Department of Natural Resources and Environmental Science, University of Nevada, Reno, Nevada, USA.
Flathead Lake Biological Station, University of Montana, Polson, Montana, USA.
Ecol Lett. 2023 Sep;26(9):1510-1522. doi: 10.1111/ele.14269. Epub 2023 Jun 23.
Directly observing autotrophic biomass at ecologically relevant frequencies is difficult in many ecosystems, hampering our ability to predict productivity through time. Since disturbances can impart distinct reductions in river productivity through time by modifying underlying standing stocks of biomass, mechanistic models fit to productivity time series can infer underlying biomass dynamics. We incorporated biomass dynamics into a river ecosystem productivity model for six rivers to identify disturbance flow thresholds and understand the resilience of primary producers. The magnitude of flood necessary to disturb biomass and thereby reduce ecosystem productivity was consistently lower than the more commonly used disturbance flow threshold of the flood magnitude necessary to mobilize river bed sediment. The estimated daily maximum percent increase in biomass (a proxy for resilience) ranged from 5% to 42% across rivers. Our latent biomass model improves understanding of disturbance thresholds and recovery patterns of autotrophic biomass within river ecosystems.
直接在许多生态系统中观察到具有生态相关性的自养生物量是困难的,这阻碍了我们通过时间预测生产力的能力。由于干扰可以通过改变基础生物量存量来长时间地对河流生产力产生显著的降低,因此拟合到生产力时间序列的机械模型可以推断基础生物量动态。我们将生物量动态纳入了六个河流的河流生态系统生产力模型中,以确定干扰流阈值并了解初级生产者的恢复力。为了干扰生物量并降低生态系统生产力,所需的洪水规模始终低于更常用的用于使河床沉积物移动的干扰流阈值。估计的每日最大生物量增加百分比(恢复力的代理)在河流之间的范围从 5%到 42%不等。我们的潜在生物量模型提高了对河流生态系统中自养生物量的干扰阈值和恢复模式的理解。