Human Activities Research Articles

Assessing the spatiotemporal dynamics of water and carbon fluxes in subtropical forest of Xin’an River Basin using an improved Biome-BGC model

Extreme climate occurred frequently in subtropical region, which seriously affects carbon and water fluxes such as evapotranspiration (ET) and gross primary productivity (GPP) of terrestrial ecosystems. The process-based biome biogeochemical cycles (Biome-BGC) model is widely used for simulating carbon and water fluxes of forest ecosystems. However, the lack of the interaction information of climate, vegetation and soil, such as the hysteresis effect, canopy stratification on photosynthesis, impedes better simulations of the ecohydrological processes. Here, we tended to improve the simulation accuracy of Biome-BGC model at a subtropical forest on the Xin’an River in Southeastern China by reconstructing the precipitation series, modifying the ET and canopy multilayers modules, and optimizing the parameters. The spatiotemporal patterns of GPP, ET, water use efficiency (WUE) and their response to environmental factors across the Xin’an River Basin from 1982 to 2018 were further explored. The results showed that the improved model performed well, with the determination coefficient, root means square error and mean absolute error being 0.730, 1.522 gC/m2/d and 1.218 gC/m2/d for GPP, 0.857, 1.082 mm/d and 0.838 mm/d for ET, respectively. Basin-averaged GPP, ET and WUE increased during 1982-2018 and these increasing trends were more pronounced during 1999-2018. Significant positive trends of WUE occurred in the northeast corner. The increasing air temperature and precipitation respectively dominated the increase in GPP and ET, the increasing CO2 concentration and NDVI mitigated the negative effect of extreme precipitation on WUE. Given that human activities such as afforestation have effectively reduced the extent of damage to forest ecosystems from extreme precipitation, we highlight an urgent need to formulate adaptation strategies aimed at reducing the risk of extreme climate in humid regions.

Flavopiridol-loaded lubricative microspheres for osteoarthritis treatment in rabbit

Osteoarthritis considerably affects the daily activities of humans and pets. Medication is an effective treatment option for osteoarthritis. However, commonly used medications require frequent injections or oral administration, which may cause side effects such as gastrointestinal reactions, drug overdose, and missed doses. In this study, we developed lubricative drug-releasing microspheres based on poly(lactic-co-glycolic acid) (PLGA), for the treatment of osteoarthritis. PLGA microspheres formed using microfluidic electronic technology have uniform spherical morphology, sufficient biocompatibility, and excellent drug-release performance. Animal experiments in rabbits have shown that flavopiridol-loaded PLGA is an effective drug carrier for osteoarthritis treatment, since it promotes glycosaminoglycan deposition. Therefore, our flavopiridol-loaded lubricating microspheres is anticipated to exhibit considerable potential for osteoarthritis treatment in humans and pets.

What are the dominant drivers and optimal thresholds for a healthy ecosystem in the Yellow River Basin, China? from a perspective of nonlinear nexus

Identifying the dominant factors influencing ecosystem health and their optimal thresholds is essential for the management and restoration of ecosystems. Most of the works, however, have less detected the importance level of individual factors, especially their changes over time and scale, and rarely determined their threshold effects on ecosystem health (EH), which seriously hinders the formulation of targeted policies for sustainable ecosystem management. To address these research gaps, we present an innovative visualization approach to reveal importance changes in natural and anthropogenic variables and their nonlinear coupling process with EH in the China’s Yellow River Basin (YRB) in the last two decades. Results show that (i) Although the EH in the YRB has improved slightly in the past 20 years, it is still not optimistic and shows distinct spatial heterogeneity. (ii) The impact of human activities on the ecosystem health of the YRB has increased and increasingly plays a decisive role, while that of the natural aspect has decreased recently. Specifically, environmental factors (slope, NDVI, and annual temperature) are the dominant factors affecting the upstream EH. Midstream EH is significantly affected by the synergistic effect of natural and anthropogenic factors, but the importance of the proportion of built-up land is intensified (ranked from 8th to 4th). Anthropogenic factors exert the greatest influence on downstream EH variation, especially for population density whose importance order rising from 7th to 2nd. (iii) By illustrating the nonlinear response curves of EH at multi-scale, the tipping point caused ecosystem deterioration in the YRB is explored and the optimal thresholds of leading factors oriented towards the most effective ecosystem conservation goal are obtained. These results help precisely identify the current health status of YRB's ecosystem, as well as providing a valuable reference for moderate restoration standards and sustainable ecosystem management.

