Development of time-lapse photography for the population monitoring of a colonial seabird.

2020 ◽  
Author(s):  
◽  
Alice Edney
Keyword(s):  
Citizen Science ◽  
Large Scale ◽  
Time Lapse ◽  
Daily Maximum ◽  
Population Declines ◽  
Chick Survival ◽  
Monitoring Methods ◽  
Weather Extremes ◽  
Egg Survival ◽  
Expert Analysis

Seabirds are one of the most threatened groups of birds and large-scale monitoring is needed to link changing population trends to causative factors, in order to address population declines. Rapid advances in technology are offering new and exciting possibilities to expand monitoring over larger spatial and temporal scales, however, they also raise new challenges, such as dealing with increased amounts of data and ensuring the data obtained are comparable to that from ‘traditional’ monitoring methods. Specifically, this research focused on the use of time-lapse cameras to monitor the Black-legged Kittiwake Rissa tridactyla, a species listed as Vulnerable on the International Union for Conservation of Nature (IUCN) Red List. Chapters one and two used a case study on Skomer Island, Wales, to compare measurements of productivity and phenology obtained from fieldwork with expert analysis of time-lapse images. Chapter two then went on to explore the effects of weather on Kittiwake nest survival on Skomer. Chapter three used data from across a much wider area, to compare expert analysis of time-lapse images with citizen science analysis. This study showed that both field and image-derived data have inherent biases, but together can inform meaningful investigation into the factors contributing to Kittiwake decline. I found that strong westerly winds may be reducing egg and chick survival at the Wick colony, Skomer, and high daily maximum temperatures could also be lowering egg survival. If these results represent a longer-term pattern, then it could have important implications for Kittiwake population dynamics with climate change, which is predicted to increase the frequency and intensity of weather extremes. Expanding the scale of monitoring via the citizen science project, Seabird Watch, was found to have promising potential; although further work is needed to ensure volunteer data are as good as expert classification. Many factors affected the accuracy of citizen science results and these must be carefully considered before using the data to answer bigger scientific questions. Overall, this study has shown the potential of using time-lapse imagery to monitor a cliff-nesting seabird and will likely become an increasingly cost-effective monitoring solution in the coming years.

scholarly journals Time-lapse imagery is cheap and timely in the fight against colonial species' decline

2021 ◽  
Author(s):  
Tom Hart ◽  
Fiona Jones ◽  
Caitlin Black ◽  
Chris Lintott ◽  
Casey Youngflesh ◽  
...  
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Parameter Estimation ◽  
Citizen Science ◽  
Large Scale ◽  
Individual Recognition ◽  
Spatial Scales ◽  
Time Lapse ◽  
Machine Learning Algorithms ◽  
Series Data

Many of the species in decline around the world are subject to different environmental stressors across their range, so replicated large-scale monitoring programmes, are necessary to disentangle the relative impacts of these threats. At the same time as funding for long-term monitoring is being cut, studies are increasingly being criticised for lacking statistical power. For those taxa or environments where a single vantage point can observe individuals or ecological processes, time-lapse cameras can provide a cost-effective way of collecting time series data replicated at large spatial scales that would otherwise be impossible. However, networks of time-lapse cameras needed to cover the range of species or processes create a problem in that the scale of data collection easily exceeds our ability to process the raw imagery manually. Citizen science and machine learning provide solutions to scaling up data extraction (such as locating all animals in an image). Crucially, citizen science, machine learning-derived classifiers, and the intersection between them, are key to understanding how to establish monitoring systems that are sensitive to – and sufficiently powerful to detect –changes in the study system. Citizen science works relatively ‘out of the box’, and we regard it as a first step for many systems until machine learning algorithms are sufficiently trained to automate the process. Using Penguin Watch (www.penguinwatch.org) data as a case study, we discuss a complete workflow from images to parameter estimation and interpretation: the use of citizen science and computer vision for image processing, and parameter estimation and individual recognition for investigating biological questions. We discuss which techniques are easily generalizable to a range of questions, and where more work is needed to supplement ‘out of the box’ tools. We conclude with a horizon scan of the advances in camera technology, such as on-board computer vision and decision making.

scholarly journals Preparing for translocations of a Critically Endangered petrel through targeted monitoring of nest survival and breeding biology

Oryx ◽  
2021 ◽  
pp. 1-9
Author(s):  
Johannes H. Fischer ◽  
Heiko U. Wittmer ◽  
Graeme A. Taylor ◽  
Igor Debski ◽  
Doug P. Armstrong
Keyword(s):  
Southern Oscillation ◽  
Nest Survival ◽  
Growth Curves ◽  
Breeding Biology ◽  
Source Population ◽  
Breeding Phenology ◽  
Chick Survival ◽  
Egg Survival ◽  
Dune System ◽  
Burrow Density

