A chironomid-based salinity inference model from lakes on the Tibetan Plateau

Previous studies have shown chironomids to be excellent indicators of environmental change and training sets have been developed in order to allow these changes to be reconstructed quantitatively from subfossil sequences. Here we present the results of an investigation into the relationships between surface sediment subfossil chironomid distribution and lake environmental variables from 42 lakes on the Tibetan Plateau. Canonical correspondence analysis (CCA) revealed that of the 11 measured environmental variables, salinity (measured as total dissolved solids TDS) was most important, accounting for 10.5% of the variance in the chironomid data. This variable was significant enough to allow the development of quantitative inference models. A range of TDS inference models were developed using Weighted Averaging (WA), Partial Least Squares (PLS), Weighted Averaging–Partial Least Squares (WA–PLS), Maximum Likelihood (ML), Modern Analogues Technique (MAT) and Modern Analogues Techniques weighted by similarity (WMAT). Evaluation of the site data indicated that four lakes were major outliers, and after omitting these from the training set the models produced jack-knifed coefficients of determination (r ²) between 0.60 and 0.80, and root-mean-squared errors of prediction (RMSEP) between 0.29 and 0.44 log₁₀ TDS. The best performing model was the two-component WA–PLS model with r ² _jack = 0.80 and RMSEP_jack = 0.29 log₁₀ TDS. The model results were similar to other chironomid-salinity models developed in different regions, and they also showed similar ecological groupings along the salinity gradient with respect to freshwater/salinity thresholds and community diversity. These results therefore indicate that similar processes may be controlling chironomid distribution across salinity gradients irrespective of biogeographical constraints. The performance of the transfer functions illustrates that chironomid assemblages from the Tibetan Plateau lakes are clearly sensitive indicators of salinity. The models will therefore allow the quantification of long-term records of past water salinity for lacustrine sites across the Tibetan Plateau, which has important implications for future hydrological research in the region.     

Chrysophyte cyst relationships to water chemistry in Pyrenean lakes (NE Spain) and their potential for environmental reconstruction

Chrysophyte cysts were identified from the surface sediment of 105 mountain lakes in the Pyrenees (NE Spain), and their statistical relationship to water chemistry was examined using canonical correspondence analysis (CCA). The chemical parameters that explained significant and independent amounts of variability were alkalinity, pH, potassium, nitrate and magnesium. In a CCA using these parameters, the first canonical axis was related to a gradient of alkalinity and pH, which reflected the varying nature of the watershed bedrock in the Pyrenees, while the second axis was correlated with potassium (negatively) and nitrate (positively). The potential for environmental reconstructions of the five chemical parameters was further studied by: (i) analyzing the distribution of optima and tolerances calculated by weighted-averaging (WA); (ii) carrying out detrended canonical correspondence analysis (DCCA) with a single environmental variable; and (iii) examining the performance of WA-PLS transfer functions. Acceptable transfer functions were obtained for alkalinity, pH and nitrate. However, for potassium and magnesium the tolerance of cysts was too broad and the distribution of optima too skewed, respectively. The possibility of reconstructing nitrogen-related issues using chrysophyte cysts is particularly interesting because of the lack of direct chemical records of nitrogen compounds in sediments. Nitrate reconstructions using transfer functions may be complemented by a holistic reconstruction using partial CCA, where, after subtracting the effects of other chemicals, samples are ordered on a plain defined by potassium and nitrate. This ordination could show down-core trends in lake productivity and renewal time.     

