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：本数据集于2017年8月采用无人飞行器摄影测量技术开展地形勘测。我们使用三款无人飞行器（Unoccupied Aerial Vehicle, UAV）平台，以3厘米的精细空间分辨率采集RGB多光谱数据：分别为DJI Phantom 4 Pro、Advanced型号（多旋翼机型）与Phantom FX-61型号（固定翼机型）；并参照Cunliffe等人（2019a、2019b）的研究方法，借助多视图立体运动恢复结构（structure from motion with multiview stereopsis）技术，生成空间分辨率为10厘米的精细数字地表模型（Digital Surface Model, DSM）与正射影像图（orthomosaic）。

thermsum.tif：本数据集基于R语言中的microclima包（Kearney等，2020；Maclean等，2019），以1米的空间粒度模拟地表气温。我们利用前述高分辨率数字地表模型（DSM），针对2017年7月13日至8月9日的茶袋埋置实验周期内的研究区每日平均地表温度开展建模。该微气候模型整合了来自RCNEP网格全球数据集的局地每日气候、辐射、云量与海岸暴露度数据（Kemp等，2012）。我们将该建模流程生成的28个TIF文件进行求和，得到28天热积温变量——该指标可表征整个实验期间地表的整体受热情况。

引用文献：
1. Cunliffe, A., I. Myers-Smith, J. Kerby及W. Palmer（2019a）：《加拿大育空地区Qikiqtaruk——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（NERC）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及I. Myers-Smith（2019b）：《利用航空无人机摄影测量观测到的多年冻土海岸线快速退缩》，《冰冻圈（The Cryosphere）》，13(5):1513-1528，DOI: 10.5194/tc-13-1513-2019。
3. Maclean, I. M.（2020）：《高时空分辨率下的未来气候预测》，《全球变化生物学（Global Change Biology）》，26(2):1003–1011。
4. Kearney, M. R., Gillingham, P. K., Bramer, I., Duffy, J. P.及Maclean, I. M.（2020）：《全球任意区域逐小时历史地形校正微气候的计算方法》，《生态学与进化方法（Methods in Ecology and Evolution）》，11(1):38-43。
5. Kemp, M. U., Van Loon, E. E., Shamoun-Baranes, J.及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（Methods in Ecology & Evolution）》，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，该碳库极易发生加速分解。目前我们对苔原生态系统中凋落物分解的景观尺度调控机制知之甚少，这阻碍了我们对全球碳循环的理解。
本研究针对加拿大育空地区Qikiqtaruk——赫歇尔岛的异质性苔原景观，探究了局地尺度的地形、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，并将其与包括基于无人机地形数据模拟得到的高分辨率微气候数据所生成的热积温地表温度数据在内的环境梯度进行对比分析。
研究发现，苔原景观中更湿润、更温暖的区域的绿茶凋落物质量损失量更大，分解速率更快；而在多年冻土活动层更厚的区域，该现象则相对较弱。
空间异质性的地下条件（土壤湿度与活动层厚度）相比地表气温，能更好地解释景观尺度（>10米）下的分解指标变异。
令人意外的是，海拔与坡度并未对凋落物分解产生显著调控作用。我们还发现，在湿润而非温暖的微生境中，北坡的分解速率高于南坡。