Abstract The population of the recently-described Whenua Hou diving petrel Pelecanoides whenuahouensis comprises c. 200 adults that all breed in a single 0.018 km2 colony in a dune system vulnerable to erosion. The species would therefore benefit from the establishment of a second breeding population through a translocation. However, given the small size of the source population, it is essential that translocations are informed by carefully targeted monitoring data. We therefore modelled nest survival at the remaining population in relation to potential drivers (distance to sea and burrow density of conspecifics and a competitor) across three breeding seasons with varying climatic conditions as a result of the southern oscillation cycle. We also documented breeding phenology and burrow attendance, and measured chicks, to generate growth curves. We estimated egg survival at 0.686, chick survival at 0.890, overall nest survival at 0.612, and found no indication that nest survival was affected by distance to sea or burrow density. Whenua Hou diving petrels laid eggs in mid October, eggs hatched in late November, and chicks fledged in mid January at c. 86% of adult weight. Burrow attendance (i.e. feeds) decreased from 0.94 to 0.65 visits per night as chicks approached fledging. Nest survival and breeding biology were largely consistent among years despite variation in climate. Nest survival estimates will facilitate predictions about future population trends and suitability of prospective translocation sites. Knowledge of breeding phenology will inform the timing of collection of live chicks for translocation, and patterns of burrow attendance combined with growth curves will structure hand-rearing protocols. A tuhinga whakarāpopoto (te reo Māori abstract) can be found in the Supplementary material.

scholarly journals A Citizen Science Unmanned Aerial System Data Acquisition Protocol and Deep Learning Techniques for the Automatic Detection and Mapping of Marine Litter Concentrations in the Coastal Zone

Drones ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 6
Author(s):  
Apostolos Papakonstantinou ◽  
Marios Batsaris ◽  
Spyros Spondylidis ◽  
Konstantinos Topouzelis
Keyword(s):  
Deep Learning ◽  
Data Acquisition ◽  
Citizen Science ◽  
Coastal Zone ◽  
Automatic Detection ◽  
Monitoring Methods ◽  
Monitoring Method ◽  
Marine Litter ◽  
Density Maps ◽  
Learning Techniques

Marine litter (ML) accumulation in the coastal zone has been recognized as a major problem in our time, as it can dramatically affect the environment, marine ecosystems, and coastal communities. Existing monitoring methods fail to respond to the spatiotemporal changes and dynamics of ML concentrations. Recent works showed that unmanned aerial systems (UAS), along with computer vision methods, provide a feasible alternative for ML monitoring. In this context, we proposed a citizen science UAS data acquisition and annotation protocol combined with deep learning techniques for the automatic detection and mapping of ML concentrations in the coastal zone. Five convolutional neural networks (CNNs) were trained to classify UAS image tiles into two classes: (a) litter and (b) no litter. Testing the CCNs’ generalization ability to an unseen dataset, we found that the VVG19 CNN returned an overall accuracy of 77.6% and an f-score of 77.42%. ML density maps were created using the automated classification results. They were compared with those produced by a manual screening classification proving our approach’s geographical transferability to new and unknown beaches. Although ML recognition is still a challenging task, this study provides evidence about the feasibility of using a citizen science UAS-based monitoring method in combination with deep learning techniques for the quantification of the ML load in the coastal zone using density maps.

scholarly journals Analyzing indoor mycobiomes through a large‐scale citizen science study in Norway

2021 ◽  
Author(s):  
Pedro M. Martin‐Sanchez ◽  
Eva‐Lena F. Estensmo ◽  
Luis N. Morgado ◽  
Sundy Maurice ◽  
Ingeborg B. Engh ◽  
...  
Keyword(s):  
Citizen Science ◽  
Large Scale ◽  
Science Study

scholarly journals The epistemic culture in an online citizen science project: Programs, antiprograms and epistemic subjects

2018 ◽  
Vol 48 (4) ◽  
pp. 564-588 ◽  
Author(s):  
Dick Kasperowski ◽  
Thomas Hillman
Keyword(s):  
Citizen Science ◽  
Distributed Cognition ◽  
Large Scale ◽  
Science Project ◽  
Large Sets ◽  
The Galaxy ◽  
Epistemic Culture ◽  
Classification Of Images ◽  
Citizen Science Project

In the past decade, some areas of science have begun turning to masses of online volunteers through open calls for generating and classifying very large sets of data. The purpose of this study is to investigate the epistemic culture of a large-scale online citizen science project, the Galaxy Zoo, that turns to volunteers for the classification of images of galaxies. For this task, we chose to apply the concepts of programs and antiprograms to examine the ‘essential tensions’ that arise in relation to the mobilizing values of a citizen science project and the epistemic subjects and cultures that are enacted by its volunteers. Our premise is that these tensions reveal central features of the epistemic subjects and distributed cognition of epistemic cultures in these large-scale citizen science projects.