The Application of Microbially Induced Calcium Carbonate Precipitation (MICP) Technology in Building Materials and its Contribution to Waste Resource Utilization

Abstract: In many countries around the world, waste generation has become an increasingly pressing issue, particularly in urban areas experiencing rapid population growth and industrialization. The volume of waste produced by human activities continues to rise, posing significant challenges to the environment, economy, and public health. Improper waste management can lead to air and water pollution, soil degradation, and the spread of diseases. Additionally, waste generation consumes substantial natural resources and energy, exacerbating resource depletion and contributing to greenhouse gas emissions.To address these challenges, sustainable waste management practices are essential to reduce waste generation and promote resource recovery and recycling. In this context, the development of innovative technologies, such as Microbially Induced Calcium Carbonate Precipitation (MICP) in building materials, offers an effective means of converting waste into valuable and sustainable applications. MICP is an environmentally friendly biogeochemical technique that employs microorganisms and chemical agents in biological processes to produce carbonate minerals, providing an energy-efficient, cost-effective, and sustainable solution to environmental and engineering challenges.Recent research indicates that waste streams can substitute for several MICP chemical components in microbial and cementitious agent growth media. MICP technology has been found not only to be effective in handling hazardous waste streams but also to be a cost-effective and sustainable solution applicable to various waste media. This comprehensive review aims to provide insights into the environmental advantages and engineering applications of MICP technology, with a particular focus on the potential contributions of waste streams. It also offers guidance for researchers on identifying and overcoming challenges associated with using waste streams for MICP technology applications.

1#, 1#*, 1, Ebele Benedeth Onuigbo1*, Anthony Anthony Attama2

Salmonella is ubiquitous bacteria commonly found in the water, animals, humans, and the environment. The transmission is facilitated by human activities, including the irrigation of farm products using contaminated surface water, and is a public health concern. This study was carried out to assess Salmonella contamination in the Ekulu River in the Enugu metropolis and determine their susceptibility to some selected relevant antibiotics. Water samples were collected randomly in the region and processed for isolation and identification of Salmonella spp using the direct plating method. The antimicrobial susceptibility tests of the isolates against ciprofloxacin (5 μg), chloramphenicol (30 μg), amoxicillin (10 μg), and streptomycin (10 μg) were done using the disc-diffusion method. Twenty-six (26) (100 %) of the isolates were resistant to amoxicillin antibiotics, and 42.31 %, 23.07 %, and 46.15 % were resistant to ciprofloxacin, chloramphenicol, and streptomycin, respectively. This study shows the importance of establishing adequate measures to control contamination of surface water used for domestic activities in the Emene community Enugu metropolis. Improved water quality increases health and reduces the transmission of diseases/infections.

Integrating street view imagery and taxi trajectory for identifying urban function of street space

ABSTRACT Street space is a crucial component of public space, serving as a site for a variety of human activities. However, prior studies have primarily focused on the traffic function of street space, neglecting other functional types, such as residential and commercial. To address this gap, this study proposes a classification method for street space by integrating taxi trajectory and street view imagery. The dynamic travel features of the residents are extracted from taxi trajectory data and the multi-level physical environment features of the streets are constructed based on street view imagery data. Then, the street space with same urban functions is assigned to the same cluster based on the dynamic travel features of the residents, the multi-level physical environment features of streets and K-means method. The proposed method is empirically applied to the Futian District of Shenzhen to demonstrate its validity, and the street space is successfully classified into five types, namely public, traffic, commercial, residential, and mixed commercial and residential. This work contributes to the evaluation of street space quality, facilitating scientific planning and efficient governance of street space.

Mapping Annual Tidal Flat Loss and Gain in the Micro-Tidal Area Integrating Dual Full-Time Series Spectral Indices

