The Application of NIRS to Determine Animal Physiological Traits for Wildlife Management and Conservation

The ability to measure and monitor wildlife populations is important for species management and conservation. The use of near-infrared spectroscopy (NIRS) to rapidly detect physiological traits from wildlife scat and other body materials could play an important role in the conservation of species. Previous research has demonstrated the potential for NIRS to detect diseases such as the novel COVID-19 from saliva, parasites from feces, and numerous other traits from animal skin, hair, and scat, such as cortisol metabolites, diet quality, sex, and reproductive status, that may be useful for population monitoring. Models developed from NIRS data use light reflected from a sample to relate the variation in the sample’s spectra to variation in a trait, which can then be used to predict that trait in unknown samples based on their spectra. The modelling process involves calibration, validation, and evaluation. Data sampling, pre-treatments, and the selection of training and testing datasets can impact model performance. We review the use of NIRS for measuring physiological traits in animals that may be useful for wildlife management and conservation and suggest future research to advance the application of NIRS for this purpose.

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Comparison of spectral selection methods in the development of classification models from visible near infrared hyperspectral imaging data

Journal of Spectral Imaging ◽

10.1255/jsi.2019.a4 ◽

2019 ◽

Cited By ~ 3

Author(s):

Aoife Gowen ◽

Jun-Li Xu ◽

Ana Herrero-Langreo

Keyword(s):

Hyperspectral Imaging ◽

Near Infrared ◽

Spatial Information ◽

Hyperspectral Image ◽

Imaging Spectroscopy ◽

Model Performance ◽

Data Sampling ◽

Classification Models ◽

Imaging Data ◽

Selection Of

Applications of hyperspectral imaging (HSI) to the quantitative and qualitative measurement of samples have grown widely in recent years, due mainly to the improved performance and lower cost of imaging spectroscopy instrumentation. Data sampling is a crucial yet often overlooked step in hyperspectral image analysis, which impacts the subsequent results and their interpretation. In the selection of pixel spectra for the calibration of classification models, the spatial information in HSI data can be exploited. In this paper, a variety of sampling strategies for selection of pixel spectra are presented, exemplified through five case studies. The strategies are compared in terms of the proportion of global variability captured, practicality and predictive model performance. The use of variographic analysis as a guide to the spatial segmentation prior to sampling leads to the selection of representative subsets while reducing the variation in model performance parameters over repeated random selection.

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International Wildlife Management: Conservation Challenges in a Changing World. Wildlife Management and Conservation. Edited by John L. Koprowski and Paul R. Krausman. Published in association with The Wildlife Society by Johns Hopkins University Press, Baltimore, Maryland. $74.95. xvii + 226 p.; ill.; index. ISBN: 9781421432854 (hc); 9781421432861 (eb). 2019.

The Quarterly Review of Biology ◽

10.1086/714464 ◽

2021 ◽

Vol 96 (2) ◽

pp. 154-154

Author(s):

Julia Greenberg

Keyword(s):

Wildlife Management ◽

Johns Hopkins University ◽

Management And Conservation ◽

Changing World

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Wildlife Management and Conservation.

Journal of Ecology ◽

10.2307/2257678 ◽

1966 ◽

Vol 54 (1) ◽

pp. 279

Author(s):

J. M. Cherrett ◽

J. B. Trefethen

Keyword(s):

Wildlife Management ◽

Management And Conservation

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Commentary: Linking Movement Ecology with Wildlife Management and Conservation

Frontiers in Ecology and Evolution ◽

10.3389/fevo.2016.00030 ◽

2016 ◽

Vol 4 ◽

Cited By ~ 9

Author(s):

Jennifer McGowan ◽

Hugh P. Possingham

Keyword(s):

Wildlife Management ◽

Movement Ecology ◽

Management And Conservation

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Two Decades of Invasive Western Corn Rootworm Population Monitoring in Croatia

Insects ◽

10.3390/insects9040160 ◽

2018 ◽

Vol 9 (4) ◽

pp. 160 ◽

Cited By ~ 1

Author(s):

Martina Mrganić ◽

Renata Bažok ◽

Katarina Mikac ◽

Hugo Benítez ◽

Darija Lemic

Keyword(s):

Adult Population ◽

Monitoring Program ◽

Population Monitoring ◽

The United States ◽

Western Corn Rootworm ◽

Population Variation ◽

Future Research ◽

Corn Rootworm ◽

Population Abundance ◽

National Monitoring

Western corn rootworm (WCR) is the worst pest of maize in the United States, and since its spread through Europe, WCR is now recognized as the most serious pest affecting maize production. After the beetle’s first detection in Serbia in 1992, neighboring countries such as Croatia have established a national monitoring program. For more than two decades WCR adult population abundance and variability was monitored. With traditional density monitoring, more recent genetic monitoring, and the newest morphometric monitoring of WCR populations, Croatia possesses a great deal of knowledge about the beetle’s invasion process over time and space. Croatia’s position in Europe is unique as no other European nation has demonstrated such a detailed and complete understanding of an invasive insect. The combined use of traditional monitoring (attractant cards), which can be effectively used to predict population abundance, and modern monitoring procedures, such as population genetics and geometric morphometrics, has been effectively used to estimate inter- and intra-population variation. The combined application of traditional and modern monitoring techniques will enable more efficient control and management of WCR across Europe. This review summarizes the research on WCR in Croatia from when it was first detected in 1992 until 2018. An outline of future research needs is provided.

