Subjects: Biology >> Ecology submitted time 2023-07-06
Abstract： The collection, transport and transformation of sediments, nutrients, organic matter, energy and information are key topics in the studies on ecosystem processes. However, there is no systematic literature on watershed information flow (WIF) in watershed ecology. To promote research on the WIF, we proposed the concept of watershed biological information flow (WBIF) by referencing the concept of biological information flow, and defined it as the path, processes and control of biological information transport, exchange, interaction and feedback among different spaces and systems along with watershed ecosystem processes. We proposed that the key of WBIF research should focus on 1) the WBIF between land and river, branch and main stream, upstream and downstream and different patches, 2) the periodical fluctuation and trending drift of the WBIF, and 3) the impacts of geomorphologic, hydrologic situations and human activities on WBIF. We conducted a case study on the WBIF in the Shaliu River basin indicated by the environmental microbes in riverine water and riparian soil using environmental DNA technology. Shaliu River is one of the main inflowing rivers of Qinghai Lake, which has a relative simple watershed ecosystem. In the river, there is a simple aquatic ecosystem with low biodiversity and a migratory fish Gymnocypris przewalskii which migration between river and lake. On the land, there are dominant grassland and limited human activities. To reveal the essential features of WBIF driven by natural runoff, we compared the bacterial community (indicated by operational taxonomic units (OTUs)) from upstream riverine water samples with from downstream riverine water samples and from riverine water samples with from adjacent riparian soil samples. Results showed that (1) the WBIF from soil to water was driven by surface flow and subsurface flow and filtrated by environment change. Its transport efficiency was 62.76% in rainy day and 44.16% in sunny day. Correspondingly, their transport capacity was 68.49% and 56.82%, respectively; their environmental attenuation was 8.38% and 22.38%, respectively. (2) The WBIF from upstream to downstream was driven by river flow and attenuated in transport. Its basic integrated transport efficiency was 97.41% per kilometer, in which the transport capacity was 99.42% per kilometer, the proportion of noneffective WBIF was 43.46%, and half-life distance of noneffective WBIF was 14.52 kilometers. (3) As the transport efficiency of the WBIF was mainly constrained by transport capacity of WBIF, precipitation drove the arising of surface flow, then enhanced the power of erosion and transportation, and finally promoted the increase of WBIF transport capacity and efficiency. (4) The WBIF increased the detectable biodiversity of sink aquatic ecosystem, but the increase of detectable biodiversity is limited rather than accumulated along the river.
Subjects: Biology >> Ecology submitted time 2023-07-06
Abstract： Watershed biological information flow (WBIF) is defined as the path, processes and control of biological information transport, exchange, interaction and feedback among different spaces and systems along with watershed ecosystem processes, and could be partly described as the land-to-river and upstream-to-downstream bioinformation transportation (including organisms, nucleic acids, peptides and other biomarkers), which is driven by the hydrologic processes of watershed systems. The WBIF labels the transport of organic matter and energy. The WBIF integrates the ecological processes of environmental DNA (eDNA), including the origin, state, transport, and fate of eDNA, and makes it possible that the species composition in river system is monitored and assessed using eDNA. The WBIF estimation is the key for watershed ecosystem processes studying and riverine biodiversity monitoring. However, in practice, the parallel samples in each sampling site always are limited. And how parallel samples would impact WBIF estimation is unknown. Based on the principles of sampling survey, we hypothesized that parallel samples would not impact the accuracy of the WBIF estimation, but affect the precision of the WBIF estimation. Then, we transformed this hypothesis into a set of formulas and tested it with a series of analog computation. Results showed that the number of parallel samples (efficiency of detection) affected both the accuracy and precision of the WBIF estimation. The optimal WBIF estimation was less than the actual WBIF in any condition. Along with the increase of parallel samples (efficiency of detection), the optimal WBIF estimation gradually neared to the actual WBIF, the range of WBIF estimation gradually focused on the actual WBIF. In other words, more parallel samples (higher efficiency of detection) led higher accuracy and precision of the WBIF estimation. In addition, the actual WBIF affected both the accuracy and precision of the WBIF estimation too. Larger actual WBIF led higher accuracy and precision of the WBIF estimation. The relative relationship between the number of biological information types in upstream and downstream samples affected both the accuracy and precision of the WBIF estimation too. The accuracy and precision of WBIF estimation would be higher when the number of biological information types in upstream samples was more than those in downstream samples. So, we suggest that in the work of watershed ecosystem processes studying and riverine biodiversity monitoring, the relationship between parallel sample number and detection efficiency should be assessed, the suitable parallel sample number should be estimated based on the reliability target of WBIF estimation, the sampling program should be designed with suitable parallel samples, the WBIF should be estimated based on all parallel samples of each sampling site, at last the estimated results of WBIF should be re-evaluated according to the posterior probability of WBIF in different conditions. The current work provided the framework and methodology reference for the post-evaluation.
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