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首页> 外文期刊>Hydrobiologia >Diatom-salinity relationships in wetlands: assessing the influence of salinity variability on the development of inference models
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Diatom-salinity relationships in wetlands: assessing the influence of salinity variability on the development of inference models

机译：湿地中的硅藻盐度关系：评估盐度变异性对推断模型发展的影响

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摘要

Diatoms are among the most widely used indicators of human and climate induced wetland salinity history in the world. This is particularly as a result of the development of diatom-based models for inferring past salinity. These models have primarily been developed from relationships between diatoms and salinity measured at the time of sampling or during the preceding year. Although within site variation in salinity has the potential to reduce the efficacy of such models, its influence has been rarely considered. Hence, diatom-conductivity relationships in eight seasonally monitored wetlands have been investigated. In developing a diatom-conductivity transfer function from these sites, we sought to assess the influence of conductivity variation on diatom inference model performance. Our sites were characterised by variability in conductivity that was not correlated to its range and thus were well suited to an investigation of this type. We found, contrary to expectations, that short-term (seasonal) changes in conductivity which were often dramatic did not result in unduly reduced transfer function performance. By contrast, sites that were more variable in the medium term (5-6 years) tended to have larger model errors. In addition, we identified a secondary ecological gradient in the diatom data which could not be related to any measured variable (including pH, turbidity or nutrient concentrations).
机译：硅藻是人类和气候导致的湿地盐碱化历史上最广泛使用的指标之一。这尤其是由于基于硅藻的模型推断过去盐度的结果。这些模型主要是根据在采样时或前一年中测量的硅藻与盐度之间的关系开发的。尽管盐度在位点内部变化可能会降低此类模型的功效，但很少考虑其影响。因此，已经研究了八个季节性监测湿地中的硅藻电导率关系。在从这些位置开发硅藻电导率传递函数时，我们试图评估电导率变化对硅藻推断模型性能的影响。我们的站点的特点是电导率的变化与其范围无关，因此非常适合对此类型进行研究。与预期相反，我们发现电导率的短期（季节性）变化（通常是剧烈的）并不会导致传递函数性能的过度降低。相比之下，中期（5-6年）中变化更大的站点往往具有更大的模型误差。此外，我们在硅藻数据中确定了一个次级生态梯度，该梯度与任何测量变量（包括pH值，浊度或营养物浓度）均不相关。

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