Browsing by Author "Yi S"

Now showing 1 - 4 of 4
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    An improved method for monitoring multiscale plant species diversity of alpine grassland using UAVs: A case study in the source region of the Yellow River, China
    (Frontiers Media, 9/06/2022) Sun Y; Yuan Y; Luo Y; Ji W; Bian Q; Zhu Z; Wang J; Qin Y; He XZ; Li M; Yi S
    Plant species diversity (PSD) is essential in evaluating the function and developing the management and conservation strategies of grassland. However, over a large region, an efficient and high precision method to monitor multiscale PSD (α-, β-, and γ-diversity) is lacking. In this study, we proposed and improved an unmanned aerial vehicle (UAV)-based PSD monitoring method (UAVB) and tested the feasibility, and meanwhile, explored the potential relationship between multiscale PSD and precipitation on the alpine grassland of the source region of the Yellow River (SRYR), China. Our findings showed that: (1) UAVB was more representative (larger monitoring areas and more species identified with higher α- and γ-diversity) than the traditional ground-based monitoring method, though a few specific species (small in size) were difficult to identify; (2) UAVB is suitable for monitoring the multiscale PSD over a large region (the SRYR in this study), and the improvement by weighing the dominance of species improved the precision of α-diversity (higher R 2 and lower P values of the linear regressions); and (3) the species diversity indices (α- and β-diversity) increased first and then they tended to be stable with the increase of precipitation in SRYR. These findings conclude that UAVB is suitable for monitoring multiscale PSD of an alpine grassland community over a large region, which will be useful for revealing the relationship of diversity-function, and helpful for conservation and sustainable management of the alpine grassland.
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    Per- and polyfluoroalkyl substances (PFAS), trace elements and life history parameters of mass-stranded common dolphins (Delphinus delphis) in New Zealand
    (Elsevier Ltd, 2021-12) Stockin KA; Yi S; Northcott GL; Betty EL; Machovsky-Capuska GE; Jones B; Perrott MR; Law RJ; Rumsby A; Thelen MA; Graham L; Palmer EI; Tremblay LA
    Profiles of 33 PFAS analytes and 12 essential and non-essential trace elements were measured in livers of stranded common dolphins (Delphinus delphis) from New Zealand. PFAS concentrations reported were largely comparable to those measured in other marine mammal species globally and composed mostly of long-chain compounds including perfluorooctanesulfonic acid (PFOS), perfluorododecanoic acid (PFDoDA), perfluorotridecanoic acid (PFTrDA) and perfluorooctanesulfonamide (FOSA). PFAS profiles did not vary significantly by location, body condition, or life history. Notably, significant positive correlations were observed within respective PFAS and trace elements. However, only negative correlations were evident between these two contaminant types, suggesting different exposure and metabolic pathways. Age-associated concentrations were found for PFTrDA and four trace elements, i.e. silver, mercury, cadmium, selenium, indicating differences in the bioaccumulation biomagnification mechanisms. Overall, our results contribute to global understanding of accumulation of PFAS by offering first insights of PFAS exposure in cetaceans living within South Pacific Australasian waters.
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    Predicting the distribution of oxytropis ochrocephala bunge in the source region of the yellow river (China) based on uav sampling data and species distribution model
    (1/12/2021) Zhang X; Yuan Y; Zhu Z; Ma Q; Yu H; Li M; Ma J; Yi S; He XZ; Sun Y
    Oxytropis ochrocephala Bunge is an herbaceous perennial poisonous weed. It severely affects the production of local animal husbandry and ecosystem stability in the source region of Yellow River (SRYR), China. To date, however, the spatiotemporal distribution of O. ochrocephala is still unclear, mainly due to lack of high-precision observation data and effective methods at a regional scale. In this study, an efficient sampling method, based on unmanned aerial vehicle (UAV), was proposed to supply basic sampling data for species distribution models (SDMs, BIOMOD in this study). A total of 3232 aerial photographs were obtained, from 2018 to 2020, in SRYR, and the potential and future distribution of O. ochrocephala were predicted by an ensemble model, consisting of six basic models of BIOMOD. The results showed that: (1) O. ochrocephala mainly distributed in the southwest, middle, and northeast of the SRYR, and the high suitable habitat of O. ochrocephala accounted for 3.19%; (2) annual precipitation and annual mean temperature were the two most important factors that affect the distribution of O. ochrocephala, with a cumulative importance of 60.45%; and (3) the distribution probability of O. ochrocephala tends to increase from now to the 2070s, while spatial distribution ranges will remain in the southwest, middle, and northeast of the SRYR. This study shows that UAVs can potentially be used to obtain the basic data for species distribution modeling; the results are both beneficial to establishing reasonable management practices and animal husbandry in alpine grassland systems.
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    UAV Assisted Livestock Distribution Monitoring and Quantification: A Low-Cost and High-Precision Solution
    (MDPI AG, 29/09/2023) Ji W; Luo Y; Liao Y; Wu W; Wei X; Yang Y; Shen Y; Ma Q; He X; Yi S; Sun Y
    Grazing management is one of the most widely practiced land uses globally. Quantifying the spatiotemporal distribution of livestock is critical for effective management of livestock-grassland grazing ecosystem. However, to date, there are few convincing solutions for livestock dynamic monitor and key parameters quantification under actual grazing situations. In this study, we proposed a pragmatic method for quantifying the grazing density (GD) and herding proximities (HP) based on unmanned aerial vehicles (UAVs). We further tested its feasibility at three typical household pastures on the Qinghai-Tibetan Plateau, China. We found that: (1) yak herds grazing followed a rotational grazing pattern spontaneously within the pastures, (2) Dispersion Index of yak herds varied as an M-shaped curve within one day, and it was the lowest in July and August, and (3) the average distance between the yak herd and the campsites in the cold season was significantly shorter than that in the warm season. In this study, we developed a method to characterize the dynamic GD and HP of yak herds precisely and effectively. This method is ideal for studying animal behavior and determining the correlation between the distribution of pastoral livestock and resource usability, delivering critical information for the development of grassland ecosystem and the implementation of sustainable grassland management.