scholarly journals A methodological roadmap to quantify animal-vectored spatial ecosystem subsidies

2020 ◽  
Author(s):  
Diego Ellis-Soto ◽  
Kristy M. Ferraro ◽  
Matteo Rizzuto ◽  
Emily Briggs ◽  
Julia D. Monk ◽  
...  
Keyword(s):  
Animal Movement ◽  
Open Systems ◽  
Nutrient Transport ◽  
Ecosystem Dynamics ◽  
Ecosystem Impacts ◽  
Practical Applications ◽  
Ecosystem Theory ◽  
Spatio Temporal ◽  
High Level ◽  
Tracking Devices

Ecosystems are open systems connected through spatial flows of energy, matter, and nutrients. Predicting and managing ecosystem interdependence requires a rigorous quantitative understanding of the drivers and vectors that connect ecosystems across spatio-temporal scales. Animals act as such vectors when they transport nutrients across landscapes in the form of excreta, egesta, and their own bodies. Here, we introduce a methodological roadmap that combines movement, foraging, and ecosystem ecology to study the effects of animal-vectored nutrient transport on meta-ecosystems. The meta-ecosystem concept — the notion that ecosystems are connected in space and time by flows of energy, matter, and organisms across boundaries — provides a theoretical framework on which to base our understanding of animal-vectored nutrient transport. However, partly due to its high level of abstraction, there are few empirical tests of meta-ecosystem theory, and while we may label animals as important mediators of ecosystem services, we lack predictive inference of their relative roles and impacts on diverse ecosystems. Recently developed technologies and methods — tracking devices, mechanistic movement models, diet reconstruction techniques and remote sensing — have the potential to facilitate the quantification of animal-vectored nutrient flows and increase the predictive power of meta-ecosystem theory. Understanding the mechanisms by which animals shape ecosystem dynamics may be important for ongoing conservation, rewilding, and restoration initiatives around the world, and for more accurate models of ecosystem nutrient budgets. We provide conceptual examples that show how our proposed integration of methodologies could help investigate ecosystem impacts of animal movement. We conclude by describing practical applications to understanding cross-ecosystem contributions of animals on the move.

Unoccupied aerial vehicle-assisted monitoring of benthic vegetation in the coastal zone enhances the quality of ecological data

2021 ◽  
pp. 030913332110520
Author(s):  
Niels Svane ◽  
Troels Lange ◽  
Sara Egemose ◽  
Oliver Dalby ◽  
Aris Thomasberger ◽  
...  
Keyword(s):  
Zostera Marina ◽  
Spatial Scales ◽  
Fucus Vesiculosus ◽  
Ecosystem Dynamics ◽  
Spatial Extent ◽  
Total Biomass ◽  
Ecological Data ◽  
Error Matrix ◽  
Object Based ◽  
Spatio Temporal

Traditional monitoring (e.g., in-water based surveys) of eelgrass meadows and perennial macroalgae in coastal areas is time and labor intensive, requires extensive equipment, and the collected data has a low temporal resolution. Further, divers and Remotely Operated Vehicles (ROVs) have a low spatial extent that cover small fractions of full systems. The inherent heterogeneity of eelgrass meadows and macroalgae assemblages in these coastal systems makes interpolation and extrapolation of observations complicated and, as such, methods to collect data on larger spatial scales whilst retaining high spatial resolution is required to guide management. Recently, the utilization of Unoccupied Aerial Vehicles (UAVs) has gained popularity in ecological sciences due to their ability to rapidly collect large amounts of area-based and georeferenced data, making it possible to monitor the spatial extent and status of SAV communities with limited equipment requirements compared to ROVs or diver surveys. This paper is focused on the increased value provided by UAV-based, data collection (visual/Red Green Blue imagery) and Object Based Image Analysis for gaining an improved understanding of eelgrass recovery. It is demonstrated that delineation and classification of two species of SAV ( Fucus vesiculosus and Zostera marina) is possible; with an error matrix indicating 86–92% accuracy. Classified maps also highlighted the increasing biomass and areal coverage of F. vesiculosus as a potential stressor to eelgrass meadows. Further, authors derive a statistically significant conversion of percentage cover to biomass ( R2 = 0.96 for Fucus vesiculosus, R2 = 0.89 for Zostera marina total biomass, and R2 = 0.94 for AGB alone, p < 0.001). Results here provide an example of mapping cover and biomass of SAV and provide a tool to undertake spatio-temporal analyses to enhance the understanding of eelgrass ecosystem dynamics.