scholarly journals Form and function in hillslope hydrology: characterization of subsurface flow based on response observations

2017 ◽  
Vol 21 (7) ◽  
pp. 3727-3748 ◽  
Author(s):  
Lisa Angermann ◽  
Conrad Jackisch ◽  
Niklas Allroggen ◽  
Matthias Sprenger ◽  
Erwin Zehe ◽  
...  
Keyword(s):  
Preferential Flow ◽  
Explanatory Power ◽  
Subsurface Flow ◽  
Time Lapse ◽  
Storm Event ◽  
Monitoring Methods ◽  
Catchment Scale ◽  
Flow Paths ◽  
Form And Function ◽  
And Function

Abstract. The phrase form and function was established in architecture and biology and refers to the idea that form and functionality are closely correlated, influence each other, and co-evolve. We suggest transferring this idea to hydrological systems to separate and analyze their two main characteristics: their form, which is equivalent to the spatial structure and static properties, and their function, equivalent to internal responses and hydrological behavior. While this approach is not particularly new to hydrological field research, we want to employ this concept to explicitly pursue the question of what information is most advantageous to understand a hydrological system. We applied this concept to subsurface flow within a hillslope, with a methodological focus on function: we conducted observations during a natural storm event and followed this with a hillslope-scale irrigation experiment. The results are used to infer hydrological processes of the monitored system. Based on these findings, the explanatory power and conclusiveness of the data are discussed. The measurements included basic hydrological monitoring methods, like piezometers, soil moisture, and discharge measurements. These were accompanied by isotope sampling and a novel application of 2-D time-lapse GPR (ground-penetrating radar). The main finding regarding the processes in the hillslope was that preferential flow paths were established quickly, despite unsaturated conditions. These flow paths also caused a detectable signal in the catchment response following a natural rainfall event, showing that these processes are relevant also at the catchment scale. Thus, we conclude that response observations (dynamics and patterns, i.e., indicators of function) were well suited to describing processes at the observational scale. Especially the use of 2-D time-lapse GPR measurements, providing detailed subsurface response patterns, as well as the combination of stream-centered and hillslope-centered approaches, allowed us to link processes and put them in a larger context. Transfer to other scales beyond observational scale and generalizations, however, rely on the knowledge of structures (form) and remain speculative. The complementary approach with a methodological focus on form (i.e., structure exploration) is presented and discussed in the companion paper by Jackisch et al.(2017).

scholarly journals Revisiting Ophidiomycosis (Snake Fungal Disease) After a Decade of Targeted Research

2021 ◽  
Vol 8 ◽  
Author(s):  
Christina M. Davy ◽  
Leonard Shirose ◽  
Doug Campbell ◽  
Rachel Dillon ◽  
Christina McKenzie ◽  
...  
Keyword(s):  
Large Scale ◽  
Sublethal Effects ◽  
Clinical Signs ◽  
Fungal Disease ◽  
Host Susceptibility ◽  
Current Evidence ◽  
Molecular Testing ◽  
Population Declines ◽  
Snake Fungal Disease ◽  
Free Ranging

Emerging infectious diseases (EIDs) are typically characterized by novelty (recent detection) and by increasing incidence, distribution, and/or pathogenicity. Ophidiomycosis, also called snake fungal disease, is caused by the fungus Ophidiomyces ophidiicola (formerly “ophiodiicola”). Ophidiomycosis has been characterized as an EID and as a potential threat to populations of Nearctic snakes, sparking over a decade of targeted research. However, the severity of this threat is unclear. We reviewed the available literature to quantify incidence and effects of ophidiomycosis in Nearctic snakes, and to evaluate whether the evidence supports the ongoing characterization of ophidiomycosis as an EID. Data from Canada remain scarce, so we supplemented the literature review with surveys for O. ophidiicola in the Canadian Great Lakes region. Peer-reviewed reports of clinical signs consistent with ophidiomycosis in free-ranging, Nearctic snakes date back to at least 1998, and retrospective molecular testing of samples extend the earliest confirmed record to 1986. Diagnostic criteria varied among publications (n = 33), confounding quantitative comparisons. Ophidiomycosis was diagnosed or suspected in 36/121 captive snakes and was fatal in over half of cases (66.7%). This result may implicate captivity-related stress as a risk factor for mortality from ophidiomycosis, but could also reflect reporting bias (i.e., infections are more likely to be detected in captive snakes, and severe cases are more likely to be reported). In contrast, ophidiomycosis was diagnosed or suspected in 441/2,384 free-ranging snakes, with mortality observed in 43 (9.8 %). Ophidiomycosis was only speculatively linked to population declines, and we found no evidence that the prevalence of the pathogen or disease increased over the past decade of targeted research. Supplemental surveys and molecular (qPCR) testing in Ontario, Canada detected O. ophidiicola on 76 of 657 free-ranging snakes sampled across ~136,000 km2. The pathogen was detected at most sites despite limited and haphazard sampling. No large-scale mortality was observed. Current evidence supports previous suggestions that the pathogen is a widespread, previously unrecognized endemic, rather than a novel pathogen. Ophidiomycosis may not pose an imminent threat to Nearctic snakes, but further research should investigate potential sublethal effects of ophidiomycosis such as altered reproductive success that could impact population growth, and explore whether shifting environmental conditions may alter host susceptibility.