Tracking long-term tidal flat dynamics is crucial for coastal restoration decision making. Accurately capturing the loss and gain of tidal flats due to human-induced disturbances is challenging in the micro-tidal areas. In this study, we developed an automated method for mapping the annual tidal flat changes in the micro-tidal areas under intense human activities, by integrating spectral harmonization, time series segmentation from dual spectral indices, and the tide-independent hierarchical classification strategy. Our method has two key novelties. First, we adopt flexible temporal segments for each pixel based on the dual full-time series spectral indices, instead of solely using a fixed period window, to help obtain more reliable inundation frequency features. Second, a tide-independent hierarchical classification strategy based on the inundation features and the Otsu algorithm capture the tidal flat changes well. Our method performed well in Guangdong, Hong Kong, and Macao (GHKM), a typical area with micro-tidal range and intense human activities, with overall accuracies of 89% and 92% for conversion types and turning years, respectively. The tidal flats in GHKM decreased by 24% from 1986 to 2021, resulting from the loss of 504.45 km2, partially offset by an accretion of 179.88 km2. Further, 70.9% of the total loss was in the Great Bay Area, concentrated in 1991–1998 and 2001–2016. The historical trajectories of tidal flat loss were driven by various policies implemented by the national, provincial, and local governments. Our method is promising for extension to other micro-tidal areas to provide more scientific support for coastal resource management and restoration.

Tapestry of Time and Actions: Modeling Human Activity Sequences Using Temporal Point Process Flows

Human beings always engage in a vast range of activities and tasks that demonstrate their ability to adapt to different scenarios. These activities can range from the simplest daily routines, like walking and sitting, to multi-level complex endeavors such as cooking a four-course meal. Any human activity can be represented as a temporal sequence of actions performed to achieve a certain goal. Unlike the time series datasets extracted from electronics or machines, these action sequences are highly disparate in their nature—the time to finish a sequence of actions can vary between different persons. Therefore, understanding the dynamics of these sequences is essential for many downstream tasks such as activity length prediction, goal prediction, and next action recommendation. Existing neural network based approaches that learn a continuous-time activity sequence are limited to the presence of only visual data or are designed specifically for a particular task (i.e., limited to next action or goal prediction). In this article, we present ProActive , a neural marked temporal point process framework for modeling the continuous-time distribution of actions in an activity sequence while simultaneously addressing three high-impact problems: next action prediction, sequence goal prediction, and end-to-end sequence generation. Specifically, we utilize a self-attention module with temporal normalizing flows to model the influence and the inter-arrival times between actions in a sequence. Moreover, for time-sensitive prediction, we perform an early detection of sequence goal via a constrained margin-based optimization procedure. This in turn allows ProActive to predict the sequence goal using a limited number of actions. In addition, we propose a novel addition over the ProActive model, called ProActive++ , that can handle variations in the order of actions (i.e., different methods of achieving a given goal). We demonstrate that this variant can learn the order in which the person or actor prefers to do their actions. Extensive experiments on sequences derived from three activity recognition datasets show the significant accuracy boost of our ProActive and ProActive++ over the state of the art in terms of action and goal prediction, and the first-ever application of end-to-end action sequence generation.

Expansion of Toxic Algal Blooms in Coastal and Marine Areas in the Philippines and Malaysia: Is It Climate Change Related?

This paper provides a review of toxic algal blooms in the Philippine and Malaysian coastal and marine systems, considering relevant available knowledge, including climate change dimension/s in the assessment of their recorded recent expansion. The first record of human toxicity in the Philippines associated with HABs/toxic algal blooms specifically was during the bloom of Pyrodinium bahamense in the Sorsogon, Samar, and Leyte waters in 1983. Since then, the species has been identified to occur and cause blooms in about 44 sites/areas in the country. Recent government reports, i.e., 2021, 2022, and 2023, have also identified other paralytic shellfish poisoning (PSP) causative organisms (Gymnodinium catenatum, Alexandrium spp.) in the country. New records indicate that the presence of PSP causative species has been reported almost year-round in the Philippines. In Malaysia, PSP caused by P. bahamense was initially confined in 1981 to the state of Sabah, Malaysia Borneo, but since then, blooms of this species have been reported almost annually at different scales across the coastal waters of Sabah. P. bahamense and other cyst-forming dinoflagellates could be transported naturally or through human activities. Other eco-physiological and environment factors from the field and the laboratory have been used to study the bloom dynamics and transport of PSP causative species in several areas in the Philippines and Malaysia. More recently, plastics and other marine litter have been considered potential vectors of invasion/transport or expansion of dinoflagellates with other microorganisms. ENSO events have been observed to be stronger since 1950 compared with those recorded from 1850 to 1950. The extreme phases of the ENSO phenomenon have a strong modulating effect based on seasonal rainfall in the Philippines, with extreme ENSO warm events (El Niño) often associated with drought and stresses on water resources and agriculture/aquaculture. In contrast, cold events (La Niña) often result in excessive rainfall. The La Nina Advisories from 2021 to 2023 (18 advisories) showed the persistence of this part of ENSO, particularly in regions with recurrent and new records of HABs/toxic algal blooms. More studies and monitoring of another type of toxic algal bloom, Ciguatera Fish Poisoning (CFP), are recommended in tropical countries such as the Philippines and Malaysia, which have extensive reef areas that harvest and culture marine fish for local and export purposes, as accelerating reports of this type of poisoning have apparently increased and causative organisms have been identified in several areas. There is an urgent need to enhance HAB/toxic algal bloom research and monitoring, particularly those related to climate change, which has apparently impacted these blooms/occurrences directly or indirectly. Local researchers and managers should be made aware of the knowledge and tools already available for their utilization and enhancement to meet local conditions and challenges for potential recurrence and expansion of HABs/toxic algal blooms. Regional and international HAB research and collaboration should be further advanced for the protection of public health and marine resources.