Damage Detection in Flexible Propeller Beam Structures by Exploiting Impact-Induced Coupled Acceleration Signals

2011 ◽  
Author(s):  
Ioannis T. Georgiou
Keyword(s):  
Data Driven ◽  
Distributed Information ◽  
Modal Expansion ◽  
Shape Difference ◽  
Spatio Temporal ◽  
Temporal Sample ◽  
High Level ◽  
Proper Orthogonal ◽  
Acceleration Signals

A local damage at the tip of a composite propeller is diagnosed by properly comparing its impact-induced free coupled dynamics to that of a pristine wooden propeller of the same size and shape. This is accomplished by creating indirectly via collocated measurements distributed information for the coupled acceleration field of the propellers. The powerful data-driven modal expansion analysis delivered by the Proper Orthogonal Decomposition (POD) Transform reveals that ensembles of impact-induced collocated coupled experimental acceleration signals are underlined by a high level of spatio-temporal coherence. Thus they furnish a valuable spatio-temporal sample of coupled response induced by a point impulse. In view of this fact, a tri-axial sensor was placed on the propeller hub to collect collocated coupled acceleration signals induced via modal hammer nondestructive impacts and thus obtained a reduced order characterization of the coupled free dynamics. This experimental data-driven analysis reveals that the in-plane unit components of the POD modes for both propellers have similar shapes-nearly identical. For the damaged propeller this POD shape-difference is quite pronounced. The shapes of the POD modes are used to compute indices of difference reflecting directly damage. At the first POD energy level, the shape-difference indices of the damaged composite propeller are quite larger than those of the pristine wooden propeller.

scholarly journals An Assessment of the Reliability of the NIGNET Data

2019 ◽  
Vol 3 (1) ◽  
pp. 18-29
Author(s):  
E. G. Ayodele ◽  
C. J. Okolie ◽  
O. A. Mayaki
Keyword(s):  
National Development ◽  
Accurate Information ◽  
Positional Accuracy ◽  
Data Archiving ◽  
Practical Applications ◽  
3 Dimensional ◽  
Gnss Network ◽  
High Level ◽  
Gnss Data ◽  
Geodetic Reference Frame

The Nigerian Geodetic Reference Frame is defined by a number of Continuously Operating Reference Stations (CORS) that constitute the Nigerian GNSS Network (NIGNET). NIGNET is essential for planning and national development with the main goal of ensuring consistency in the geodetic framework both nationally and internationally. Currently, the strength of the network in terms of data reliability has not been adequately studied due to the fact that research into CORS in Nigeria is just evolving, which constitutes a limitation in its applications. Therefore, the aim of this research is to explore the reliability of the 3-dimensional coordinates of NIGNET to inform usability and adequacy for both scientific and practical applications. In particular, this study examines if the 3-dimensional coordinates of NIGNET are equally reliable in terms of positional accuracy. Accordingly, this study utilised GNSS data collected over a period of six years (2011 – 2016) from the network to compute the daily geocentric coordinates of the stations. Exploratory and statistical data analysis techniques were used to understand the magnitude of the errors and the accuracy level in the 3-dimensional coordinates. For this purpose, accuracy metrics such as standard deviation (𝜎), standard error (𝑆𝐸) and root mean square error (RMSE) were computed. While One-way ANOVA was conducted to explore the coordinate differences. The results obtained showed that SE and RMSE ranged from 13.00 − 56.50𝑚𝑚 and 14.38 − 73.16𝑚𝑚 respectively, which signifies high accuracy. Overall, while 88% of the network showed a high level of positional accuracy, the reliability has been compromised due to excessive gaps in the data archiving. Therefore, due attention must be given to NIGNET to achieve its purpose in the provision of accurate information for various geospatial applications. Also, any efforts directed at understanding the practical implications of NIGNET must be well-embraced for the realization of its set objectives.

