Developing a statistical-weighted index of biotic integrity for large-river ecological evaluations

Biogeographical Distribution of River Microbial Communities in Atlantic Catchments

Microbes inhabit virtually all river ecosystems, influencing energy flow and playing a key role in global sustainability and climate change. Yet, there is uncertainty about how various taxonomic groups respond to large-scale factors in river networks. We analysed microbial community richness and composition across six European Atlantic catchments using environmental DNA sequencing. Our findings reveal different drivers for diversity and composition: land use is pivotal for eukaryotes, while climate and geology are crucial for prokaryotes. A strong regional influence shapes these communities, with warmer, drier regions (Portugal and France) differing from cooler, wetter ones (Northern Spain, Ireland and the United Kingdom). These patterns suggest potential indicators for global change, such as taxa resistant to temperature increases and water scarcity, or those sensitive to land use changes.

Assessing the effects of aquaculture on tidal flat ecological status using multi-metrics interaction-based index of biotic integrity (Mt-IBI)

Given tidal flat special environmental conditions and the degree of pollution caused by human activities, there is an urgent need to quantitatively assess their ecological status. Bioindication has become an indispensable part of environmental quality monitoring on account of its sensitivity to environmental disturbance. Thus, this study used bio-indicators to establish a multi-metrics-based index of biotic integrity (Mt-IBI) to evaluate the ecological status of the tidal flats with/without aquaculture through metagenomic sequencing. Four core indexes that were significantly correlated to other indexes with redundancy (p < 0.05), including Escherichia, beta-lactam antibiotic resistance genes, cellulase and xyloglucanases and the keystone species with 21° in the network, were selected after the screening processes. By implementing Mt-IBI in the tidal flats, the ecological health of the sampling sites was categorized into three levels, with Mt-IBI values of 2.01-2.63 (severe level), 2.81-2.93 (moderate level) and 3.23-4.18 (mild level), respectively. Through SEM analysis, water chemical oxygen demand and antibiotics were determined to be the primary controlling factors of the ecological status of tidal flat regions influenced by aquaculture, followed by salinity and total nitrogen. It is worth noting that the alteration of microbial communities impacted ecological status through the mediation of antibiotics. It is hoped that the results of our study will provide a theoretical basis for coastal environment restoration and that the use of Mt-IBI to assess ecosystem status in different aquatic environments will be further popularized in the future.

Improved method for benthic ecosystem health assessment by integrating chemical indexes into multiple biological indicator species-A case study of the Baiyangdian Lake, China

A comprehensive and scientific assessment of benthic ecosystem health is key to the rational selection of endogenous pollution reduction technologies for lakes. However, current assessments are mainly limited to biological indicators and ignore the actual benthic ecosystem situations, such as the impact of eutrophication and heavy metal pollution, which may lead to the one-sidedness of the evaluation results. In this study, taking Baiyangdian Lake, the largest shallow mesotrophic-eutrophic lake in the North China Plain, as an example, the chemical assessment index and biological integrity index were first combined to estimate the biological conditions, nutritional status and heavy metal pollution of lakes. The indicator system incorporated three biological assessments (benthic index of biotic integrity (B-IBI), submerged aquatic vegetation index of biological integrity (SAV-IBI) and microbial index of biological integrity (M-IBI)) and three chemical assessments (dissolved oxygen (DO), comprehensive trophic level index (TLI) and index of geoaccumulation (I_geo)). Twenty-three attributes of B-IBI, fourteen attributes of SAV-IBI and twelve attributes of M-IBI were screened by range, responsiveness, and redundancy tests to keep the core metrics that were significantly correlated with disturbance gradients or showed strong discriminatory power between reference and impaired sites. The assessment results of B-IBI, SAV-IBI, and M-IBI showed significant differences in the response to anthropogenic activities and seasonal change, among which the submerged plants showed more significant seasonal differences. It is difficult to reach a comprehensive conclusion regarding the benthic ecosystem health status based on a single biological community. In comparison with biological indicators, the score of chemical indicators is relatively low. DO, TLI and I_geo provide an essential supplement for the benthic ecosystem health assessment of lakes with eutrophication and heavy metal pollution problems. Using the new integrated assessment method, the benthic ecosystem health of Baiyangdian Lake was rated as fair, especially the northern parts of the lake adjacent to the inflow mouth of the Fu River, which were in poor condition, indicating that the lake has experienced anthropogenic disturbance, resulting in eutrophication, heavy metal pollution and biological community degradation. Whether it's spring or summer, the integrated assessment method provides a more plausible and comprehensive view of benthic ecosystem health under the pressure of increasing human activities and changing habitat and hydrological conditions, overcoming the narrow perspective and uncertainties of the single-index method. Thus, it can assist lake managers in providing technical support for ecological indication and restoration.

Integration of ABC curve, three dimensions of alpha diversity indices, and spatial patterns of fish assemblages into the health assessment of the Chishui River basin, China

Index of biotic integrity (IBI) based on fish has been applied globally. However, few have considered that fish assemblages change among different aggregate ecoregions when conducted their health assessment. Indeed, some comprehensive indices, such as functional and phylogenetic diversity indices and ABC curve, can be used to identify aspects that are not captured by traditional metrics. Consequently, we try to integrate comprehensive indices and spatial patterns of fish assemblages to develop IBI systems and then verified their effectiveness and accuracy for assessing the environmental health of the Chishui River basin. The comprehensive disturbance index (CDI), based on 11 water quality parameters and 4 human land use, was set to distinguish reference sites and impaired sites. According to the spatial patterns of fish assemblages, the 40 sites were finally divided into 2 aggregate ecoregions, include wadeable streams and nonwadeable rivers. 97 candidate metrics were selected to develop our IBI systems based on the systematic screening method. The result also showed that our IBI systems performed well in discriminating anthropogenic disturbances at both aggregate ecoregions, which suggests that our systems could provide a reliable evaluation. The mean IBI score of the Chishui River basin was 72.09 ± 16.58, and was classified as good status. However, S1 (Chishuiyuan Town), Baisha River, Tongzi River, and Xishui River were disturbed by various human activities. We conclude that the spatial patterns of fish assemblages should be combined with more comprehensive indices to assess river health. On the other hand, we do believe that the process of developing and verifying our IBI systems could be regarded as a reference for biomonitoring in more mountain river systems.

Analysis on the Development of Digital Economy in Guangdong Province Based on Improved Entropy Method and Multivariate Statistical Analysis

The lack of adequate indicators in the research of digital economy may lead to the shortage of data support on decision making for governments. To solve this problem, first we establish a digital economy indicator evaluation system by dividing the digital economy into four types: "basic type", "technology type", "integration type" and "service type" and select 5 indicators for each type. On this basis, the weight of each indicator is calculated to find the deficiencies in the development of some digital economic fields by the improved entropy method. By drawing on the empowerment idea of Analytic Hierarchy Process, the improved entropy method firstly compares the difference coefficient of indicators in pairs and maps the comparison results to the scales 1-9. Then, the judgment matrix is constructed based on the information entropy, which can solve as much as possible the problem that the difference among the weight of each indicator is too large in traditional entropy method. The results indicate that: the development of digital economy in Guangdong Province was relatively balanced from 2015 to 2018 and will be better in the future while the development of rural e-commerce in Guangdong Province is relatively backward, and there is an obvious digital gap between urban and rural areas. Next we extract two new variables respectively to replace the 20 indicators we select through principal component analysis and factor analysis methods in multivariate statistical analysis, which can retain the original information to the greatest extent and provide convenience for further research in the future. Finally, we and provide constructive comments of digital economy in Guangdong Province from 2015 to 2018.