10 research outputs found
Boosting freshwater fish conservation with high-resolution distribution mapping across a large territory
The lack of high-resolution distribution maps for freshwater species across large extents fundamentally challenges biodiversity conservation worldwide. We devised a simple framework to delineate the distributions of freshwater fishes in a high-resolution drainage map based on stacked species distribution models and expert information. We applied this framework to the entire Chinese freshwater fish fauna (>1600 species) to examine high-resolution biodiversity patterns and reveal potential conflicts between freshwater biodiversity and anthropogenic disturbances. The correlations between spatial patterns of biodiversity facets (species richness, endemicity, and phylogenetic diversity) were all significant (r = 0.43–0.98, p < 0.001). Areas with high values of different biodiversity facets overlapped with anthropogenic disturbances. Existing protected areas (PAs), covering 22% of China's territory, protected 25–29% of fish habitats, 16–23% of species, and 30–31% of priority conservation areas. Moreover, 6–21% of the species were completely unprotected. These results suggest the need for extending the network of PAs to ensure the conservation of China's freshwater fishes and the goods and services they provide. Specifically, middle to low reaches of large rivers and their associated lakes from northeast to southwest China hosted the most diverse species assemblages and thus should be the target of future expansions of the network of PAs. More generally, our framework, which can be used to draw high-resolution freshwater biodiversity maps combining species occurrence data and expert knowledge on species distribution, provides an efficient way to design PAs regardless of the ecosystem, taxonomic group, or region considered.Strategic Priority Research Program of Chinese Academy of Sciences XDB31000000Second Tibetan PlateauScientific Expedition Program 2019QZKK0304, 2019QZKK05010102National Key Research and Devel-opment Program of China 2021YFC3200300103National Natural Science Foundation of China 32070436, 4207744
Convolutional Neural Networks Facilitate River Barrier Detection and Evidence Severe Habitat Fragmentation in the Mekong River Biodiversity Hotspot
Construction of river infrastructure, such as dams and weirs, is a global issue for ecosystem protection due to the fragmentation of river habitat and hydrological alteration it causes. Accurate river barrier databases, increasingly used to determine river fragmentation for ecologically sensitive management, are challenging to generate. This is especially so in large, poorly mapped basins where only large dams tend to be recorded. The Mekong is one of the world's most biodiverse river basins but, like many large rivers, impacts on habitat fragmentation from river infrastructure are poorly documented. To demonstrate a solution to this, and enable more sensitive basin management, we generated a whole‐basin barrier database for the Mekong, by training Convolutional Neural Network (CNN)–based object detection models, the best of which was used to identify 10,561 previously unrecorded barriers. Combining manual revision and merged with the existing barrier database, our new barrier database for the Mekong Basin contains 13,054 barriers. Existing databases for the Lower Mekong documented under ∼3% of the barriers recorded by CNN combined with manual checking. The Nam Chi/Nam Mun region, eastern Thailand, is the most fragmented area within the basin, with a median [95% CI] barrier density of 15.53 [0.00–49.30] per 100 km, and Catchment Area‐based Fragmentation Index value, calculated in an upstream direction, of 1,178.67 [0.00–6,418.46], due to the construction of dams and sluice gates. The CNN‐based object detection framework is effective and potentially can transform our ability to identify river barriers across many large river basins and facilitate ecologically‐sensitive management
Mixing Mechanism of Microfluidic Mixer with Staggered Virtual Electrode Based on Light-Actuated AC Electroosmosis
In this paper, we present a novel microfluidic mixer with staggered virtual electrode based on light-actuated AC electroosmosis (LACE). We solve the coupled system of the flow field described by Navier–Stokes equations, the described electric field by a Laplace equation, and the concentration field described by a convection–diffusion equation via a finite-element method (FEM). Moreover, we study the distribution of the flow, electric, and concentration fields in the microchannel, and reveal the generating mechanism of the rotating vortex on the cross-section of the microchannel and the mixing mechanism of the fluid sample. We also explore the influence of several key geometric parameters such as the length, width, and spacing of the virtual electrode, and the height of the microchannel on mixing performance; the relatively optimal mixer structure is thus obtained. The current micromixer provides a favorable fluid-mixing method based on an optical virtual electrode, and could promote the comprehensive integration of functions in modern microfluidic-analysis systems
A global dataset on species occurrences and functional traits of Schizothoracinae fish
Abstract The Schizothoracinae fish are a natural group of cyprinids widely distributed in rivers and lakes in the Qinghai-Tibetan Plateau (QTP) and adjacent regions. These fish parallelly evolved with the QTP uplift and are thus important for uncovering geological history, the paleoclimatic environment, and the mechanisms of functional adaptation to environmental change. However, a dataset including species occurrences and functional traits, which are essential for resolving the above issues and guiding relevant conservation, remains unavailable. To fill this gap, we systematically compiled a comprehensive dataset on species occurrences and functional traits of Schizothoracinae fish from our long-term field samplings and various sources (e.g., publications and online databases). The dataset includes 7,333 occurrence records and 3,204 records of 32 functional traits covering all the genera and species of Schizothoracinae fish (i.e., 12 genera and 125 species or subspecies). Sampling records spanned over 180 years. This dataset will serve as a valuable resource for future research on the evolution, historical biogeography, responses to environmental change, and conservation of the Schizothoracinae fish
