Supplemental Data Files for "Benthic Biofilm Controls on Fine Particle Dynamics in Streams". Water Resources Research

Benthic (streambed) biofilms metabolize a substantial fraction of particulate
organic matter and nutrient inputs to streams. These microbial communities
comprise a significant proportion of overall biomass in headwater streams, and
they present a primary control on the transformation and export of labile
organic carbon. Biofilm growth has been linked to enhanced fine particle
deposition and retention, a feedback that confers a distinct advantage for the
acquisition and utilization of energy sources. We quantified the influence of
biofilm structure on fine particle deposition and resuspension in experimental
stream mesocosms. Biofilms were grown in identical 3-m recirculating flumes
over periods of 18-47 days to obtain a range of biofilm characteristics.
Fluorescent, 8-mm particles were introduced to each flume, and their concentrations in
the water column were monitored over a 30-minute period. We measured particle
concentrations using a flow cytometer and mesoscale (10 μm to 1 cm) biofilm
structure using optical coherence tomography. Particle deposition-resuspension
dynamics were determined by fitting results to a stochastic mobile-immobile
model, which showed retention timescales for particles within the
biofilm-covered streambeds followed a power-law residence time distribution. Particle
retention timescales increased with biofilm areal coverage, biofilm roughness,
and mean biofilm height.  Our findings suggest that biofilm structural parameters are key predictors
of particle retention in streams and rivers.

底栖（河床）生物膜可代谢溪流输入的绝大部分颗粒有机质与营养盐。这类微生物群落在源头溪流的总生物量中占据可观比例，同时是调控活性有机质转化与输出的核心驱动因子。生物膜的生长与细颗粒沉积、滞留能力的提升存在显著关联，这一反馈过程为能量源的获取与利用赋予了独特优势。本研究在实验溪流中宇宙系统中，量化了生物膜结构对细颗粒沉积与再悬浮过程的影响。研究中，我们在规格统一的3米长循环水槽中培养生物膜，培养时长为18至47天，以此获得一系列不同的生物膜特征参数。我们向每个水槽投放荧光标记的8毫米颗粒，并在30分钟内持续监测水柱中的颗粒浓度；通过流式细胞仪（flow cytometer）测定颗粒浓度，利用光学相干断层扫描（optical coherence tomography）测量中尺度（10微米至1厘米）的生物膜结构。我们通过将实验结果拟合至随机移动-固定模型（stochastic mobile-immobile model），解析了颗粒沉积-再悬浮动力学过程；模型结果显示，覆盖生物膜的河床内颗粒的滞留时间尺度遵循幂律滞留时间分布。颗粒滞留时间尺度随生物膜面积覆盖率、生物膜粗糙度以及平均生物膜高度的增加而升高。本研究结果表明，生物膜结构参数是溪流与河流中颗粒滞留情况的关键预测因子。