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In the context of the comprehensive advancement of the green water protection campaign, guiding river chiefs to effectively assume inter-generational responsibilities and promote the ecological sustainability of urban inland rivers is a critical practical challenge. This paper addresses the issues of "difficult inter-generational coordination of river chiefs and limited internal government supervision" within the sustainable governance framework of urban inland rivers. Utilizing evolutionary game theory, we develop a four-player evolutionary game model that includes the previous and next generations of river chiefs, government administrative supervision departments, and the public. By examining the strategic evolution of the system under various influencing factors, we explore how local government administrative supervision departments can collaborate with the public to establish an internal and external dual-layer multi-governance supervision system, thereby encouraging river chiefs to fulfill their inter-generational responsibilities. Our findings indicate that the influence between the two generations of river chiefs is asymmetric over time and space, with the governance strategy of the previous generation having a more significant impact on the next. As comprehensive management costs increase, both generations exhibit a tendency towards negative governance intentions. Reducing the cost-sharing ratio alleviates the burden on the previous generation but hinders the continuity of governance by the next, leading to interruptions in management efforts. Enhanced administrative supervision can accelerate system stabilization, significantly affecting both generations of river chiefs. However, relying solely on increased enforcement without adjusting rewards and penalties will gradually diminish its effectiveness. Changes in performance-based rewards, penalties, and base salaries affect system stability to varying degrees, but base salary adjustments have a limited impact compared to the responsiveness of performance incentives. Although increased public reporting intensity does not significantly alter the strategy choices of the two generations of river chiefs, it does contribute to reducing system stabilization time. This study not only enriches the theoretical understanding of inter-generational responsibilities of government officials and sustainable environmental governance but also provides a theoretical foundation for the sustainable ecological management of urban inland rivers. By analyzing the impact of various factors on the strategic choices of river chiefs across generations, it offers insights into the internal mechanisms of urban inland river ecological governance. Furthermore, it supports local government administrative supervision departments in collaborating with the public to build a dual-layer multi-governance supervision system, facilitating continuous improvements in the ecological environment of urban inland rivers.

, correspAuthors=Yang ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Jing SHEN, Qing WEN, Min ZHANG, Yang ZHANG, Rui ZHAN, Li HE), CN=ArticleExt(id=1241116672321441965, articleId=1241116643661762894, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=河长代际责任下城市内河可持续治理机制研究, columnId=1234106419604157142, journalTitle=中国环境科学, columnName=环境影响评价与管理, runingTitle=null, highlight=null, articleAbstract=

在全面推进碧水保卫战背景下,如何通过有效的政策措施科学引导河长承担代际责任,以推动城市内河的可持续治理,是亟需解决的重要现实问题.本文旨在破解城市内河可持续治理模式中“河长代际衔接难、政府内部监管有限”困境,基于演化博弈理论,构建了包含上代河长、下代河长、政府行政监督部门和公众的四方演化博弈模型,分析不同因素对系统策略演化的影响,探究地方政府行政监督部门如何与公众合作,构建内外双层多元共治监督体系,以促进河长承担代际责任.研究表明:(1)在时空演进中,两代河长之间的相互影响是不对称的,上代河长的治理策略对下代河长的影响较大.(2)随着综合治理成本的增加,两代河长均表现出消极的治理意愿;而成本分担比例的减少虽减轻了上代河长的治理负担,但不利于下代河长延续治理,导致治理中断现象.(3)政府行政监督部门的执行力度增加会不同程度地缩短系统趋稳时间,对两代河长均有显著影响.(4)绩效奖励额、绩效惩罚额以及级别工资变化会不同程度地影响系统趋稳时间,但与绩效奖惩的弹性相比,级别工资变化对两代河长治理策略的影响有限.(5)提高公众举报力度在一定程度上缩短了系统趋稳时间.该研究不仅丰富了政府官员代际责任与生态环境可持续治理理论的研究范畴,而且为城市内河生态可持续治理提供了理论借鉴和参考.

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* 责任作者,副教授,
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申婧(1988-),女,新疆乌鲁木齐人,讲师,博士,研究方向为水环境治理.发表论文10余篇..

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申婧(1988-),女,新疆乌鲁木齐人,讲师,博士,研究方向为水环境治理.发表论文10余篇..

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申婧(1988-),女,新疆乌鲁木齐人,讲师,博士,研究方向为水环境治理.发表论文10余篇..