scholarly journals Changes in landscape composition influence the decline of a threatened woodland caribou population

2020 ◽  
Author(s):  
Heiko Wittmer ◽  
B McLellan ◽  
R Serrouya ◽  
C Apps
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Apparent Competition ◽  
Timber Harvesting ◽  
Conservation Strategies ◽  
Home Ranges ◽  
Vital Rates ◽  
Population Declines ◽  
Woodland Caribou ◽  
Habitat Alterations

Large-scale habitat loss is frequently identified with loss of biodiversity, but examples of the direct effect of habitat alterations on changes in vital rates remain rare. Quantifying and understanding the relationship between habitat composition and changes in vital rates, however, is essential for the development of effective conservation strategies. It has been suggested that the decline of woodland caribou Rangifer tarandus caribou populations in North America is precipitated by timber harvesting that creates landscapes of early seral forests. Such habitat changes have altered the predator-prey system resulting in asymmetric predation, where predators are maintained by alternative prey (i.e. apparent competition). However, a direct link between habitat condition and caribou population declines has not been documented. We estimated survival probabilities for the threatened arboreal lichen-feeding ecotype of woodland caribou in British Columbia, Canada, at two different spatial scales. At the broader scale, observed variation in adult female survival rates among 10 distinct populations (range = 0.67-0.93) was best explained by variation in the amount of early seral stands within population ranges and population density. At the finer scale, home ranges of caribou killed by predators had lower proportions of old forest and more mid-aged forest as compared with multi-annual home ranges where caribou were alive. These results are consistent with predictions from the apparent competition hypothesis and quantify direct fitness consequences for caribou following habitat alterations. We conclude that apparent competition can cause rapid population declines and even extinction where changes in species composition occur following large scale habitat change. © 2007 The Authors. Journal compilation © 2007 British Ecological Society.

scholarly journals An Open Source Framework Approach to Support Condition Monitoring and Maintenance

2020 ◽  
Vol 10 (18) ◽  
pp. 6360
Author(s):  
Jaime Campos ◽  
Pankaj Sharma ◽  
Michele Albano ◽  
Luis Lino Ferreira ◽  
Martin Larrañaga
Keyword(s):  
Condition Monitoring ◽  
Open System ◽  
Health Monitoring ◽  
Large Scale ◽  
Condition Based Maintenance ◽  
Monitoring Methods ◽  
Industry Standards ◽  
Framework Approach ◽  
Push Forward ◽  
Predictive Health

This paper discusses the integration of emergent ICTs, such as the Internet of Things (IoT), the Arrowhead Framework, and the best practices from the area of condition monitoring and maintenance. These technologies are applied, for instance, for roller element bearing fault diagnostics and analysis by simulating faults. The authors first undertook the leading industry standards for condition-based maintenance (CBM), i.e., open system architecture–condition-based maintenance (OSA–CBM) and Machinery Information Management Open System Alliance (MIMOSA), which has been working towards standardizing the integration and interchangeability between systems. In addition, this paper highlights the predictive health monitoring methods that are needed for an effective CBM approach. The monitoring of industrial machines is discussed as well as the necessary details are provided regarding a demonstrator built on a metal sheet bending machine of the Greenbender family. Lastly, the authors discuss the benefits of the integration of the developed prototypes into a service-oriented platform, namely the Arrowhead Framework, which can be instrumental for the remotization of maintenance activities, such as the analysis of various equipment that are geographically distributed, to push forward the grand vision of the servitization of predictive health monitoring methods for large-scale interoperability.

scholarly journals Combining citizen science and weather radar data to study large‐scale bird movements

Ibis ◽  
2020 ◽  
Author(s):  
Nadja Weisshaupt ◽  
Teemu Lehtiniemi ◽  
Jarmo Koistinen
Keyword(s):  
Citizen Science ◽  
Large Scale ◽  
Weather Radar ◽  
Radar Data
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