scholarly journals Fast Drivable Areas Estimation with Multi-Task Learning for Real-Time Autonomous Driving Assistant

2021 ◽  
Vol 11 (22) ◽  
pp. 10713
Author(s):  
Dong-Gyu Lee
Keyword(s):  
Real Time ◽  
Computational Efficiency ◽  
Autonomous Driving ◽  
Learning Approaches ◽  
Practical Applications ◽  
Task Learning ◽  
Lane Line ◽  
High Level ◽  
Time Autonomous

Autonomous driving is a safety-critical application that requires a high-level understanding of computer vision with real-time inference. In this study, we focus on the computational efficiency of an important factor by improving the running time and performing multiple tasks simultaneously for practical applications. We propose a fast and accurate multi-task learning-based architecture for joint segmentation of drivable area, lane line, and classification of the scene. An encoder-decoder architecture efficiently handles input frames through shared representation. A comprehensive understanding of the driving environment is improved by generalization and regularization from different tasks. The proposed method learns end-to-end through multi-task learning on a very challenging Berkeley Deep Drive dataset and shows its robustness for three tasks in autonomous driving. Experimental results show that the proposed method outperforms other multi-task learning approaches in both speed and accuracy. The computational efficiency of the method was over 93.81 fps at inference, enabling execution in real-time.

scholarly journals The International School of Crystallography: an example of continuing education

2014 ◽  
Vol 70 (a1) ◽  
pp. C1274-C1274
Author(s):  
Annalisa Guerri ◽  
Giovanna Scapin ◽  
Paola Spadon
Keyword(s):  
Interpersonal Relationships ◽  
Public Awareness ◽  
International School ◽  
Theoretical Background ◽  
Great Success ◽  
Practical Applications ◽  
Local Staff ◽  
School Teaching ◽  
Traditional Lectures ◽  
High Level

2014 has been declared by UNESCO the International Year of Crystallography. Following the declaration, many initiatives have flourished with the intent of spreading the science and culture of crystallography, since among the major objectives of the IYCr2014 are increase of public awareness on the science of crystallography, promotion of education and research in all fields of crystallography and fostering of international collaborations. The International School of Crystallography is an internationally recognized meeting that was started in 1974 by Prof. Riva di Sanseverino, with the similar goals of promoting high level crystallographic education, scientific exchanges and collaborations. In 2014 the school celebrates its 40th year of activity. During these forty years, courses have been held on many different topics addressing all aspects of crystallography, from crystal growth theory to practical applications in drug discovery to the use of cutting edge technologies; students and teachers have been brought together in an environment that fostered high level scientific discussions as well as unique interpersonal relationships. Many of the students moved on to become well known personality in the crystallographic community, while retaining collaborations and friendships started during the School. Through these years the School teaching methods have also evolved, taking advantage of the fast technological progress of the past 10 years or so. The School offers both traditional lectures and practical computer-based workshops, to guarantee the students not only a theoretical background, but also hands-on experiences on applied crystallography. The dedication of the organizers and lecturers, the unconditioned support of the local staff, and the unique location of the School have made it a great success and a very popular meeting for generations of crystallographers.

scholarly journals Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecology

2010 ◽  
Vol 365 (1550) ◽  
pp. 2303-2312 ◽  
Author(s):  
Mark Hebblewhite ◽  
Daniel T. Haydon
Keyword(s):  
Animal Ecology ◽  
Animal Movement ◽  
Gps Telemetry ◽  
Long Distance ◽  
Location Data ◽  
The Past ◽  
Movement Data ◽  
Migratory Songbirds ◽  
Spatio Temporal ◽  
Gps Devices