Diatom assemblages from Adirondack lakes (New York,USA) and the development of inference models for retrospective environmental assessment

Detrended canonical coreespondence analysis (DCCA) was used to examine the relationships between diatom species distributions and environmental variables from 62 drainage lakes in the Adirondack region, New York (USA). The contribution of lakewater pH, Al_m (monomeric Al), NH₄, maximum depth, Mg, and DOC (dissolved organic carbon) were statistically significant in explaining the patterns of variation in the diatom species composition. Twenty-three and sixteen diatom taxa were identified as potential indicator species for pH and Al_m, respectively (i.e. a taxon with a strong statistical relationship to the environmental variable of interest, a well defined optimum, and a narrow tolerance to the variable of interest). Using weighted-averaging regression and calibration, predictive models were developed to infer lakewater pH (r ²=0.91), Al_m (r ²=0.83), DOC (dissolved organic carbon) (r ²=0.64), and ANC (acid neutralizing capacity; r ²=0.90). These variables are of key importance in understanding watershed acidification processes. These predictive models have been used in the PIRLA-II (Paleoecological Investigation of Recent Lake Acidification-II) project to answer policy-related questions concerning acidification, recovery, and fisheries loss.     

Interdecadal correlation of solar activity with Tibetan Plateau snow depth and winter atmospheric circulation in East Asia

Studies on the impact of solar activity on climate system are very important in understanding global climate change. Previous studies in this field were mostly focus on temperature, wind and geopotential height. In this paper, interdecadal correlations of solar activity with Winter Snow Depth Index (WSDI) over the Tibetan Plateau, Arctic Oscillation Index (AOI) and the East Asian Winter Monsoon Index (EAWMI) are detected respectively by using Solar Radio Flux (SRF), Total Solar Irradiance (TSI) and Solar Sunspot Number (SSN) data and statistical methods. Arctic Oscillation and East Asian winter monsoon are typical modes of the East Asian atmospheric circulation. Research results show that on interdecadal time scale over 11-year solar cycle, the sun modulated changes of winter snow depth over the Tibetan Plateau and East Asian atmospheric circulation. At the fourth lag year, the correlation coefficient of SRF and snow depth is 0.8013 at 0.05 significance level by Monte-Carlo test method. Our study also shows that winter snow depth over the Tibetan Plateau has significant lead and lag correlations with Arctic Oscillation and the East Asian winter monsoon on long time scale. With more snow in winter, the phase of Arctic Oscillation is positive, and East Asian winter monsoon is weak, while with less snow, the parameters are reversed. An example is the winter of 2012/2013, with decreased Tibetan Plateau snow, phase of Arctic Oscillation was negative, and East Asian winter monsoon was strong.     

青藏高原高寒草地净初级生产力(NPP)时空分异

基于1982-2009 年间的遥感数据和野外台站生态实测数据,利用遥感生产力模型(CASA模型) 估算青藏高原高寒草地植被净初级生产力(NPP),分别从地带属性(自然地带、海拔高程、经纬度)、流域、行政区域(县级) 等方面对其时空变化过程进行分析,阐述了1982 年以来青藏高原高寒草地植被NPP的时空格局与变化特征。结果表明:① 青藏高原高寒草地NPP多年均值的空间分布表现为由东南向西北逐渐递减;1982-2009 年间,青藏高原高寒草地的年均总NPP为177.2×10¹² gC·yr^-1,单位面积年均植被NPP为120.8 gC·m^-2yr^-1;② 研究时段内,青藏高原高寒草地年均NPP 在112.6~129.9 gC·m^-2yr^-1 间,呈波动上升的趋势,增幅为13.3%;NPP 增加的草地占草地总面积的32.56%、减少的占5.55%;③ 青藏高原多数自然地带内的NPP呈增加趋势,仅阿里山地半荒漠、荒漠地带NPP呈轻微减低趋势,其中高寒灌丛草甸地带和草原地带的NPP增长幅度明显大于高寒荒漠地带;年均NPP增加面积比随着海拔升高呈现"升高—稳定—降低"的特点,而降低面积比则呈现"降低—稳定—升高"的特征;④ 各主要流域草地年均植被NPP均呈现增长趋势,其中黄河流域增长趋势显著且增幅最大。植被NPP和盖度及生长季时空变化显示,青藏高原高寒草地生态系统健康状况总体改善局部恶化。