Camera traps are an effective tool for monitoring insect-plant interactions.
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ABSTRACT:
SUBMITTER: Naqvi Q
PROVIDER: S-EPMC9163375 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Camera traps have become a ubiquitous tool in ecology and conservation. They are routinely deployed in wildlife survey and monitoring work, and are being advocated as a tool for planetary-scale biodiversity monitoring. The camera trap's widespread adoption is predicated on the assumption of its effectiveness, but the evidence base for this is lacking. Using 104 past studies, we recorded the qualitative overall recommendations made by study authors (for or against camera traps, or ambiguous), together with quantitative data on the effectiveness of camera traps (e.g. number of species detected or detection probabilities) relative to 22 other methods. Most studies recommended the use of camera traps overall and they were 39% more effective based on the quantitative data. They were significantly more effective compared with live traps (88%) and were otherwise comparable in effectiveness to other methods. Camera traps were significantly more effective than other methods at detecting a large number of species (31% more) and for generating detections of species (91% more). This makes camera traps particularly suitable for broad-spectrum biodiversity surveys. Film camera traps were found to be far less effective than digital models, which has led to an increase in camera trap effectiveness over time. There was also evidence from the authors that the use of attractants with camera traps reduced their effectiveness (counter to their intended effect), while the quantitative data indicated that camera traps were more effective in closed than open habitats. Camera traps are a highly effective wildlife survey tool and their performance will only improve with future technological advances. The images they produce also have a range of other benefits, for example as digital voucher specimens and as visual aids for outreach. The evidence-base supports the increasing use of camera traps and underlines their suitability for meeting the challenges of global-scale biodiversity monitoring.
| S-EPMC6458413 | biostudies-literature
Project description:Practical techniques are required to monitor invasive animals, which are often cryptic and occur at low density. Camera traps have potential for this purpose, but may have problems detecting and identifying small species. A further challenge is how to standardise the size of each camera's field of view so capture rates are comparable between different places and times. We investigated the optimal specifications for a low-cost camera trap for small mammals. The factors tested were 1) trigger speed, 2) passive infrared vs. microwave sensor, 3) white vs. infrared flash, and 4) still photographs vs. video. We also tested a new approach to standardise each camera's field of view. We compared the success rates of four camera trap designs in detecting and taking recognisable photographs of captive stoats (Mustelaerminea), feral cats (Felis catus) and hedgehogs (Erinaceuseuropaeus). Trigger speeds of 0.2-2.1 s captured photographs of all three target species unless the animal was running at high speed. The camera with a microwave sensor was prone to false triggers, and often failed to trigger when an animal moved in front of it. A white flash produced photographs that were more readily identified to species than those obtained under infrared light. However, a white flash may be more likely to frighten target animals, potentially affecting detection probabilities. Video footage achieved similar success rates to still cameras but required more processing time and computer memory. Placing two camera traps side by side achieved a higher success rate than using a single camera. Camera traps show considerable promise for monitoring invasive mammal control operations. Further research should address how best to standardise the size of each camera's field of view, maximise the probability that an animal encountering a camera trap will be detected, and eliminate visible or audible cues emitted by camera traps.
| S-EPMC3695914 | biostudies-literature
Project description:Insect monitoring is essential to design effective conservation strategies, which are indispensable to mitigate worldwide declines and biodiversity loss. For this purpose, traditional monitoring methods are widely established and can provide data with a high taxonomic resolution. However, processing of captured insect samples is often time-consuming and expensive, which limits the number of potential replicates. Automated monitoring methods can facilitate data collection at a higher spatiotemporal resolution with a comparatively lower effort and cost. Here, we present the Insect Detect DIY (do-it-yourself) camera trap for non-invasive automated monitoring of flower-visiting insects, which is based on low-cost off-the-shelf hardware components combined with open-source software. Custom trained deep learning models detect and track insects landing on an artificial flower platform in real time on-device and subsequently classify the cropped detections on a local computer. Field deployment of the solar-powered camera trap confirmed its resistance to high temperatures and humidity, which enables autonomous deployment during a whole season. On-device detection and tracking can estimate insect activity/abundance after metadata post-processing. Our insect classification model achieved a high top-1 accuracy on the test dataset and generalized well on a real-world dataset with captured insect images. The camera trap design and open-source software are highly customizable and can be adapted to different use cases. With custom trained detection and classification models, as well as accessible software programming, many possible applications surpassing our proposed deployment method can be realized.
