Dissolved organic carbon in streams within a subarctic catchment analysed using a GIS/remote sensing approach

Climate change projections show that temperature and precipitation increases can alter the exchange of greenhouse gases between the atmosphere and high latitude landscapes, including their freshwaters. Dissolved organic carbon (DOC) plays an important role in greenhouse gas emissions, but the impact of catchment productivity on DOC release to subarctic waters remains poorly known, especially at regional scales. We test the hypothesis that increased terrestrial productivity, as indicated by the normalized difference vegetation index (NDVI), generates higher stream DOC concentrations in the Stordalen catchment in subarctic Sweden. Furthermore, we aimed to determine the degree to which other generic catchment properties (elevation, slope) the explain DOC concentration, and whether or not land cover variables representing the local vegetation type (e.g., mire, forest) need to be included to obtain adequate predictive models for DOC delivered into rivers. We show that the land cover type, especially the proportion of mire, played a dominant role in the catchment's release of DOC, while NDVI, slope, and elevation were supporting predictor variables. The NDVI as a single predictor showed weak and inconsistent relationships to DOC concentrations in recipient waters, yet NDVI was a significant positive regulator of DOC in multiple regression models that included land cover variables. Our study illustrates that vegetation type exerts primary control in DOC regulation in Stordalen, while productivity (NDVI) is of secondary importance. Thus, predictive multiple linear regression models for DOC can be utilized combining these different types of explanatory variables.

气候变化预测表明，气温与降水的升高会改变大气与高纬度景观（包括其淡水生态系统）之间的温室气体交换过程。溶解性有机碳（Dissolved Organic Carbon, DOC）在温室气体排放过程中发挥关键作用，但目前学界对集水区生产力向亚寒带水域释放DOC的影响仍知之甚少，在区域尺度上尤为如此。本研究针对瑞典亚寒带地区斯托尔达伦（Stordalen）集水区提出假说：归一化差分植被指数（Normalized Difference Vegetation Index, NDVI）所表征的陆地生产力提升，会导致溪流中DOC浓度升高，并对此展开验证。此外，本研究旨在明确其他通用集水区属性（海拔、坡度）对DOC浓度的解释程度，同时探究是否需要纳入表征本地植被类型的土地覆被变量（如沼泽、森林），才能构建出对河流输入DOC具有良好预测能力的模型。研究结果表明，土地覆被类型（尤其是沼泽占比）在集水区DOC释放过程中占据主导地位，而NDVI、坡度与海拔则作为辅助预测变量。单独以NDVI作为预测变量时，其与受纳水体DOC浓度仅呈现微弱且不一致的相关性；但在纳入土地覆被变量的多元回归模型中，NDVI则是DOC浓度的显著正向调控因子。本研究证实，在斯托尔达伦集水区，植被类型是DOC调控的核心控制因素，而生产力（NDVI）仅处于次要地位。因此，可通过结合上述不同类型的解释变量，构建针对DOC的多元线性回归预测模型。