VR digital twin of office space with computer vision-based estimation of room occupancy and power consumption

AbstractIn the past years, energy consumption has increased rapidly due to many factors, including the rise in technology adoption. This has many downfalls, from higher costs to CO$$_2$$ 2 emissions. Human activities in offices and houses represent a considerable amount of energy usage. A digital twin (DT) of an open-plan common space is created, serving the purpose of remote room occupancy monitoring and automatic detection of energy consumption. A virtual reality (VR) model is developed and integrated to temperature, humidity and imaging sensors. For maintaining privacy, images are processed in local computers to measure occupancy levels and live video feed were never transmitted. The same set of imaging sensors were also used in a bespoke computer vision module for energy consumption estimation. The human avatars were mapped with high correlation (R$$^{2}$$ 2 $$= 0.85$$ = 0.85 ) with actual positions on floor. Our energy consumption algorithm accuracy obtained true positive rate of $$91.58\%$$ 91.58 % and F1 score of $$81.96\%$$ 81.96 % . Finally, all this information is transmitted and visualized to the 3D digital twin for remote monitoring and simulation.

Land subsidence monitoring using InSAR technique in the southwestern region of Bangladesh

Deltas like the Ganges-Brahmaputra Delta (GBD) experience significant land subsidence due to overlaying load, consolidation, sediment compaction, regional tectonics, and human activity. The southwestern region of Bangladesh, marked by its low-lying floodplain with compressible sediments, experiences significant land subsidence. However, accurate assessments for these areas are very scarce, often focusing on the point-based measurements. This study employed Interferometric Synthetic Aperture Radar analysis, spanning from 2014 to 2022, to effectively measure land subsidence, and visualize it spatially. In the study area, subsidence rates were found to be ranging from 3 to 20 mm/year, with most areas experiencing 3-10 mm/year. While some areas show higher rates of 10-13 mm/year, very few exceeded 14 mm/year. The average subsidence rate was 5.98 mm/year, demonstrating significant spatial variability, with higher rates in Gopalganj, Patuakhali, Bhola, Barishal, and other areas. The findings were validated based on existing Global navigation satellite system (GNSS) data points, affirming their reliability. Despite minor discrepancies with other measurements at specific points, the overall results align well with existing data. This comprehensive analysis provides a detailed assessment of land subsidence in the southwestern region of Bangladesh, highlighting significant spatial variability and offering valuable insights for future coastal development and risk mitigation strategies.

Elemental composition and potential health risk of vegetable cultivated in residential area situated close to abandoned gold mine dump: Characteristics of soil quality on the vegetables

The presence of toxic metals in residential areas near abandoned gold mine tailings is a major environmental issue. This study mainly aimed to investigate the elemental distribution of both toxic and essential elements in soils and leafy vegetables (Brassica oleracea) collected from eight different sites around the Davidsonville residential area, located closer to the abandoned Princess gold mine dump, Johannesburg, South Africa. The nutritional value of vegetables in the human diet was determined to assess their value to their health. The vegetables contained metals in the following descending order: Ca > Mg > Ca > Sb > Pb > Fe > Mo > Cr > Se > As > V > Ni > Co > Cd. The bioaccumulation factor (BAF) revealed that vegetables tend to accumulate most metals even (toxic) during the transfer and translocation process. Based on the recommended daily allowance (%RDA) the vegetables showed to contribute 152%, 84% and 75% toward RDA for Se, V and Ca, respectively for most adults and these play a role in human metabolic activities. The vegetables were found to be a good source of essential elements (Ca, Mg, Ni, Na, Fe) but with some traces of toxic metals such as Pb, As and Sb. Based on the health risk assessment, the vegetable posed an adverse health hazard for human consumption due to metals with high HRI >1.

