Sediment Accumulation Rate (SAR; measured as mm yr⁻¹) and Mass Accumulation Rate (MAR; measured as g cm⁻² yr⁻¹) data were collected from published lake core records that spanned the past ~ 150 years, from approximately 500 sites worldwide. For each lake, key watershed characteristics including watershed size, slope, land use and climate were extracted, with the goal of quantifying the relative importance of these variables as drivers of SAR and MAR. General additive models provided evidence of accelerated global lake sediment infilling rates after AD 1950. Whereas the onset of sedimentation acceleration varied across ecoregions, global lake MAR values were found to have increased ~ threefold on average, since baseline conditions pre-1900 (i.e. μ_baseline = 0.040 ± 0.044 g cm⁻² yr⁻¹ and μ_modern = 0.13 ± 0.22 g cm⁻² yr⁻¹). The significant drivers, identified through Linear Mixed Effect modeling of MAR time series, were watershed population density (log-transformed) and watershed cropland density (log-transformed). Our results highlight important spatial heterogeneity in SAR and MAR among lakes, precluding the use of simple modeling approaches. SAR and MAR were found to be moderately correlated to one another, despite the potential for post-depositional disparities between segments of the sediment cores. We identified organic matter content (loss-on-ignition, LOI) as a significant co-variate that could be used to correct inflated very recent SAR rates. Our empirical analyses suggest that, despite a wide range of natural variability among lakes, both SAR and MAR increased globally and the increases appear to be mainly the result of enhanced watershed activities associated with agriculture and urbanization.

沉积物积累率（SAR；测量为 mm yr ^-1）和质量积累率（MAR；测量为 g cm ^-2  yr ^-1）数据是从过去约 150 年的已发布湖芯记录中收集的，来自大约 500 个站点全世界。对于每个湖泊，提取关键流域特征，包括流域大小、坡度、土地利用和气候，目的是量化这些变量作为 SAR 和 MAR 驱动因素的相对重要性。通用加法模型提供了公元 1950 年之后全球湖泊沉积物填充速率加速的证据。虽然沉积加速的开始因生态区而异，但发现全球湖泊 MAR 值平均增加了约三倍，因为基线条件在 1900 年之前（即 μ_基线 = 0.040 ± 0.044 g cm ^-2  yr ^-1和 μ_现代 = 0.13 ± 0.22 g cm ^-2  yr ^-1）。通过 MAR 时间序列的线性混合效应模型确定的重要驱动因素是流域人口密度（对数转换）和流域农田密度（对数转换）。我们的结果突出了湖泊之间 SAR 和 MAR 的重要空间异质性，排除了简单建模方法的使用。发现 SAR 和 MAR 彼此适度相关，尽管沉积岩心各段之间存在沉积后差异的可能性。我们将有机物含量（烧失量，LOI）确定为一个重要的协变量，可用于校正最近膨胀的 SAR 率。我们的实证分析表明，尽管湖泊之间存在广泛的自然变异，