an important factor affecting the composition of the mammal community(Fig.1a,b),and the three-dimensional structure of the forest also determines the behavior pattern of wildlife multidimensional habitat selection or use(Flaspohler et al.2010;Palminteri et al.2012;Müller et al.2014).For instance,forest structure determines the vertical distribution of annual edible shoots,fruits,or seed nuts resources in space,providing additional ecological niches for frugivores,rodents,and other species,and then leading to niche differentiation of wild animals in vertical space utilization,thus increasing species coexistence(e.g.Li et al.2023).
基金the Fundamental Research Funds for the Central Universities(2572018BC07,2572017PZ14)the Heilongjiang postdoctoral project fund project(LBH-Z18003)+2 种基金Biodiversity Survey,Monitoring and Assessment Project of Ministry of Ecology and Environment,China(2019HB2096001006)the National Natural Science Foundation of China(NSFC 31872241,31572285)the Individual Identification Technological Research on Camera-trapping images of Amur tigers(NFGA 2017).
文摘The automatic individual identification of Amur tigers(Panthera tigris altaica)is important for population monitoring and making effective conservation strategies.Most existing research primarily relies on manual identifi-cation,which does not scale well to large datasets.In this paper,the deep convolution neural networks algorithm is constructed to implement the automatic individual identification for large numbers of Amur tiger images.The experimental data were obtained from 40 Amur tigers in Tieling Guaipo Tiger Park,China.The number of images collected from each tiger was approximately 200,and a total of 8277 images were obtained.The experiments were carried out on both the left and right side of body.Our results suggested that the recognition accuracy rate of left and right sides are 90.48%and 93.5%,respectively.The accuracy of our network has achieved the similar level compared to other state of the art networks like LeNet,ResNet34,and ZF_Net.The running time is much shorter than that of other networks.Consequently,this study can provide a new approach on automatic individual identification technology in the case of the Amur tiger.
基金This study was funded by the National Key Programme of Research and Development,Ministry of Science and Technology(2016YFC0503200)the Fundamental Research Funds for the Central Universities(2572014EA06,2572016AA10)+2 种基金the National Natural Science Foundation of China(Grant ID 31272336,31572285)China Postdoctoral Science Foundation funded project(2015M581416,LBH-Z14017)2 projects of the State Forestry Administration,entitled“Study on Tiger and Amur Leopard Population Resources Monitoring Technology”and“Survey Standard Compiling and Information Summary of Amur Leopard and Tiger Population and Habitat.”。
文摘A small,isolated Amur tiger population ranges across the southwest Primorskii Krai region in Russia and Hunchun region in China.Many individuals,with“dual nationality,”cross the border frequently.Formulating effective conservation strategies requires a clear understanding of tiger food requirements in both countries.While the diets of tigers ranging in Russia is clearly understood,little is known of the tigers’feeding habits in China..We used scat analysis combined with data on the abundance of 4 prey species to examine Amur tiger diet and prey preferences in Hunchun.We examined 53 tiger scat samples from 2011 to 2016 and found that tigers preyed on 12 species(11 species in winter),4 of which were domestic animals with 33.58%biomass contribution;this was the first record of Amur tigers eating lynx in this area.Tigers showed a strong preference for wild boar(Jacobs index:+0.849),which were also the most frequently consumed prey,and a strong avoidance of roe deer(Jacobs index:–0.693).On the Russian side,domestic animals(just dog)were rarely found in tiger scat,and tigers did not show strong avoidance of roe deer,but of sika deer.We also found red deer footprints during winter surveys and that tigers ate red deer on the Chinese side,while there was no record of red deer feeding on the Russian side.Reducing or eliminating human disturbance,such as grazing,is essential to recovering tiger prey and habitat in this area and the Sino–Russian joint ungulate annual survey is indispensable for prey estimates of this small,isolated Amur tiger population.
基金funded by a program of the Natural Science Foundation of Heilongjiang Province,Research on Key Technologies of Wildlife Intelligent Monitoring(LH2020C034)the National Natural Science Foundation of China(NSFC31872241,32100392)the Fundamental Research Funds for the Central Universities(2572022DS04).
文摘Unmanned aerial vehicle(UAV)technology,artificial intelligence,and the relevant hardware can be used for monitoring wild animals.However,existing methods have several limitations.Therefore,this study explored the monitoring and protection of Amur tigers and their main prey species using images from UAVs by optimizing the algorithm models with respect to accuracy,model size,recognition speed,and elimination of environmental inter-ference.Thermal imaging data were collected from 2000 pictures with a thermal imaging lens on a DJI M300RTK UAV at the Hanma National Nature Reserve in the Greater Khingan Mountains in Inner Mongolia,Wangqing National Nature Reserve in Jilin Province,and Siberian Tiger Park in Heilongjiang Province.The YOLO V5s al-gorithm was applied to recognize the animals in the pictures.The accuracy rate was 94.1%,and the size of the model weight(total weight of each model layer trained with the training set)was 14.8 MB.The authors improved the structures and parameters of the YOLO V5s algorithm.As a result,the recognition accuracy rate became 96%,and the model weight was 9.3 MB.The accuracy rate increased by 1.9%,the model weight decreased by 37.2%from 14.8 MB to 9.3 MB,and the recognition time of a single picture was shortened by 34.4%from 0.032 to 0.021 s.This not only increases the recognition accuracy but also effectively lowers the hardware requirements that the algorithm relies on,which provides a lightweight fast recognition method for UAV-based edge computing and online investigation of wild animals.
