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Using digital time-lapse cameras to monitor species-specific understorey and overstorey phenology in support of wildlife habitat assessment

Using digital time-lapse cameras to monitor species-specific understorey and overstorey phenology in support of wildlife habitat assessment
Using digital time-lapse cameras to monitor species-specific understorey and overstorey phenology in support of wildlife habitat assessment
Critical to habitat management is the understanding of not only the location of animal food resources, but also the timing of their availability. Grizzly bear (Ursus arctos) diets, for example, shift seasonally as different vegetation species enter key phenological phases. In this paper, we describe the use of a network of seven ground-based digital camera systems to monitor understorey and overstorey vegetation within species-specific regions of interest. Established across an elevation gradient in western Alberta, Canada, the cameras collected true-colour (RGB) images daily from 13 April 2009 to 27 October 2009. Fourth-order polynomials were fit to an RGB-derived index, which was then compared to field-based observations of phenological phases. Using linear regression to statistically relate the camera and field data, results indicated that 61% (r 2?= 0.61, df = 1, F?= 14.3, p?= 0.0043) of the variance observed in the field phenological phase data is captured by the cameras for the start of the growing season and 72% (r 2?= 0.72, df = 1, F?= 23.09, p?= 0.0009) of the variance in length of growing season. Based on the linear regression models, the mean absolute differences in residuals between predicted and observed start of growing season and length of growing season were 4 and 6 days, respectively. This work extends upon previous research by demonstrating that specific understorey and overstorey species can be targeted for phenological monitoring in a forested environment, using readily available digital camera technology and RGB-based vegetation indices.
0167-6369
1-13
Bater, Christopher W.
c826643f-810c-44d7-a8aa-eb8c915e6684
Coops, Nicholas C.
5511e778-fec2-4f54-8708-de65ba5a0992
Wulder, Michael A.
13414360-db3d-4d88-a76d-ccffd69d0084
Hilker, Thomas
c7fb75b8-320d-49df-84ba-96c9ee523d40
Nielsen, Scott E.
4cf6ab4b-dbf8-433b-b9da-5c4c58916e54
McDermid, Greg
7d3bf34b-12c5-453a-ab33-4ef6a9d14dd2
Stenhouse, Gordon B.
7d2baab4-cdc2-40bd-ba3a-e3a34e606749
Bater, Christopher W.
c826643f-810c-44d7-a8aa-eb8c915e6684
Coops, Nicholas C.
5511e778-fec2-4f54-8708-de65ba5a0992
Wulder, Michael A.
13414360-db3d-4d88-a76d-ccffd69d0084
Hilker, Thomas
c7fb75b8-320d-49df-84ba-96c9ee523d40
Nielsen, Scott E.
4cf6ab4b-dbf8-433b-b9da-5c4c58916e54
McDermid, Greg
7d3bf34b-12c5-453a-ab33-4ef6a9d14dd2
Stenhouse, Gordon B.
7d2baab4-cdc2-40bd-ba3a-e3a34e606749

Bater, Christopher W., Coops, Nicholas C., Wulder, Michael A., Hilker, Thomas, Nielsen, Scott E., McDermid, Greg and Stenhouse, Gordon B. (2011) Using digital time-lapse cameras to monitor species-specific understorey and overstorey phenology in support of wildlife habitat assessment. Environmental Monitoring and Assessment, 180 (1), 1-13. (doi:10.1007/s10661-010-1768-x).

Record type: Article

Abstract

Critical to habitat management is the understanding of not only the location of animal food resources, but also the timing of their availability. Grizzly bear (Ursus arctos) diets, for example, shift seasonally as different vegetation species enter key phenological phases. In this paper, we describe the use of a network of seven ground-based digital camera systems to monitor understorey and overstorey vegetation within species-specific regions of interest. Established across an elevation gradient in western Alberta, Canada, the cameras collected true-colour (RGB) images daily from 13 April 2009 to 27 October 2009. Fourth-order polynomials were fit to an RGB-derived index, which was then compared to field-based observations of phenological phases. Using linear regression to statistically relate the camera and field data, results indicated that 61% (r 2?= 0.61, df = 1, F?= 14.3, p?= 0.0043) of the variance observed in the field phenological phase data is captured by the cameras for the start of the growing season and 72% (r 2?= 0.72, df = 1, F?= 23.09, p?= 0.0009) of the variance in length of growing season. Based on the linear regression models, the mean absolute differences in residuals between predicted and observed start of growing season and length of growing season were 4 and 6 days, respectively. This work extends upon previous research by demonstrating that specific understorey and overstorey species can be targeted for phenological monitoring in a forested environment, using readily available digital camera technology and RGB-based vegetation indices.

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Accepted/In Press date: 21 October 2010
e-pub ahead of print date: 18 November 2010
Published date: September 2011
Organisations: Global Env Change & Earth Observation, Geography & Environment

Identifiers

Local EPrints ID: 384648
URI: https://eprints.soton.ac.uk/id/eprint/384648
ISSN: 0167-6369
PURE UUID: af5cae0f-6942-49cd-974d-18843d1c28bd

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Date deposited: 27 Jan 2016 12:08
Last modified: 17 Jul 2017 20:03

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