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Liese C, Crosson S. Quantifying the economic effects of different fishery management regimes in two otherwise similar fisheries. PLoS One 2023; 18:e0287250. [PMID: 37339153 DOI: 10.1371/journal.pone.0287250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 06/02/2023] [Indexed: 06/22/2023] Open
Abstract
In the southeast U.S., two very similar fisheries are managed by very different management regimes. In the Gulf of Mexico Reef Fish fishery, all major species are managed by individual transferable quotas (ITQs). The neighboring S. Atlantic Snapper-Grouper fishery continues to be managed by traditional regulations such as vessel trip-limits and closed seasons. Using detailed landings and revenue data from logbooks together with trip-level and annual, vessel-level economic survey data, we develop financial statements for each fishery to estimate cost structures, profits, and resource rent. By comparing the two fisheries from an economic perspective, we illustrate the detrimental effects of the regulatory measures on the S. Atlantic Snapper-Grouper fishery and quantify the difference in economic outcomes, including estimating the difference in resource rent. We find that the choice of fishery management regime shows up as a regime shift in the productivity and profitability of the fisheries. The ITQ fishery generates substantially more resource rents than the traditionally managed fishery; the difference is a large fraction of revenue (~30%). In the S. Atlantic Snapper-Grouper fishery, the potential value of the resource has almost completely dissipated via lower ex-vessel prices and hundreds of thousands of gallons of wasted fuel. Excess use of labor is a lesser issue.
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Affiliation(s)
- Christopher Liese
- NOAA Southeast Fisheries Science Center, Miami, Florida, United States of America
| | - Scott Crosson
- NOAA Southeast Fisheries Science Center, Miami, Florida, United States of America
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Zeng TT, Deng TH, Liu Z, Zhan JR, Ma YZ, Yan YY, Sun X, Zhu YH, Li Y, Guan XY, Li L. HN1L/AP-2γ/PLK1 signaling drives tumor progression and chemotherapy resistance in esophageal squamous cell carcinoma. Cell Death Dis 2022; 13:1026. [PMID: 36476988 PMCID: PMC9729194 DOI: 10.1038/s41419-022-05478-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 11/24/2022] [Accepted: 11/28/2022] [Indexed: 12/12/2022]
Abstract
Hematological and neurological expressed 1 like (HN1L) is a newly identified oncogene in lung cancer and hepatocellular carcinoma recently identified by our team, but its roles in the development and treatment of esophageal squamous cell carcinoma (ESCC) remain incompletely cataloged. Here, using ESCC tissue array and public database analysis, we demonstrated that HN1L was highly expressed in ESCC tissues, which was associated with tumor tissue invasion, poor clinical stage and short survival for ESCC patients. Loss- and gain-of-function studies in ESCC cells revealed that HN1L enhances ESCC cell metastasis and proliferation in vitro and in mice models. Moreover, high level of HN1L reduces the sensibility of ESCC cells to chemotherapeutic drugs, such as Docetaxel. Mechanism studies revealed that HN1L activated the transcription of polo-like kinase 1 (PLK1) by interacting with transcription factor AP-2γ, which increased the expression of malignancy related proteins Cyclin D1 and Slug in ESCC cells. Blocking PLK1 with inhibitor BI-2356 abrogated the oncogenic function of HN1L and significantly suppressed ESCC progression by combining with chemotherapy. Therefore, this study demonstrates the vital pro-tumor role of HN1L/AP-2γ/PLK1 signaling axis in ESCC, offering a potential therapeutic strategy for ESCC patients with high HN1L by blocking PLK1.