基金funded by the Fundamental Research Funds for the Central Universities(2572020BC05)the Heilongjiang postdoctoral fund project(LBH-Z18003)+3 种基金the Biodiversity Survey,Monitoring and Assessment Project of Ministry of Ecology and Environment,China(2019HB2096001006)the National Natural Science Foundation of China(NSFC 31872241)the Individual Identification Technological Research on Cameratrapping images of Amur tigers(NFGA 2017)National Innovation and Entrepreneurship Training Program for College Student(S202010225022).
文摘The development of facial recognition technology has become an increasingly powerful tool in wild animal indi-vidual recognition.In this paper,we develop an automatic detection and recognition method with the combinations of body features of big cats based on the deep convolutional neural network(CNN).We collected dataset including 12244 images from 47 individual Amur tigers(Panthera tigris altaica)at the Siberian Tiger Park by mobile phones and digital camera and 1940 images and videos of 12 individual wild Amur leopard(Panthera pardus orientalis)by infrared cameras.First,the single shot multibox detector algorithm is used to perform the automatic detection process of feature regions in each image.For the different feature regions of the image,like face stripe or spots,CNNs and multi-layer perceptron models were applied to automatically identify tiger and leopard individuals,in-dependently.Our results show that the identification accuracy of Amur tiger can reach up to 93.27%for face front,93.33%for right body stripe,and 93.46%for left body stripe.Furthermore,the combination of right face,left body stripe,and right body stripe achieves the highest accuracy rate,up to 95.55%.Consequently,the combination of different body parts can improve the individual identification accuracy.However,it is not the higher the number of body parts,the higher the accuracy rate.The combination model with 3 body parts has the highest accuracy.The identification accuracy of Amur leopard can reach up to 86.90%for face front,89.13%for left body spots,and 88.33%for right body spots.The accuracy of different body parts combination is lower than the independent part.For wild Amur leopard,the combination of face with body spot part is not helpful for the improvement of identification accuracy.The most effective identification part is still the independent left or right body spot part.It can be applied in long-term monitoring of big cats,including big data analysis for animal behavior,and be helpful for the individual identification of other wildlife species.
基金We are grateful for support provided through the Fundamental Research Funds for the Central Universities of China(2572014EA06 and 2572014AA14),the National Natural Science Foundation of China(NSFC31272336,31572285)and the"Study on Resource Survey Technology for Tiger and Amur Leopard Population"and"Standard of Tiger and Amur Leopard Population and Habitat Survey and Data Summarization"(State Forestry Administration).
文摘A healthy population of captive Amur tigers might assist recovery of the wild population in Northeast China if individuals were properly prepared and considered suitable for release in the wild.We analyzed the breeding records of 68 female Amur tigers from 1995 to 2010 in the Hengdaohezi Felid Breeding Center of China and compared the reproductive parameters of this population to wild female Amur tigers.We found that the reproductive parameters of the captive population(the age of first parturition,length of gestation and litter survival rate)were not significantly different from those of wild Amur tigers.Differences in birth date and litter size between wild and captive populations may be caused by management protocols for the captive population or insufficient field data from the wild population.Reproductive parameters of females giving birth after losing a litter were similar to parameters of females that did not lose a litter,except for birth date.These results provide no indication of major problems in using captive females for a breeding program for release of cubs into the wild,but additional information is still needed to assess their suitability.
基金funded by the National Natural Science Foundation of China(NSFC31872241 and 31702031)the National Key Programme of Research and Development,the Ministry of Science and Technology(2016YFC0503200)+2 种基金the Fundamental Research Funds for the Central Universities(2572017PZ14 and 2572020BC05)the Biodiversity Survey,Monitoring and Assessment Project of Ministry of Ecology and EnvironEnvironment,China(2019HB2096001006)the Heilongjiang postdoctoral project fund(LBH-Z18003).
文摘So far,there has been no safe and convenient method to weigh the largefierce animals,like Amur tigers.To address this problem,we built models to predict the body weight of Amur tigers based on the fact that body weight is proportional to body measurements or age.Using the method of body measurements,we extracted the body measurements from 4 different kinds of the lateral body image of tigers,that is,total lateral image,central lateral image,ellipsefitting image,and rectanglefitting image,and then we respectively used artificial neural network(ANN)and power regression model to analyze the predictive relationships between body weight and body measurements.Our results demonstrated that,among all ANN models,the model built with rectanglefitting image had the smallest mean square error.Comparatively,we screened power regression models which had the smallest Akakai information criteria(AIC).In addition,using the method of age,wefitted nonlinear regression models for the relationship between body weight and age and found that,for male tigers,logistic model had the smallest AIC.For female tigers,Gompertz model had the smallest AIC.Consequently,this study could be applied to estimate body weight of captive,or even wild,Amur tigers safely and conveniently,helping to monitor individual health and growth of the Amur tiger populations.