In the past decade, ecologists have witnessed vast improvements in our ability to collect animal movement data through animal-borne technology, such as through GPS or ARGOS systems. However, more data does not necessarily yield greater knowledge in understanding animal ecology and conservation. In this paper, we provide a review of the major benefits, problems and potential misuses of GPS/Argos technology to animal ecology and conservation. Benefits are obvious, and include the ability to collect fine-scale spatio-temporal location data on many previously impossible to study animals, such as ocean-going fish, migratory songbirds and long-distance migratory mammals. These benefits come with significant problems, however, imposed by frequent collar failures and high cost, which often results in weaker study design, reduced sample sizes and poorer statistical inference. In addition, we see the divorcing of biologists from a field-based understanding of animal ecology to be a growing problem. Despite these difficulties, GPS devices have provided significant benefits, particularly in the conservation and ecology of wide-ranging species. We conclude by offering suggestions for ecologists on which kinds of ecological questions would currently benefit the most from GPS/Argos technology, and where the technology has been potentially misused. Significant conceptual challenges remain, however, including the links between movement and behaviour, and movement and population dynamics.

Revisitation analysis uncovers spatio-temporal patterns in animal movement data

Ecography ◽  
2018 ◽  
Vol 41 (11) ◽  
pp. 1801-1811 ◽  
Author(s):  
Chloe Bracis ◽  
Keith L. Bildstein ◽  
Thomas Mueller
Keyword(s):  
Animal Movement ◽  
Temporal Patterns ◽  
Movement Data ◽  
Spatio Temporal

scholarly journals Practical Applications of Systems Thinking to Business

Systems ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 14
Author(s):  
Jamie Monat ◽  
Matthew Amissah ◽  
Thomas Gannon
Keyword(s):  
Systems Thinking ◽  
Business Management ◽  
Organizational Management ◽  
System Thinking ◽  
Business Managers ◽  
Practical Applications ◽  
Business Failures ◽  
Hands On ◽  
High Level ◽  
Systems Thinking Approach

In this paper we summarize the research on Systems Thinking for business management and explore several examples of business failures due to a lack of application of Systems Thinking, with an ultimate goal of offering a Systems Thinking approach that is useful to all levels of management. Although there is significant literature aimed at facilitating Systems Thinking in organizational management, there remains a lack of adoption of Systems Thinking in mainstream business practice. This is perhaps because the literature does not reduce high-level Systems Thinking principles to hands-on, practical protocols that are accessible for typical managers, thus limiting the working application of Systems Thinking concepts to researchers and consultants who specialize in the field. The goal of this work is to not only elaborate on the high-level ideals of System Thinking, but also to articulate a more precise and practical hands-on approach that is useful to all levels of business managers.

scholarly journals Asymmetric Residual Neural Network for Accurate Human Activity Recognition

Information ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 203 ◽  
Author(s):  
Jun Long ◽  
Wuqing Sun ◽  
Zhan Yang ◽  
Osolo Ian Raymond
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Time Window ◽  
Research Problem ◽  
Human Activity Recognition ◽  
Sensor Data ◽  
Practical Applications ◽  
Long Time ◽  
Benchmark Datasets ◽  
High Level

Human activity recognition (HAR) using deep neural networks has become a hot topic in human–computer interaction. Machines can effectively identify human naturalistic activities by learning from a large collection of sensor data. Activity recognition is not only an interesting research problem but also has many real-world practical applications. Based on the success of residual networks in achieving a high level of aesthetic representation of automatic learning, we propose a novel asymmetric residual network, named ARN. ARN is implemented using two identical path frameworks consisting of (1) a short time window, which is used to capture spatial features, and (2) a long time window, which is used to capture fine temporal features. The long time window path can be made very lightweight by reducing its channel capacity, while still being able to learn useful temporal representations for activity recognition. In this paper, we mainly focus on proposing a new model to improve the accuracy of HAR. In order to demonstrate the effectiveness of the ARN model, we carried out extensive experiments on benchmark datasets (i.e., OPPORTUNITY, UniMiB-SHAR) and compared the results with some conventional and state-of-the-art learning-based methods. We discuss the influence of networks parameters on performance to provide insights about its optimization. Results from our experiments show that ARN is effective in recognizing human activities via wearable datasets.

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