6411321
doi
10.5281/zenodo.6411321
oai:zenodo.org:6411321
Isla Myers-Smith
University of Edinburgh
Gergana Daskalova
University of Edinburgh
Jeffrey Kerby
Aarhus University
Haydn Thomas
University of Edinburgh
Andrew Cunliffe
University of Exeter
Litter decomposition is moderated by scale-dependent microenvironmental variation in tundra ecosystems
Elise Gallois
University of Edinburgh
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
dsm
microclimate
microclima
thermal sum
decomposition
<p><strong>QHI_crop.tiff </strong>= We carried out topographic surveys using unoccupied aerial vehicles photogrammetry in August 2017. We used three UAV platforms to collect RGB multispectral data at a fine (3 cm) spatial resolution: DJI Phantom 4 Pro and Advanced (multicopter), and Phantom FX-61 (fixed wing), and used used structure from motion with multiview steriopsis to obtain a fine-grain 10 cm spatial resolution digital surface model and orthomosaic as described in Cunliffe et al. (2019a, 2019b).</p>
<p><strong>thermsum.tif </strong>= We used the microclima package in R (Kearney et al., 2020; Maclean et al., 2019) to model surface air temperature at a 1-m spatial grain. Using our fine resolution DSM, we modelled mean surface temperatures at the study site for each day spanning the teabag burial period of 13th July to 9th August 2017. The microclima model incorporates local daily climate, radiation, cloud cover and coastal exposure data from gridded global datasets derived from RCNEP (<a href="https://www.zotero.org/google-docs/?broken=Zl6wgI">Kemp et al., 2012)</a>. We summed the 28 TIF files produced through this modelling technique to produce a 28-day thermal sum variable - a metric which captures the overall heating of the ground surface over the course of the experiment.</p>
<p><strong>Cited Works:</strong></p>
<p> </p>
<p>Cunliffe, A., I. Myers-Smith. J. Kerby and W. Palmer (2019a). Orthomosaic of permafrost landscape on Qikiqtaruk – Herschel Island, Yukon, Canada: August 2017. NERC Polar Data Centre. DOI:10.5285/29bf1c9f-a39a-452c-b9f9-de35d9fb9179.</p>
<p> </p>
<p>Cunliffe, A., G. Tanski, B. Radosavljevic, W. Palmer, T. Sachs, H. Lantuit, J. Kerby, and I. Myers-Smith (2019b) Rapid retreat of permafrost coastline observed with aerial drone photogrammetry. The Cryosphere 13(5):1513-1528. DOI: 10.5194/tc-13-1513-2019.</p>
<p> </p>
<p><a href="https://www.zotero.org/google-docs/?hjdBYY">Maclean, I. M. (2020). Predicting future climate at high spatial and temporal resolution. <em>Global Change Biology</em>, <em>26</em>(2), 1003–1011.</a></p>
<p> </p>
<p>Kearney, M. R., Gillingham, P. K., Bramer, I., Duffy, J. P., & Maclean, I. M. (2020). A method for computing hourly, historical, terrainâcorrected microclimate anywhere on Earth. <em>Methods in Ecology and Evolution</em>, <em>11</em>(1), 38-43.</p>
<p> </p>
<p>Kemp, M. U., Van Loon, E. E., Shamoun-Baranes, J., & Bouten, W. (2012). RNCEP: global weather and climate data at your fingertips. <em>Methods in Ecology & Evolution</em>, <em>3</em>(1), 65-70.</p>
<p><strong>Paper Abstract:</strong></p>
<ol>
<li>
<p><strong>The Arctic tundra is one of the world’s largest organic carbon stores, yet this carbon is vulnerable to accelerated decomposition as climate warming progresses. We currently know very little about landscape-scale controls of litter decomposition in tundra ecosystems, which hinders our understanding of the global carbon cycle. </strong></p>
</li>
<li>
<p><strong>Here, we examined how local-scale topography, surface air temperature, soil moisture and permafrost conditions influenced litter decomposition rates across a heterogeneous tundra landscape on Qikiqtaruk - Herschel Island (Yukon, Canada).</strong></p>
</li>
<li>
<p><strong>We used the Tea Bag Index protocol to derive decomposition metrics which we then compared across environmental gradients, including thermal sum surface temperature data derived from fine-resolution microclimate data modelled from drone derived topographic data.</strong></p>
</li>
<li>
<p><strong>We found greater green tea litter mass loss and faster decomposition rates in wetter and warmer areas within the landscape, and to a lesser extent in areas with deeper permafrost active layer thickness.</strong></p>
</li>
<li>
<p><strong>Spatially heterogeneous belowground conditions (soil moisture and active layer depth) explained variation in decomposition metrics at the landscape-scale (> 10 m) better than surface temperature.</strong></p>
</li>
<li>
<p><strong>Surprisingly, there was no strong control of elevation or slope of litter decomposition. We also found higher decomposition rates on North-facing relative to South-facing aspects at microsites that were wetter rather than warmer.</strong></p>
</li>
</ol>
Zenodo
2022-04-14
info:eu-repo/semantics/other
6411320
award_title=E4: Edinburgh Earth, Ecology and Environment Doctoral Training Partnership; award_number=NE/S007407/1; funder_id=001aqnf71; funder_name=UK Research and Innovation;
1686653606.568045
1478682236
md5:143537ef32323b4960f1b212b1fdfd6f
https://zenodo.org/records/6411321/files/qhi_crop.tiff
3094154
md5:9ddc97d506c85221838a12637ffb8a32
https://zenodo.org/records/6411321/files/thermsum.tif
public
10.5281/zenodo.6411320
isVersionOf
doi