Measuring nested frequency of plants from digital images with SampleFreq
As our understanding of ecological systems grows, natural resource management becomes ever more dependent on timely, accurate, and inexpensively-collected monitoring data to support management decisions. Vegetation cover, density, and frequency are abundance metrics used in resource management; howe...
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2021
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oai:doaj.org-article:29b664ca40914c05b31e468c57d0c2152021-12-01T04:30:15ZMeasuring nested frequency of plants from digital images with SampleFreq1470-160X10.1016/j.ecolind.2020.106946https://doaj.org/article/29b664ca40914c05b31e468c57d0c2152021-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20308852https://doaj.org/toc/1470-160XAs our understanding of ecological systems grows, natural resource management becomes ever more dependent on timely, accurate, and inexpensively-collected monitoring data to support management decisions. Vegetation cover, density, and frequency are abundance metrics used in resource management; however, frequency data can be collected more quickly than density data and with more repeatability and less sensitivity to inter- and intra-seasonal variation in plant morphology. Moreover, frequency is perhaps the best method for monitoring invasive species across extensive areas. A limitation to the use of frequency data is that plot size affects frequency. The optimal plot size is one that yields measurements suitably removed from 0 or 100% to allow detection of both upward and downward frequency trends, yet the optimum plot size cannot be known before sampling. We addressed this conundrum by developing SampleFreq software that facilitates frequency measurements from digital nadir images of any scale with up to 10 nested plot sizes within the confines of the image dimensions. We conducted accuracy and agreement tests of the software using both artificial populations and field plots. Using artificial population plots, accuracy across all users was 93.4% with a repeatability coefficient of 1.4%, indicating high precision. In a field test, SampleFreq and standard field data averaged a 3.4% difference, and were within approximately 10.5% of each other 95% of the time. From the same field test, SampleFreq repeatability coefficient was 6.7%, while the field method was 4.3%, illustrating that both methods have relatively high precision. Because SampleFreq has high potential accuracy, high agreement with field data, and high precision across a range of users, we recommend using SampleFreq with nadir digital images as a suitable alternative method for monitoring plant frequency.Samuel E. CoxD. Terrance BoothRobert D. BerrymanElsevierarticleVegetationDensityFrequencyPhotographyMonitoringEcologyQH540-549.5ENEcological Indicators, Vol 121, Iss , Pp 106946- (2021) |
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Vegetation Density Frequency Photography Monitoring Ecology QH540-549.5 |
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Vegetation Density Frequency Photography Monitoring Ecology QH540-549.5 Samuel E. Cox D. Terrance Booth Robert D. Berryman Measuring nested frequency of plants from digital images with SampleFreq |
description |
As our understanding of ecological systems grows, natural resource management becomes ever more dependent on timely, accurate, and inexpensively-collected monitoring data to support management decisions. Vegetation cover, density, and frequency are abundance metrics used in resource management; however, frequency data can be collected more quickly than density data and with more repeatability and less sensitivity to inter- and intra-seasonal variation in plant morphology. Moreover, frequency is perhaps the best method for monitoring invasive species across extensive areas. A limitation to the use of frequency data is that plot size affects frequency. The optimal plot size is one that yields measurements suitably removed from 0 or 100% to allow detection of both upward and downward frequency trends, yet the optimum plot size cannot be known before sampling. We addressed this conundrum by developing SampleFreq software that facilitates frequency measurements from digital nadir images of any scale with up to 10 nested plot sizes within the confines of the image dimensions. We conducted accuracy and agreement tests of the software using both artificial populations and field plots. Using artificial population plots, accuracy across all users was 93.4% with a repeatability coefficient of 1.4%, indicating high precision. In a field test, SampleFreq and standard field data averaged a 3.4% difference, and were within approximately 10.5% of each other 95% of the time. From the same field test, SampleFreq repeatability coefficient was 6.7%, while the field method was 4.3%, illustrating that both methods have relatively high precision. Because SampleFreq has high potential accuracy, high agreement with field data, and high precision across a range of users, we recommend using SampleFreq with nadir digital images as a suitable alternative method for monitoring plant frequency. |
format |
article |
author |
Samuel E. Cox D. Terrance Booth Robert D. Berryman |
author_facet |
Samuel E. Cox D. Terrance Booth Robert D. Berryman |
author_sort |
Samuel E. Cox |
title |
Measuring nested frequency of plants from digital images with SampleFreq |
title_short |
Measuring nested frequency of plants from digital images with SampleFreq |
title_full |
Measuring nested frequency of plants from digital images with SampleFreq |
title_fullStr |
Measuring nested frequency of plants from digital images with SampleFreq |
title_full_unstemmed |
Measuring nested frequency of plants from digital images with SampleFreq |
title_sort |
measuring nested frequency of plants from digital images with samplefreq |
publisher |
Elsevier |
publishDate |
2021 |
url |
https://doaj.org/article/29b664ca40914c05b31e468c57d0c215 |
work_keys_str_mv |
AT samuelecox measuringnestedfrequencyofplantsfromdigitalimageswithsamplefreq AT dterrancebooth measuringnestedfrequencyofplantsfromdigitalimageswithsamplefreq AT robertdberryman measuringnestedfrequencyofplantsfromdigitalimageswithsamplefreq |
_version_ |
1718405832949891072 |