| S-EPMC10990185 | biostudies-literature
Project description:The occurrence and distribution of insects and their possible associations with plant species are largely unknown in Germany and baseline data to monitor future trends are urgently needed. Using newly-designed automated Malaise trap multi-samplers, the occurrence of insect species and their potential associations with plants was monitored synchronously at two contrasting field sites in Germany: an urban botanical garden and a forest research station. Taxa were identified by metabarcoding of the insects and the plant traces present in the preservative ethanol of the Malaise trap samples. For comparison, a botanical survey was conducted in the vicinity of the traps. Across both sites, we identified a total of 1290 exact sequence variants (ESVs) assigned to Insecta, of which 205 are known to be pollinators. In the botanical garden, we detected the occurrence of 128 plant taxa, of which 41 also had one of their known insect pollinator species detected. Insect species richness was highest in May, mainly attributed to an increase in Diptera. These results present a case study of the applicability of automated sampling and DNA-based methods to monitor the timings of flowering and corresponding activity of plant-visiting insects.
| S-EPMC11303846 | biostudies-literature
Project description:The aim of this study is to identify Arabidopsis genes whose expression is altered by aphid feeding. An understanding of the plant aphid interaction at the level of the plant transcriptome will 1) consolidate current areas of investigation focused on the phloem composition (the aphid diet), 2) open up areas of plant aphid interactions for ourselves and other workers, 3) Contribute to understanding the use of new molecular technologies in an environmental context and 4) contribute to existing and development of novel control strategies.Our Arabidopsis/Myzus persicae system provides a valuable model for the study because of: a) the advantages of using Arabidopsis, b) The ability to use clonal insects, c) phloem feeding aphids facilitate focus on a specific cell type, d) aphid stylectomy allows collection of pure phloem sap to monitor phloem phenotype of the plant and the insect diet, e) we have techniques to monitor the reproductive performance and feeding behaviour aphids.Our strategy has been to test the function of selected genes, particularly those regulating phloem composition (the feeding site of the aphid) based on current phloem models of phloem function. Gene choice is limited the simplicity of current models of phloem aphid interaction.We propose a simple two treatment (aphid infested vs control plants) experiment that will identify novel target genes for future analysis. Arabidopsis plants (variety Columbia) will be grown in 16/8 light/dark in temperature controlled growth rooms. At growth stage 3.90, when rosette growth is complete, 10 clonal adult Myzus persicae will be caged in clip cages on the two largest leaves on each plant. Control plants will be treated identically except that the cages will be empty. Leaves will be harvested 8 h after infestation. This time point is selected as we know that 90% of aphids are plugged into the sieve element within 2h and that a 6h lag phase has period has previously been used when examining gene expression affected by wounding. In subsequent experiments we will examine time courses of expression of relevant genes using other approaches. Pooling two leaves from each of ten plants will generate the RNA sample, ensuring that expression signals are representative of the population of plants. Experimenter name: Jeremy Pritchard Experimenter phone: 0121 414 5570 Experimenter fax: 0121 414 5925 Experimenter institute: University of Birmingham Experimenter address: School of Biosciences Experimenter address: University of Birmingham, Edgbaston, Birmingham, West Midlands Experimenter zip/postal_code: B30 2EN Experimenter country: UK Keywords: pathogenicity_design
2007-01-22 | GSE6823 | GEO
Project description:The aim of this study is to identify Arabidopsis genes whose expression is altered by aphid feeding. An understanding of the plant aphid interaction at the level of the plant transcriptome will 1) consolidate current areas of investigation focused on the phloem composition (the aphid diet), 2) open up areas of plant aphid interactions for ourselves and other workers, 3) Contribute to understanding the use of new molecular technologies in an environmental context and 4) contribute to existing and development of novel control strategies.Our Arabidopsis/Myzus persicae system provides a valuable model for the study because of: a) the advantages of using Arabidopsis, b) The ability to use clonal insects, c) phloem feeding aphids facilitate focus on a specific cell type, d) aphid stylectomy allows collection of pure phloem sap to monitor ‘phloem phenotype’ of the plant and the insect diet, e) we have techniques to monitor the reproductive performance and feeding behaviour aphids.Our strategy has been to test the function of selected genes, particularly those regulating phloem composition (the feeding site of the aphid) based on current phloem models of phloem function. Gene choice is limited the simplicity of current models of phloem aphid interaction.We propose a simple two treatment (aphid infested vs control plants) experiment that will identify novel target genes for future analysis. Arabidopsis plants (variety Columbia) will be grown in 16/8 light/dark in temperature controlled growth rooms. At growth stage 3.90, when rosette growth is complete, 10 clonal adult Myzus persicae will be caged in clip cages on the two largest leaves on each plant. Control plants will be treated identically except that the cages will be empty. Leaves will be harvested 8 h after infestation. This time point is selected as we know that 90% of aphids are plugged into the sieve element within 2h and that a 6h lag phase has period has previously been used when examining gene expression affected by wounding. In subsequent experiments we will examine time courses of expression of relevant genes using other approaches. Pooling two leaves from each of ten plants will generate the RNA sample, ensuring that expression signals are representative of the population of plants. Keywords: pathogenicity_design