Synecdemus Novus: Presenting the Dataset of Human Activities on Crete (201–1204 C.E.)

Synecdemus Novus: Presenting the Dataset of Human Activities on Crete (201–1204 C.E.)

Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data

Activity recognition is one of the significant technologies accompanying the development of the Internet of Things (IoT). It can help in recording daily life activities or reporting emergencies, thus improving the user’s quality of life and safety, and even easing the workload of caregivers. This study proposes a human activity recognition (HAR) system based on activity data obtained via the micro-Doppler effect, combining a two-stream one-dimensional convolutional neural network (1D-CNN) with a bidirectional gated recurrent unit (BiGRU). Initially, radar sensor data are used to generate information related to time and frequency responses using short-time Fourier transform (STFT). Subsequently, the magnitudes and phase values are calculated and fed into the 1D-CNN and Bi-GRU models to extract spatial and temporal features for subsequent model training and activity recognition. Additionally, we propose a simple cross-channel operation (CCO) to facilitate the exchange of magnitude and phase features between parallel convolutional layers. An open dataset collected through radar, named Rad-HAR, is employed for model training and performance evaluation. Experimental results demonstrate that the proposed 1D-CNN+CCO-BiGRU model demonstrated superior performance, achieving an impressive accuracy rate of 98.2%. This outperformance of existing systems with the radar sensor underscores the proposed model’s potential applicability in real-world scenarios, marking a significant advancement in the field of HAR within the IoT framework.

Effects of increasing soil moisture on Antarctic desert microbial ecosystems.

Overgeneralization and a lack of baseline data for microorganisms in high-latitude environments have restricted the understanding of the microbial response to climate change, which is needed to establish Antarctic conservation frameworks. To bridge this gap, we examined over 17,000 sequence variants of bacteria and microeukarya across the hyperarid Vestfold Hills and Windmill Islands regions of eastern Antarctica. Using an extended gradient forest model, we quantified multispecies response to variations along 79 edaphic gradients to explore the effects of change and wind-driven dispersal on community dynamics under projected warming trends. We also analyzed a second set of soil community data from the Windmill Islands to test our predictions of major environmental tipping points. Soil moisture was the most robust predictor for shaping the regional soil microbiome; the highest rates of compositional turnover occurred at 10-12% soil moisture threshold for photoautotrophs, such as Cyanobacteria, Chlorophyta, and Ochrophyta. Dust profiles revealed a high dispersal propensity for Chlamydomonas, a microalga, and higher biomass was detected at trafficked research stations. This could signal the potential for algal blooms and increased nonendemic species dispersal as human activities increase in the region. Predicted increases in moisture availability on the Windmill Islands were accompanied by high photoautotroph abundances. Abundances of rare oligotrophic taxa, such as Eremiobacterota and Candidatus Dormibacterota, which play a crucial role in atmospheric chemosynthesis, declined over time. That photosynthetic taxa increased as soil moisture increased under a warming scenario suggests the potential for competition between primary production strategies and thus a more biotically driven ecosystem should the climate become milder. Better understanding of environmental triggers will aid conservation efforts, and it is crucial that long-term monitoring of our study sites be established for the protection of Antarctic desert ecosystems. Furthermore, the successful implementation of an improved gradient forest model presents an exciting opportunity to broaden its use on microbial systems globally.

Anthropogenic changes of interannual-to-decadal climate variability in CMIP6 multi-ensemble simulations

Abstract As well as having an impact on the background state of the climate, global warming due to human activities could affect its natural oscillations and internal variability. In this study, we use four initial-condition ensembles from the CMIP6 framework to investigate the potential evolution of internal climate variability under different warming pathways for the 21st century. Our results suggest significant changes in natural climate variability, and point to two distinct regimes driving these changes. First, a decrease of internal variability of surface air temperature at high latitudes and all frequencies, associated with a poleward shift and the gradual disappearance of sea-ice edges, which we show to be an important component of internal variability. Second, an intensification of the interannual variability of surface air temperature and precipitation at low latitudes, which appears to be associated with the El Niño–Southern Oscillation (ENSO). This second regime is particularly alarming because it may contribute to making the climate more unstable and less predictable, with a significant impact on human societies and ecosystems.

