Species Composition at the Sub-meter Level in Discontinuous Permafrost in Subarctic, Sweden

Authors: Samantha Anderson 1 Michael W Palace 1, Michael Layne 2, Ruth K Varner 1, Patrick M Crill 3

Institute for the Study of Earth, Ocean and Space, Earth System Research Center, University of New Hampshire, Durham, NH, USA.Division of Science and Environmental Policy, California State University: Monterey Bay, Marina, CA, USA.

Department of Geological Sciences , University of Stockholm, Stockholm, Sweden.

Introduction Northern latitudes are experiencing rapid warming. Wetlands underlain by permafrost are particularly vulnerable to warming which result sin changes in vegetative cover. Species composition including diversity and richness has been associated with greenhouse gas emissions therefore knowledge of species composition allows for the analysis of systematic change and quantification of emissions. Species composition varies on the sub-meter scale based on topography and other microsite parameters. This complexity and the understanding of vegetation on the landscape level proves vital in our estimation of carbon dioxide (CO2) and methane CH4) emissions and changes in these emissions over time.

Research Questions• What is the species composition at the sub-meter scale

using remote sensing? • Will the species change according to topography?• Can we predict site type with the species composition?

Methods• Randomly selected 25 plots that were representative of five major

cover types: Semi-wet, wet, hummock, tall graminoid, and tall shrub.

• Used 1x1m quadrat with 64 subplots to measure percent cover for 26 species.

• We collected ground based remote sensing (RS )at each plot to determine species composition using an ADC lite(near infrared, red, green) and GoPro (red, blue, green)

• Normalized each image based on a Teflon white chip placed in each image. Textural analysis was conducted on each image for entropy, angular second momentum, and lacunarity.

• A logistic regression was developed to examine vegetation cover types and remote sensing parameters. We used a multiple linear regression using forwards stepwise variable selection.

Results

Conclusions• In most cases species were found to be important according to site type. Tall shrub and hummock were significantly different at an alpha level of 0.05 due to the hydrology. Semi wet, wet and tall graminoid had similar species and site characteristics.

• Topography determined which species were established across the mire.

Acknowledgements: I would like to thank the Macro-systems grand for funding my research, it would not have been possible for me to achieve my goals without them. I also would like to thank my advisor Ruth Varner and mentor Michael Palace for guiding and supporting me throughout this project. I would like to thank the Macro-systems grand for funding my research, it would not have been possible for me to achieve my

goals without them. A special thanks to my partner in crime Michael Layne who was there through think and thin, I will be forever grateful.

(Photos by: Samantha Anderson. 1: Empetrum nigrum (crowberry) 2. Andromeda polfolia (bog rosemary))

Field Site • Stordalen mire in Abisko, Sweden (N 68⁰ 21’.182” E 19⁰ 2’.800”)• Average temperature: 12⁰C • Situated on the most marginal of the

discontinuous permafrost zones.

Photo by: Haley Dunleavy

Photo: http://www.lib.utexas.edu/maps/europe/sweden

5 Site Types

1 2

Wet SiteSpecies richness: 4

Semi-wetSpecies richness: 5

Tall GraminoidSpecies richness: 4

Hummock Species richness: 8

Tall ShrubSpecies richness: 9

Vegetation Parameters

Remote Sensing Parameters

We ran a Tukey tests to determine if a species would be influenced by site type. Figure 1.

• Rubus chamemorus (Cloudberry) and Empetrum nigrum (Crowberry) were found to be statistically significant in the tall shrub and hummock sites compared to the “wetter” sites.

Lacunarity, angular second momentum and entropy were three factors that we measured. Lacunarity measures spatial patterns and indicates gap size. The bigger the gaps the greater lacunarity. Entropy measures the number of ways a system can be arranged.

• Hummocks are ombrotrophic where as the hollows are minerotrophic

• Betula nana (Dwarf Birch) and Carex were on the opposite sides of the spectrum were Betula nana was prevalent in the tall shrub areas where as Carex was in the tall graminoid areas.

Species R^2 Prob>ChiSqVaccinium vitis-idaea (Lingonberry) 0.51 <.0001Empetrum nigrum (Crowberry) 0.57 <.0001Eriophorum vaginatum 0.22 0.0006Sphagnum 0.73 <.0001Carex 0.54 <.0001Betula nana (Dwarf Birch) 0.52 <.0001Andromeda polifolia (Bog Rosemary) 0.41 <.0001Rubus chamemorus (Cloudberry) 0.77 <.0001

Site Type Parameters

(Sphagnum was the base layer that covered the mire but it was found that it was significant in the semi wet sites and relative in the others.)

Can we predict site type with species?

(Multiple regression analysis determining species through site type. )

Table 1.

Species Intercept entropy_incell entropy_whole eveness_incell eveness_whole asm_incell asm_whole FD TIEmpetrum nigrum (Crowberry) 4.137 -2.185Eriophorum vaginatum -0.269 0.066Sphagnum 75.388 -90.408 7.698Salix lapponum (Downy Willow) -0.144 -1.255 7.146Betula nana (Dwarf Birch) 1.475 -1.169 8.928 2.404 -2.238 5.37E-02 Andromeda polifolia (Bog Rosemary) 5.222 -5Rubus chamemorus (Cloudberry) 11.280 -5.261 -6.409 0.127p>0.05, p>0.05, p>0.01

Remote Sensing Parameters

Can remote sensing predict site type ?Table 2a.

(Forward stepwise regression estimates.)

Parameter p-value r^2 RMSEEmpetrum nigrum (Crowberry) 0.0003 0.23 0.097Eriophorum vaginatum 0.0013 0.20 0.125Sphagnum <.0001 0.59 0.185Salix lapponum (Downy Willow) <.0001 0.33 0.058Betula nana (Dwarf Birch) <.0001 0.48 0.046 Andromeda polifolia (Bog Rosemary) 0.0015 0.19 0.025Rubus chamemorus (Cloudberry) <.0001 0.47 0.067

Table 2b.

Forward stepwise regression results

• Although the r2 values were low the p-values made the relationship significant at the level of <0.001.