Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater-surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.
Advances in detection of genetic material from species in aquatic ecosystems, including environmental DNA (eDNA), have improved species monitoring and management. eDNA from target species can readily move in streams and rivers and the goal is to measure it, and with that infer where and how abundant species are, adding great value to delimiting species invasions, monitoring and protecting rare species, and estimating biodiversity. To date, we lack an integrated framework that identifies environmental factors that control eDNA movement in realistic, complex, and heterogeneous flowing waters. To this end, using an empirical approach and a simple conceptual model, we propose a framework of how eDNA is transported, retained, and resuspended in stream systems. Such an understanding of eDNA dispersal in streams will be essential for designing optimized sampling protocols and subsequently estimating biomass or organismal abundance. We also discuss guiding principles for more effective use of eDNA methods, highlighting the necessity of understanding these parameters for use in future predictive modeling of eDNA transport.
While environmental DNA (eDNA) is now being regularly used to detect rare and elusive species, detection in lotic environments comes with a caveat: The species being detected is likely some distance upstream from the point of sampling. Here, we conduct a series of seminatural stream experiments to test the sensitivity of new digital droplet PCR (ddPCR) to detect low concentrations of eDNA in a lotic system, measure the residence time of eDNA compared to a conservative tracer, and we model the transport of eDNA in this system. We found that while ddPCR improves our sensitivity of detection, the residence time and transport of eDNA does not follow the same dynamics as the conservative tracer and necessitates a more stochastic framework for modeling eDNA transport. There was no evidence for differences in the transport of eDNA due to substrate type. The relatively large amount of unexplained variability in eDNA transport reveals the need for uncovering mechanisms and processes by which eDNA is transported downstream leading to species detections, particularly when inferences are to be made in natural systems where eDNA is being used for conservation management.
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