Exploration of human activity fragmentation in cyber and physical spaces using massive mobile phone data

ABSTRACT The rapid development of information and communications technology (ICT) in recent years leads to the emergence of cyber space and results in the fragmentation of human activities to some extent. Nevertheless, few studies focused on the exploration of fragmentation, the new characteristic of human activities, partially due to the limited access to proper datasets. In this work, massive Call Detail Records (CDR) data and Uniform Resource Locator (URL) data from millions of mobile phone users are used to extract the activity fragmentation in both cyber and physical spaces. The relationships between activity fragmentation in the two spaces and built environment factors are further examined at different geographical scales. The results show that: 1) the spatial distributions of physical human activity fragmentation (PHAF) and cyber human activity fragmentation (CHAF) are inversely correlated; 2) compared with PHAF, CHAF are less associated with the built environment, probably because cyber activities are less restricted in time and space; 3) CHAF are more influenced by physical fragmentations and the relationships are stable across different cites, indicating that cyber space cannot be completely detached from physical space; and 4) the impact of built environment on CHAF and PHAF are different across different cities. The findings not only shed deeper light on activity fragmentation, but also enlighten the future exploration of its association with both cyber and physical spaces.

Conservation, Sustainability, Conflict and Coexistence: Key Themes in Wildlife Management

Human activities have shaped the Earth’s biotic and abiotic elements for millennia [...]

Impact of Microclimate on Perception and Physical Activities in Public Spaces of New Urban Areas in Beijing, China

The development of new urban areas in Beijing has alleviated overcrowding in old urban centers and has ample public spaces for recreational activities. However, these public spaces are not ideally designed and have not been as successful as expected. Few studies have investigated the ineffective use of these public spaces in terms of microclimatic and thermal comfort factors. Our study investigated microclimatic factors, the subjective assessment of thermal comfort, the intensity of human activities, and the spatial features of public spaces in conjunction with surrounding buildings in a mixed commercial and residential complex in the Fangshan District, Beijing. We used a mixed-methods approach comprising microclimate measurements, questionnaires (n = 150), spatiotemporal behavior mapping, and field measurements. Our results showed that the human perception of the microclimate is related to the exposure duration and other microclimatic factors. The perception of people who spend longer periods outdoors is often inconsistent with objectively measured thermal comfort values. Activity intensity (low, medium, and high) was also related to the duration of time spent outdoors. Microclimatic factors affect the number of people at different activity intensities and the trajectory of the activities. Different spatial features cause different microclimate formations and can directly influence the human subjective assessment of thermal comfort. This study uniquely links the microclimate to human perceptions, physical activities, and spatial features in service of redesigning public spaces. We developed a comprehensive methodology that expands the post-occupancy evaluation and proposes new urban public space designs that consider microclimates. This study also provides a new perspective for promoting physical activity by enhancing the thermal comfort of the environment to achieve physical and mental health goals.

Population Genetic Assessment Model Reveals Conservation Priorities for Gymnocypris Species Resources on the Qinghai-Tibetan Plateau

The Qinghai-Tibetan Plateau (QTP) has nurtured a rich diversity of species because of its unique geographical and environmental conditions. Gymnocypris species (subfamily Schizopygopsinae) are primitive fishes that live in the special environment of the plateau, and their evolution and distribution are inseparable from the historical changes of the QTP. Recently, the resources of Gymnocypris species have been decreasing due to habit deterioration and the intensification of human activities. Therefore, the scientific conservation of the genetic resources of Gymnocypris species is urgently required. In this study, we established two models for the priority conservation assessment of germplasm resources of Gymnocypris species on the basis of the genetic diversity and phylogenetic relationships of 674 individuals from eight Gymnocypris species populations. The results show that the Gymnocypris potanini (GPO), Gymnocypris eckloni (GE), and Gymnocypris przewalskii (GPR) populations are the most genetically diverse in terms of combined genetic diversity values and should be prioritized for conservation. In terms of genetic contribution, the GPO, GE, and GPR populations have a positive impact on maintaining the distinctiveness and diversity of the entire Gymnocypris species population and should be prioritized for conservation. However, in terms of different evolutionary clades, the Gymnocypris namensis, Gymnocypris waddellii, Gymnocypris dobula, and GE populations in clade A should be given priority for protection, the GE population in clade B should be given priority, and the GPR population in clade C should be given priority. In conclusion, the two models and assessment of conservation priorities will provide a scientific basis for the conservation of Gymnocypris species.