Examining the Relationship between Moss Communities and the

Cartographic Depth-to-Water Index

Prepared by: Monique Goguen

November 2013

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Plume moss (Ptilium crista-castrensis)

Outline

• Objective

• Study Area Description

• Moss Species

• Methods

• Results

• Conclusion

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Objective • The main objective of this project is to examine the

relationship between moss communities and LiDAR-derived cartographic depth-to-water (DTW) index.

• Study aims to determine whether the DTW mapping process could be useful as a tool for predicting the spatial distribution of moss species on a landscape level.

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Study Area • Regent Bog, a wetland

complex in Fredericton, New Brunswick.

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• Study area approx. 20 hectares in size.

Bryophyte Ecology • Bryophytes are small non-vascular plants.

• Geospatial distribution influenced by microclimate and suitable substrate, including soil moisture regime.

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Sphagnum moss (Sphagnum sp.)

Schreber’s moss (Pleurozium schreberi)

Haircap moss (Polytrichum commune)

Wavy Dicranum (Dicranum polysetum)

Plume moss (Ptilium crista-castrensis)

Step moss (Hylocomium splendens)

Bazzania (Bazzania trilobata)

Geomatic Procedures • GPS on-foot tracking of inner and outer moss boundaries:

• Sphagnum moss

• Schreber’s moss

• GPS-locating plots along upland-wetland transitions

• Mapping flow accumulation, flow channels, and depth-to-water using LiDAR-derived elevation data (bare-ground, full-feature) and surface images at 1 m resolution

• Correlating plot data with raster data

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Vegetation Plots

• 180 sample locations

• 1m x 1m plots

• Visual estimate of abundance (%) for each moss species

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GPS Plot Locations on GeoNB Imagery

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Wet Areas Mapping • Data derived from the bare ground digital elevation model of

digitally processed LiDAR data at 1 metre resolution:

• Predicted Stream Channel Lines (D8 Algorithm for flow accumulation – 0.5 to 4 hectare flow initiation threshold)

• Channels may not be wet during every season, but they are predicted to have a high potential for being wet during a heavy rain event or wet season.

• Cartographic Depth-to-Water

• Informs about the depth to water index (elevation rise) between the bare ground surface and the cartographically referenced water table surface below.

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Aerial Photo (GeoNB)

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Bare Earth LiDAR (Hillshade)

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Cartographic Depth-to-Water

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Canopy Height (Full Feature LiDAR 1st returns) + (Depth-to-Water)

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Stream Flow-Initiation Area

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4 ha

1 ha

2 ha

0.5 ha

GPS Tracked Moss Boundaries

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DTW Map with GPS Lines

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DTW Map with GPS Lines

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DTW Map with GPS Lines

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DTW Map with GPS Lines

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Sphagnum Boundary Conformance

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DTW (m) Sum Shape Length (m)

Percent Total

0-0.1 2388.21 0.41

0.1-0.25 1704.69 0.29

0.25-0.5 897.15 0.15

0.5-1 508.98 0.09

Relative Abundance of Sphagnum

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Abundance vs. DTW: Sphagnum

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R² = 0.9586

R² = 0.9807

R² = 0.9294

R² = 0.9521

0

10

20

30

40

-1.5 -1.0 -0.5 0.0 0.5 1.0

Avg

. Ab

un

dan

ce (%

)

log10 of DTW

0.5 ha

1 ha

2 ha

4 ha

Dry Wet

Stream Flow-Initiation Area

Abundance vs. DTW

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Schreber’s moss Wavy Dicranum

Stream Flow-Initiation Area

0.5 ha

1 ha

2 ha

4 ha

Bazzania Plume moss Step moss

Common Haircap moss

Log10 of DTW

Avg

. Ab

un

dan

ce (%

)

Summary

• DTW mapping useful as a tool for predicting the spatial distribution of moss species in a wetland ecosystem.

• The GPS tracked moss boundaries aligned well with the DTW map (the 4 ha flow initiation worked best).

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• However, these borders straddle DTW classes depending on actual soil moisture conditions.

• Of all the moss species, Sphagnum moss showed the strongest correlation with DTW.

Sphagnum moss

Acknowledgements

• Dr. Paul A. Arp, University of New Brunswick

• Jae Ogilvie, University of New Brunswick

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Questions or Comments?