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journalId=1234093305789726721, articleId=1241116643661762894, language=EN, label=Table 1, caption=

Four-party evolutionary game payoff matrix

, figureFileSmall=null, figureFileBig=null, tableContent=
策略选择下代河长政府行政监督部门
积极执行奖惩措施(m)消极执行奖惩措施(1-m)
公众举报(z)公众不举报(1-z)公众举报(z)公众不举报(1-z)
上代河长积极治理(x)积极治理(y)a1=−lC1+R1+Vs+E1a2=−lC1+R1+Vs+E1a3=−lC1+qR1+qVs+E1a4=−lC1+qR1+qVs+E1
c1=−C2+E4+Bc2=−C2+E4+Bc3=−qC2+E4c4=−qC2+E4
d1=−C3+E5d2=E5d3=−C3+E5d4=E5
消极治理(1-y)a5=−lC1+R1+Vs+E1a6=−lC1+R1+Vs+E1a7=−lC1+qR1+qVs+E1a8=−lC1+qR1+qVs+E1
c5=−C2+lE4+Bc6=−C2+lE4+Bc7=−qC2+lE4Fc8=−qC2+lE4
d5=−C3+lE5+R4d6=lE5d7=−C3+lE5+R4d8=lE5
消极治理(1-x)积极治理(y)a9=−S1UsH1+T1a10=−S1UsH1+T1a11=−q'S1q'UsH1+T1a12=−qS1qUsH1+T1
c9=−C2+hE4+Bc10=−C2+hE4+Bc11=−qC2+hE4Fc12=−qC2+hE4
d9=−C3+hE5+R4d10=hE5d11=−C3+hE5+R4d12=hE5
消极治理(1-y)a13=−S1UsH1+T1a14=−S1UsH1+T1a15=−q'S1q'UsH1+T1a16=−qS1qUsH1+T1
c13=−C2H4+Bc14=−C2H4+Bc15=−qC2H4Fc16=−qC2H4
d13=−C3H5+R4d14=−H5d15=−C3H5+R4d16=−H5
), ArticleFig(id=1241116681955758726, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643661762894, language=CN, label=表1, caption=

四方演化博弈支付矩阵

, figureFileSmall=null, figureFileBig=null, tableContent=
策略选择下代河长政府行政监督部门
积极执行奖惩措施(m)消极执行奖惩措施(1-m)
公众举报(z)公众不举报(1-z)公众举报(z)公众不举报(1-z)
上代河长积极治理(x)积极治理(y)a1=−lC1+R1+Vs+E1a2=−lC1+R1+Vs+E1a3=−lC1+qR1+qVs+E1a4=−lC1+qR1+qVs+E1
c1=−C2+E4+Bc2=−C2+E4+Bc3=−qC2+E4c4=−qC2+E4
d1=−C3+E5d2=E5d3=−C3+E5d4=E5
消极治理(1-y)a5=−lC1+R1+Vs+E1a6=−lC1+R1+Vs+E1a7=−lC1+qR1+qVs+E1a8=−lC1+qR1+qVs+E1
c5=−C2+lE4+Bc6=−C2+lE4+Bc7=−qC2+lE4Fc8=−qC2+lE4
d5=−C3+lE5+R4d6=lE5d7=−C3+lE5+R4d8=lE5
消极治理(1-x)积极治理(y)a9=−S1UsH1+T1a10=−S1UsH1+T1a11=−q'S1q'UsH1+T1a12=−qS1qUsH1+T1
c9=−C2+hE4+Bc10=−C2+hE4+Bc11=−qC2+hE4Fc12=−qC2+hE4
d9=−C3+hE5+R4d10=hE5d11=−C3+hE5+R4d12=hE5
消极治理(1-y)a13=−S1UsH1+T1a14=−S1UsH1+T1a15=−q'S1q'UsH1+T1a16=−qS1qUsH1+T1
c13=−C2H4+Bc14=−C2H4+Bc15=−qC2H4Fc16=−qC2H4
d13=−C3H5+R4d14=−H5d15=−C3H5+R4d16=−H5
), ArticleFig(id=1241116682048033420, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643661762894, language=EN, label=Table 2, caption=

The equilibrium point and eigenvalues of system(I)

, figureFileSmall=null, figureFileBig=null, tableContent=
均衡点特征值特征值符号稳定性
1λλ2λ3λ4
(0,0,0,0)ε1+ε4ε9+ε12ε13ε15+ε16均可为负值渐进稳定
(0,0,0,1)ε1+ε3ε9+ε111314ε+ε−(ε15+ε16)均可为负值渐进稳定
(0,0,1,0)ε1+ε2ε9+ε1013εε15+ε16均可为负值渐进稳定
(0,1,0,0)ε1+ε4−(ε9+ε12)ε13ε15+ε16均可为负值渐进稳定
(1,0,0,0)−(ε1+ε4)58ε+εε13ε15+ε16均可为负值渐进稳定
(0,0,1,1)ε1+ε2910ε+ε−(ε13+ε14)−(ε15+ε16)均可为负值渐进稳定
(0,1,0,1)ε1+ε3−(ε9+ε11)ε13+ε14−(ε15+ε16)均可为负值渐进稳定
(0,1,1,0)ε1+ε2−(ε9+ε10)ε13ε15+ε16均可为负值渐进稳定
(0,1,1,1)ε1+ε2−(ε9+ε10)−(ε13+ε14)−(ε15+ε16)均可为负值渐进稳定
(1,0,0,1)−(ε1+ε3)ε5+ε7ε13+ε14−(ε15+ε16)均可为负值渐进稳定
(1,0,1,0)−(ε1+ε2)ε5+ε613εε15+ε16均可为负值渐进稳定
(1,0,1,1)−(ε1+ε2)ε5+ε6−(ε13+ε14)−(ε15+ε16)均可为负值渐进稳定
(1,1,0,0)−(ε1+ε4)−(ε5+ε8)ε13ε15均可为负值渐进稳定
(1,1,0,1)−(ε1+ε3)−(ε5+ε7)ε13ε15有正值不稳定
(1,1,1,0)−(ε1+ε2)−(ε5+ε6)13ε15ε均可为负值渐进稳定
(1,1,1,1)−(ε1+ε2)−(ε5+ε6)ε1315ε有正值不稳定
), ArticleFig(id=1241116682157085332, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116643661762894, language=CN, label=表2, caption=