2007-01-22 | GSE6172 | GEO
Project description:Predator-prey dynamics are a fundamental part of ecology, but directly studying interactions has proven difficult. The proliferation of camera trapping has enabled the collection of large datasets on wildlife, but researchers face hurdles inferring interactions from observational data. Recent advances in hierarchical co-abundance models infer species interactions while accounting for two species' detection probabilities, shared responses to environmental covariates, and propagate uncertainty throughout the entire modeling process. However, current approaches remain unsuitable for interacting species whose natural densities differ by an order of magnitude and have contrasting detection probabilities, such as predator-prey interactions, which introduce zero inflation and overdispersion in count histories. Here, we developed a Bayesian hierarchical N-mixture co-abundance model that is suitable for inferring predator-prey interactions. We accounted for excessive zeros in count histories using an informed zero-inflated Poisson distribution in the abundance formula and accounted for overdispersion in count histories by including a random effect per sampling unit and sampling occasion in the detection probability formula. We demonstrate that models with these modifications outperform alternative approaches, improve model goodness-of-fit, and overcome parameter convergence failures. We highlight its utility using 20 camera trapping datasets from 10 tropical forest landscapes in Southeast Asia and estimate four predator-prey relationships between tigers, clouded leopards, and muntjac and sambar deer. Tigers had a negative effect on muntjac abundance, providing support for top-down regulation, while clouded leopards had a positive effect on muntjac and sambar deer, likely driven by shared responses to unmodelled covariates like hunting. This Bayesian co-abundance modeling approach to quantify predator-prey relationships is widely applicable across species, ecosystems, and sampling approaches and may be useful in forecasting cascading impacts following widespread predator declines. Taken together, this approach facilitates a nuanced and mechanistic understanding of food-web ecology.
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Project description:The conservation of gray wolf (Canis lupus) and its coexistence with humans presents a challenge and requires continuous monitoring and management efforts. One of the non-invasive methods that produces high-quality wolf monitoring datasets is camera trapping. We present a novel monitoring approach where camera traps are positioned on wildlife crossing structures that channel the animals, thereby increasing trapping success and increasing the cost-efficiency of the method. In this way we have followed abundance trends of five wolf packs whose home ranges are intersected by a motorway which spans throughout the wolf distribution range in Croatia. During the five-year monitoring of six green bridges we have recorded 28 250 camera-events, 132 with wolves. Four viaducts were monitored for two years, recording 4914 camera-events, 185 with wolves. We have detected a negative abundance trend of the monitored Croatian wolf packs since 2011, especially severe in the northern part of the study area. Further, we have pinpointed the legal cull as probable major negative influence on the wolf pack abundance trends (linear regression, r2 > 0.75, P < 0.05). Using the same approach we did not find evidence for a negative impact of wolves on the prey populations, both wild ungulates and livestock. We encourage strict protection of wolf in Croatia until there is more data proving population stability. In conclusion, quantitative methods, such as the one presented here, should be used as much as possible when assessing wolf abundance trends.
| S-EPMC4915698 | biostudies-literature
Project description:In plant-insect interactions, calcium (Ca2+) variations are among the earliest events associated with the plant perception of biotic stress. Upon herbivory, Ca2+ waves travel long distances to transmit and convert the local signal to a systemic defense program. Reactive oxygen species (ROS), Ca2+ and electrical signaling are interlinked to form a network supporting rapid signal transmission, whereas the Ca2+ message is decoded and relayed by Ca2+-binding proteins (including calmodulin, Ca2+-dependent protein kinases, annexins and calcineurin B-like proteins). Monitoring the generation of Ca2+ signals at the whole plant or cell level and their long-distance propagation during biotic interactions requires innovative imaging techniques based on sensitive sensors and using genetically encoded indicators. This review summarizes the recent advances in Ca2+ signaling upon herbivory and reviews the most recent Ca2+ imaging techniques and methods.
| S-EPMC9609891 | biostudies-literature
Project description:Invasive alien plant species (IAPS) pose a threat to biodiversity as they propagate and outcompete natural vegetation. In this study, a system for monitoring IAPS on the roadside is presented. The system consists of a camera that acquires images at high speed mounted on a vehicle that follows the traffic. Images of seven IAPS (Cytisus scoparius, Heracleum, Lupinus polyphyllus, Pastinaca sativa, Reynoutria, Rosa rugosa, and Solidago) were collected on Danish motorways. Three deep convolutional neural networks for classification (ResNet50V2 and MobileNetV2) and object detection (YOLOv3) were trained and evaluated at different image sizes. The results showed that the performance of the networks varied with the input image size and also the size of the IAPS in the images. Binary classification of IAPS vs. non-IAPS showed an increased performance, compared to the classification of individual IAPS. This study shows that automatic detection and mapping of invasive plants along the roadside is possible at high speeds.
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