Understanding trophic structure variation in fish assemblages of subtropical shallow lakes: Combined effects of ecosystem size, productivity, and disturbance

Jia, Yating; Jiang, Yihang; Liu, Yuhan; Sui, Xiaoyun; Feng, Xiu; Zhu, Ren; Chen, Yifeng

doi:10.1016/j.ecolind.2021.107924

Cited by 18 publications

(10 citation statements)

References 76 publications

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“…Commercial fishing frequently focuses on large species of high trophic level (e.g., Arapaima spp. ), which consequentially alters the fish assemblage (Jia et al 2021) and explains the importance of this metric to assess biotic integrity in ALMS-IBI. In the case of piranhas, we attribute their higher abundance in the PR lakes relative to the CM lakes to the sedentary behavior of these species (Soares et al 2008), which characterizes them as residents in the PR lakes, at a longer distance from the CM lakes and isolated in the low water period.…”

Section: Discussionmentioning

confidence: 99%

“…In the study by Petesse et al (2016), the lakes with excellent biotic integrity presented the highest percentages of predatory (i.e., carnivorous) fish. Carnivorous fish play a role in structuring the lower trophic levels (Jia et al 2021), therefore changes in the proportion of fish belonging to high trophic levels can alter the fish assemblage to a higher dominance of lower trophic levels. Commercial fishing frequently focuses on large species of high trophic level (e.g., Arapaima spp.…”

Section: Discussionmentioning

confidence: 99%

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Evaluation of fisheries management strategies using a biotic integrity index in floodplain lakes in the lower Solimões River, Amazonas, Brazil

et al. 2022

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Fisheries is an important activity in the Amazon basin and potentially has a high impact on ichthyofauna. With the aim of achieving sustainability in fisheries of target species, protected areas were established within a fisheries management framework known as the Amazon Lakes Management System (ALMS). With the aim to evaluate the effect of ALMS on fish assemblages as a whole, we compared floodplain lakes with different levels of fish management in the lower Solimões River, in the Brazilian Amazon, developing an index of biotic integrity, named ALMS-IBI. We sampled fish in three lake categories: protected (PR), managed (MN), and commercially fished (CM). The ALMS-IBI was developed by selecting and testing fish assemblage metrics based on samplings carried out in 2017 and 2018, using gillnets with different mesh sizes. We captured 4565 fish of 113 species and seven trophic categories. The final index is composed of seven metrics related to species richness, trophic structure, and fish abundance, and characterized the fish assemblage in the PR and MN lakes as acceptable, and in the CM lakes as poor. Our results indicate that the ALMS-IBI can be an efficient method to monitor the whole fish assemblage in Amazonian floodplain lakes, and can be used as a complementary tool in the ALMS to assess environmental sustainability.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Evaluation of fisheries management strategies using a biotic integrity index in floodplain lakes in the lower Solimões River, Amazonas, Brazil

et al. 2022

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“…The process of categorizing fish is necessary in order to precisely measure the behavior of distinct species. Different species of fish exhibit more or smaller variances in size, texture, form, and other physical characteristics than do other species of fish [38,39]. As the three most crucial characteristics for visual identification, texture characteristics, shape characteristics, and color characteristics must all be utilized in conjunction to define image characteristics in order to produce superior classification results [40,41].…”

Section: Related Workmentioning

confidence: 99%

Fish Species Identification on Low Resolution - A Study with Enhanced Super Resolution Generative Adversarial Network (ESRGAN), YOLO and VGG-16

Adhikary¹

2022

Preprint

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A smart detection and recognition model for the species of a fish from camera footage is of urgent requirement as fishery contributes to a large portion of the world economy and these kinds of advanced models can aid fishermen on a large scale. Such models incorporating a pick-and-place machine can be very useful to sort different fish species in a bulk without human intervention and this can greatly reduce costs for large scale fishing industries. Existing methods for detecting and recognizing fish species have many limitations such as limited scalability, detection accuracy, failing to detect multiple species, degraded performance at a lower resolution, or pinpointing the exact location of the fish. By modifying the head of a very powerful deep learning model namely VGG-16 with pre-trained weights can be used to detect both the species of the fish and find the exact location of the fish in an image by implementing a modified YOLO to incorporate the bounding box regression head. We have proposed the usage of the ESRGAN algorithm along with the proposed neural network to amplify the image resolution by a factor of 4. With this method, the overall detection accuracy of 96.5% has been obtained. The experiment has been conducted based on a total of 9460 images spread across 9 species. After further improving the model, a pick-and-place machine could be integrated for very fast sorting of the fish according to their species in different large-scale fish industries.

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“…Habitat size promotes the occupancy likelihood of large‐sized predators, that require large home ranges, as well as those of intermediate trophic‐level consumers (Srivastava et al, 2008; Ward & McCann, 2017). Consequently, the presence of these top and intermediate consumers in large and habitat‐rich ecosystems would elongate food chains and increase the complexity of the vertical structure of food webs (Jia et al, 2021; Thompson & Townsend, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…As a result, the vertical food web structure in less productive systems is expected to be truncated compared to more productive systems (Binzer et al, 2016). The most productive ecosystems are supplied by a surplus of available energy favoring food web complexity with species at high trophic levels becoming more abundant and new trophic levels can add up (Jia et al, 2021; Takimoto & Post, 2013).…”

Section: Introductionmentioning

confidence: 99%

Temperature, productivity, and habitat characteristics collectively drive lake food web structure

Leclerc

Reynaud

Danis

et al. 2023

Global Change Biology

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Understanding trophic structure variation in fish assemblages of subtropical shallow lakes: Combined effects of ecosystem size, productivity, and disturbance

Cited by 18 publications

References 76 publications

Evaluation of fisheries management strategies using a biotic integrity index in floodplain lakes in the lower Solimões River, Amazonas, Brazil

Evaluation of fisheries management strategies using a biotic integrity index in floodplain lakes in the lower Solimões River, Amazonas, Brazil

Fish Species Identification on Low Resolution - A Study with Enhanced Super Resolution Generative Adversarial Network (ESRGAN), YOLO and VGG-16

Temperature, productivity, and habitat characteristics collectively drive lake food web structure

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