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Affiliation(s)
- Ting-Ting Zeng
- grid.488530.20000 0004 1803 6191State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, 510060 Guangzhou, China
| | - Tian-Hao Deng
- grid.489633.3The Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine, 410006 Changsha, China
| | - Zhen Liu
- grid.489633.3Hunan Academy of Traditional Chinese Medicine, 410006 Changsha, China
| | - Jia-Rong Zhan
- grid.488530.20000 0004 1803 6191State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, 510060 Guangzhou, China
| | - Yuan-Zhen Ma
- grid.488530.20000 0004 1803 6191State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, 510060 Guangzhou, China
| | - Yuan-Yuan Yan
- grid.412536.70000 0004 1791 7851Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510120 Guangzhou, China ,grid.412536.70000 0004 1791 7851Nanhai Translational Innovation Center of Precision Immunology, Sun Yat-sen Memorial Hospital, 528200 Foshan, China
| | - Xiao Sun
- grid.412536.70000 0004 1791 7851Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510120 Guangzhou, China ,grid.412536.70000 0004 1791 7851Nanhai Translational Innovation Center of Precision Immunology, Sun Yat-sen Memorial Hospital, 528200 Foshan, China
| | - Ying-Hui Zhu
- grid.488530.20000 0004 1803 6191State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, 510060 Guangzhou, China
| | - Yan Li
- grid.488530.20000 0004 1803 6191State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, 510060 Guangzhou, China
| | - Xin-Yuan Guan
- grid.488530.20000 0004 1803 6191State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, 510060 Guangzhou, China ,grid.440671.00000 0004 5373 5131Department of Clinical Oncology, Shenzhen Key Laboratory for Metastasis and Personalized Therapy, The University of Hong Kong-Shenzhen Hospital, 518053 Shenzhen, China ,grid.194645.b0000000121742757Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China
| | - Lei Li
- grid.412536.70000 0004 1791 7851Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510120 Guangzhou, China ,grid.412536.70000 0004 1791 7851Nanhai Translational Innovation Center of Precision Immunology, Sun Yat-sen Memorial Hospital, 528200 Foshan, China ,grid.440671.00000 0004 5373 5131Department of Clinical Oncology, Shenzhen Key Laboratory for Metastasis and Personalized Therapy, The University of Hong Kong-Shenzhen Hospital, 518053 Shenzhen, China
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Scheufele G, Pascoe S. Estimation and use of recreational fishing values in management decisions. AMBIO 2022; 51:1275-1286. [PMID: 34714515 PMCID: PMC8931158 DOI: 10.1007/s13280-021-01634-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 02/02/2021] [Accepted: 09/17/2021] [Indexed: 05/03/2023]
Abstract
In many countries, commercial and recreational fishing compete for access to marine resources. In some cases, recreational catch outweighs commercial harvest and may threaten species otherwise protected from commercial fishing. This has led to increasing calls for improved management of recreational fishing in the broader context of general fisheries management. As a result, fisheries managers face the challenge to decide how to allocate the available marine resources between competing uses. In this paper, we review and explain two common approaches that have been used to support recreational fishing allocation decisions. While economic activity analysis is an appropriate tool to assess how a change in resource allocation would affect regional economic activity (economic contributions and impacts), it is ill-suited to assess associated gains or losses in welfare of society as a whole (economic efficiency). Hence, economic activity analysis and social cost-benefit analysis complement each other, with each providing a different set of information answering a different set of questions. Unfortunately, both types of analysis use the term "economic value" suggesting that they are alternative approaches that provide the same information, whereas in fact they are not. If the objective of fishery managers is to ensure that society as a whole is made better off, the appropriate metric is economic value as defined by welfare economics. Under this definition, all goods and services provided by marine resources that are beneficial to humans have economic value. This includes non-use values such as the continued existence of an endangered marine species. The aim of this paper is to support managers and policymakers in allocating marine resources by reviewing relevant economic principles, concepts, and tools in the context of recreational fishing, including the use and challenges of estimating the non-market benefits generated by recreational fishing experiences.
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Affiliation(s)
- Gabriela Scheufele
- Marine Resource Economics Team, CSIRO Oceans and Atmosphere, Queensland Biosciences Precinct, 306 Carmody Road, Saint Lucia, 4067 Australia
| | - Sean Pascoe
- Marine Resource Economics Team, CSIRO Oceans and Atmosphere, Queensland Biosciences Precinct, 306 Carmody Road, Saint Lucia, 4067 Australia
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