Trends in Diatom Research Since 1991 Based on Topic Modeling
Diatoms are fundamental carbon sources in a wide range of aquatic food webs and have the potential for wide application in addressing environmental change. Understanding the evolution of topics in diatom research will provide a clear and needed guide to strengthen research on diatoms. However, such an overview remains unavailable. In this study, we used Latent Dirichlet Allocation (LDA), a generative model, to identify topics and determine their trends (i.e., cold and hot topics) by analyzing the abstracts of 19,000 publications from the Web of Science that were related to diatoms during 1991-2018. A total of 116 topics were identified from a Bayesian model selection. The hot topics (diversity, environmental indicator, climate change, land use, and water quality) that were identified by LDA indicated that diatoms are increasingly used as indicators to assess water quality and identify modern climate change impacts due to intensive anthropogenic activities. In terms of cold topics (growth rate, culture growth, cell life history, copepod feeding, grazing by microzooplankton, zooplankton predation, and primary productivity) and hot topics (spatial-temporal distribution, morphology, molecular identification, gene expression, and review), we determined that basic studies on diatoms have decreased and that studies tend to be more comprehensive. This study notes that future directions in diatom research will be closely associated with the application of diatoms in environmental management and climate change to cope with environmental challenges, and more comprehensive issues related to diatoms should be considered.</p
Fish Assemblage Responses to a Low-head Dam Removal in the Lancang River
Dam removal is becoming an effective approach for aquatic biodiversity restoration in damming river in order to balance the aquatic ecosystem conservation with large-scale cascade damming. However, the effects of dam removal on fish communities in Asian mountainous rivers, which are dominated by Cypriniformes fishes, are still not well known. To determine whether dam removal on a mountainous river benefit restoration of fish diversity, we investigated the response of fish assemblage to dam removal using a before- after-control-impact design in two tributaries of the Lancang River (dam removal river: the Jidu River, and control river: the Fengdian River). Fish surveys were conducted one year prior to dam removal (2012) and three years (2013-2015) following dam removal. We observed rapidly and notably spatio-temporal changes in fish biodiversity metrics and assemblage structure, occurring in the Jidu River within the first year after dam removal. Overall, fish species richness, density and Shannon-Wiener diversity all increased immediately in above- and below-dam sites, and maintained a stable level in subsequent years, compared to unchanged situation in the control river. All sites in the Jidu River experienced shifts in fish composition after dam removal, with the greatest temporal changes occurred in sites below- and above- the former dam, resulting in a temporal homogenization tendency in the dam removed river. These findings suggest that dam removal can benefit the recovery of habitat conditions and fish community in Asian mountainous rivers, but the results should be further evaluated when apply to other dammed rivers since the dam age, fluvial geomorphology and situation of source populations could all affect the responses of fish assemblages
Boosting freshwater fish conservation with high-resolution distribution mapping across a large territory
Abstract
The lack of high-resolution distribution maps for freshwater species across large scales fundamentally challenges biodiversity conservation worldwide. Here, we propose a simple framework to delineate the distributions of freshwater fishes in a high-resolution drainage map using stacked species distribution models and expert-based information. Applying this framework to the whole Chinese freshwater fish fauna (+1600 species), we produced high-resolution biodiversity patterns and revealed potential conflicts between biodiversity and anthropogenic disturbances. The correlations between spatial patterns of biodiversity facets (species richness, endemicity and phylogenetic diversity) were all significant but idiosyncratic (r = 0.43–0.98, P < 0.001). Areas with high values of different biodiversity facets overlapped with anthropogenic disturbances. Existing protected areas, covering 22% of China’s territory, were shown to protect 25–29% of fish habitats, 16–23% of species, and 30–31% of priority conservation areas. Moreover, 6–21% of the species are still completely unprotected. These results suggest the need for extending the network of protected areas to ensure the conservation of China’s freshwater fish biodiversity and the goods and services it provides to humans. Specifically, middle to low reaches of large rivers and their associated lakes from Northeast to Southwest China host the most diverse species assemblages and should be the target of future expansions of the network of protected areas. More generally, the framework we propose to draw high-resolution biodiversity maps combining species occurrence data and expert knowledge on species distribution provides an efficient way to unlock protected area designs regardless of the ecosystem, taxonomic group or world area considered