Litter decomposition is moderated by scale-dependent microenvironmental variation in tundra ecosystems

QHI_crop.tiff = 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). thermsum.tif = 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 (Kemp et al., 2012). 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. Cited Works: 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. 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. Maclean, I. M. (2020). Predicting future climate at high spatial and temporal resolution. Global Change Biology, 26(2), 1003–1011. Kearney, M. R., Gillingham, P. K., Bramer, I., Duffy, J. P., & Maclean, I. M. (2020). A method for computing hourly, historical, terrain‐corrected microclimate anywhere on Earth. Methods in Ecology and Evolution, 11(1), 38-43. Kemp, M. U., Van Loon, E. E., Shamoun-Baranes, J., & Bouten, W. (2012). RNCEP: global weather and climate data at your fingertips. Methods in Ecology & Evolution, 3(1), 65-70. Paper Abstract: 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. 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). 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. 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. 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. 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.

QHI_crop.tiff：我们于2017年8月采用无人飞行器（unoccupied aerial vehicles, UAV）摄影测量法开展地形勘测。使用三款UAV平台采集空间分辨率达3厘米的RGB多光谱数据：大疆（DJI）精灵4 Pro及进阶版（多旋翼机型），以及精灵FX-61（固定翼机型）；并通过多视图立体运动恢复结构（structure from motion with multiview stereopsis）方法获取空间分辨率为10厘米的精细数字表面模型（digital surface model, DSM）和正射影像图（orthomosaic），具体流程详见Cunliffe等人2019a、2019b的研究。
thermsum.tif：我们借助R语言的microclima程序包（Kearney等，2020；Maclean等，2019），以1米的空间粒度模拟地表气温。基于我们获取的高分辨率DSM，对2017年7月13日至8月9日的茶袋埋藏实验期内的每日研究区地表平均温度进行模拟。该microclima模型整合了来自RCNEP（Kemp等，2012）格网化全球数据集的局地每日气候、辐射、云量与海岸暴露度数据。我们将此次模拟生成的28个TIF文件求和，得到28天热累积量（thermal sum）变量——该指标可量化实验期间地表整体受热情况。
引用文献：
1. Cunliffe, A., I. Myers-Smith, J. Kerby & W. Palmer (2019a). 加拿大育空地区奇克塔鲁克岛——赫歇尔岛多年冻土景观正射影像图：2017年8月. 英国自然环境研究委员会极地数据中心. DOI:10.5285/29bf1c9f-a39a-452c-b9f9-de35d9fb9179.
2. Cunliffe, A., G. Tanski, B. Radosavljevic, W. Palmer, T. Sachs, H. Lantuit, J. Kerby & I. Myers-Smith (2019b). 利用航空无人机摄影测量法观测到的多年冻土海岸快速后退. 《冰冻圈》13(5):1513-1528. DOI: 10.5194/tc-13-1513-2019.
3. Maclean, I. M. (2020). 高时空分辨率未来气候预测. 《全球变化生物学》26(2): 1003–1011.
4. Kearney, M. R., Gillingham, P. K., Bramer, I., Duffy, J. P. & Maclean, I. M. (2020). 全球任意区域逐小时历史地形校正微气候计算方法. 《生态学与进化方法》11(1):38-43.
5. Kemp, M. U., Van Loon, E. E., Shamoun-Baranes, J. & Bouten, W. (2012). RNCEP：唾手可得的全球天气与气候数据. 《生态学与进化方法》3(1):65-70.
论文摘要：北极苔原是全球最大的有机碳储库之一，但随着气候变暖加剧，该储库中的碳正面临加速分解释放的风险。目前学界对苔原生态系统中凋落物分解的景观尺度调控机制所知甚少，这阻碍了我们对全球碳循环的理解。本研究以加拿大育空地区奇克塔鲁克岛——赫歇尔岛的异质性苔原景观为研究对象，探究局地地形、地表气温、土壤湿度与多年冻土条件对凋落物分解速率的影响。我们采用茶袋指数（Tea Bag Index）方案获取分解指标，并结合基于无人机地形数据模拟的高分辨率微气候数据得到的热累积量地表温度数据，在环境梯度间对分解指标进行对比分析。结果显示，景观内更湿润、更温暖的区域中绿茶凋落物的质量损失率更高，分解速率更快；而在多年冻土活动层厚度更深的区域，该现象则相对较弱。相较于地表温度，空间异质性的地下条件（土壤湿度与活动层深度）能够更好地解释景观尺度（>10米）下分解指标的变异。令人意外的是，海拔或坡度对凋落物分解并无显著调控作用。此外，在湿润而非温暖的微生境中，北坡的分解速率显著高于南坡。