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A Methodological Review of fNIRS in Driving Research: Relevance to the Future of Autonomous Vehicles

Frontiers in Human Neuroscience ◽

10.3389/fnhum.2021.637589 ◽

2021 ◽

Vol 15 ◽

Author(s):

Stephanie Balters ◽

Joseph M. Baker ◽

Joseph W. Geeseman ◽

Allan L. Reiss

Keyword(s):

Brain Imaging ◽

Near Infrared ◽

Functional Neuroimaging ◽

Meta Analysis ◽

Autonomous Driving ◽

Functional Brain Imaging ◽

Future Research ◽

Functional Near Infrared Spectroscopy ◽

Methodological Review ◽

The Future

As automobile manufacturers have begun to design, engineer, and test autonomous driving systems of the future, brain imaging with functional near-infrared spectroscopy (fNIRS) can provide unique insights about cognitive processes associated with evolving levels of autonomy implemented in the automobile. Modern fNIRS devices provide a portable, relatively affordable, and robust form of functional neuroimaging that allows researchers to investigate brain function in real-world environments. The trend toward “naturalistic neuroscience” is evident in the growing number of studies that leverage the methodological flexibility of fNIRS, and in doing so, significantly expand the scope of cognitive function that is accessible to observation via functional brain imaging (i.e., from the simulator to on-road scenarios). While more than a decade’s worth of study in this field of fNIRS driving research has led to many interesting findings, the number of studies applying fNIRS during autonomous modes of operation is limited. To support future research that directly addresses this lack in autonomous driving research with fNIRS, we argue that a cogent distillation of the methods used to date will help facilitate and streamline this research of tomorrow. To that end, here we provide a methodological review of the existing fNIRS driving research, with the overarching goal of highlighting the current diversity in methodological approaches. We argue that standardization of these approaches will facilitate greater overlap of methods by researchers from all disciplines, which will, in-turn, allow for meta-analysis of future results. We conclude by providing recommendations for advancing the use of such fNIRS technology in furthering understanding the adoption of safe autonomous vehicle technology.

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Near-Infrared Spectroscopic Screening for Bladder Disease in Africa: Training Rural Clinic Staff to Collect Data of Diagnostic Quality

Journal of Spectroscopy ◽

10.1155/2016/1241862 ◽

2016 ◽

Vol 2016 ◽

pp. 1-7 ◽

Cited By ~ 1

Author(s):

Lynn Stothers ◽

Andrew Macnab ◽

Sharif Mutabazi ◽

Ronald Mukisa ◽

Behnam Molavi ◽

...

Keyword(s):

Data Collection ◽

Near Infrared ◽

Diagnostic Quality ◽

Clinic Staff ◽

Bladder Disease ◽

Patient Screening ◽

Interactive Training ◽

Workshop Training ◽

Nirs Data ◽

The Cost

Background. While near-infrared spectroscopy (NIRS) has recognized relevance for developing countries, biomedical applications are rare. This reflects the cost and complexity of NIRS and the convention of comprehensive training for accurate data collection. In an international initiative using transcutaneous NIRS to screen for bladder disease in Africa, we evaluated if interactive training enabled clinic staff to collect data accurately.Methods. Workshop training in a Ugandan medical clinic on NIRS monitoring theory; bladder physiology and chromophore changes occurring with disease; device orientation; device positioning over the bladder, monitoring subjects during voiding; and saving/uploading data. Participation in patient screening followed with observation, assistance, and then data collection. Evaluation comprised conduct of serial independent screenings with analysis if saved files were of diagnostic quality.Results. 10 individuals attended 1-hour workshops and then 0.5–3.0 hours of screening. Five then felt able to conduct screening independently and all collected data were of diagnostic quality (>5 consecutive patients); all had participated in screening for >1.5 hours (6+ subjects); less participation allowed competent assistance but not consistent adherence to the monitoring protocol.Conclusion. A simplified NIRS system, small-group theory/orientation workshops, and >I.5 hours of 1 : 1 training during screening enabled clinic staff in Africa to collect accurate NIRS data.

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Evaluating Model Performance and Significance

Ecological Niches and Geographic Distributions (MPB-49) ◽

10.23943/princeton/9780691136868.003.0009 ◽

2011 ◽

Cited By ~ 1

Author(s):

A. Townsend Peterson ◽

Jorge Soberón ◽

Richard G. Pearson ◽

Robert P. Anderson ◽

Enrique Martínez-Meyer ◽

...

Keyword(s):

Model Evaluation ◽

Model Calibration ◽

Model Performance ◽

Future Research ◽

Commission Error ◽

Tests Of Significance ◽

Occurrence Data ◽

Model Predictions ◽

Key Concepts

This chapter describes a framework for selecting appropriate strategies for evaluating model performance and significance. It begins with a review of key concepts, focusing on how primary occurrence data can be presence-only, presence/background, presence/pseudoabsence, or presence/absence as well as factors that may contribute to apparent commission error. It then considers the availability of two pools of occurrence data: one for model calibration and another for evaluation of model predictions. It also discusses strategies for detecting overfitting or sensitivity to bias in model calibration, with particular emphasis on quantification of performance and tests of significance. Finally, it suggests directions for future research as regards model evaluation, highlighting areas in need of theoretical and/or methodological advances.

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Feeding for a Purpose

The Birds at My Table ◽

10.7591/cornell/9781501710780.003.0007 ◽

2018 ◽

Author(s):

Darryl Jones

Keyword(s):

Conservation Biology ◽

Wildlife Management ◽

Supplementary Foods ◽

Management And Conservation

The use of supplementary foods is a widely employed technique in wildlife management and conservation biology. Here, many well-studied examples are described as a further way to understand the possible implications of feeding birds in gardens.

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