系统(I)的均衡点及其特征值

, figureFileSmall=null, figureFileBig=null, tableContent=
均衡点特征值特征值符号稳定性
1λλ2λ3λ4
(0,0,0,0)ε1+ε4ε9+ε12ε13ε15+ε16均可为负值渐进稳定
(0,0,0,1)ε1+ε3ε9+ε111314ε+ε−(ε15+ε16)均可为负值渐进稳定
(0,0,1,0)ε1+ε2ε9+ε1013εε15+ε16均可为负值渐进稳定
(0,1,0,0)ε1+ε4−(ε9+ε12)ε13ε15+ε16均可为负值渐进稳定
(1,0,0,0)−(ε1+ε4)58ε+εε13ε15+ε16均可为负值渐进稳定
(0,0,1,1)ε1+ε2910ε+ε−(ε13+ε14)−(ε15+ε16)均可为负值渐进稳定
(0,1,0,1)ε1+ε3−(ε9+ε11)ε13+ε14−(ε15+ε16)均可为负值渐进稳定
(0,1,1,0)ε1+ε2−(ε9+ε10)ε13ε15+ε16均可为负值渐进稳定
(0,1,1,1)ε1+ε2−(ε9+ε10)−(ε13+ε14)−(ε15+ε16)均可为负值渐进稳定
(1,0,0,1)−(ε1+ε3)ε5+ε7ε13+ε14−(ε15+ε16)均可为负值渐进稳定
(1,0,1,0)−(ε1+ε2)ε5+ε613εε15+ε16均可为负值渐进稳定
(1,0,1,1)−(ε1+ε2)ε5+ε6−(ε13+ε14)−(ε15+ε16)均可为负值渐进稳定
(1,1,0,0)−(ε1+ε4)−(ε5+ε8)ε13ε15均可为负值渐进稳定
(1,1,0,1)−(ε1+ε3)−(ε5+ε7)ε13ε15有正值不稳定
(1,1,1,0)−(ε1+ε2)−(ε5+ε6)13ε15ε均可为负值渐进稳定
(1,1,1,1)−(ε1+ε2)−(ε5+ε6)ε1315ε有正值不稳定
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河长代际责任下城市内河可持续治理机制研究
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申婧 1 , 文清 1 , 张敏 1 , 张阳 1, * , 詹瑞 1 , 何理 2
中国环境科学 | 环境影响评价与管理 2025,45(3): 1731-1744
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中国环境科学 | 环境影响评价与管理 2025, 45(3): 1731-1744
河长代际责任下城市内河可持续治理机制研究
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申婧1 , 文清1, 张敏1, 张阳1, * , 詹瑞1, 何理2
作者信息
  • 1.中国计量大学经济与管理学院,浙江 杭州 310018
  • 2.天津大学,水利工程仿真与安全国家重点实验室,天津 300072
  • 申婧(1988-),女,新疆乌鲁木齐人,讲师,博士,研究方向为水环境治理.发表论文10余篇..

通讯作者:

* 责任作者,副教授,
Exploring the inter-generational accountability of river chiefs in the sustainable management of urban inland rivers: A mechanistic approach
Jing SHEN1 , Qing WEN1, Min ZHANG1, Yang ZHANG1, * , Rui ZHAN1, Li HE2
Affiliations
  • 1.School of Economics and Management, China Jiliang University, Hangzhou 310018, China
  • 2.State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China
出版时间: 2025-03-20
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在全面推进碧水保卫战背景下,如何通过有效的政策措施科学引导河长承担代际责任,以推动城市内河的可持续治理,是亟需解决的重要现实问题.本文旨在破解城市内河可持续治理模式中“河长代际衔接难、政府内部监管有限”困境,基于演化博弈理论,构建了包含上代河长、下代河长、政府行政监督部门和公众的四方演化博弈模型,分析不同因素对系统策略演化的影响,探究地方政府行政监督部门如何与公众合作,构建内外双层多元共治监督体系,以促进河长承担代际责任.研究表明:(1)在时空演进中,两代河长之间的相互影响是不对称的,上代河长的治理策略对下代河长的影响较大.(2)随着综合治理成本的增加,两代河长均表现出消极的治理意愿;而成本分担比例的减少虽减轻了上代河长的治理负担,但不利于下代河长延续治理,导致治理中断现象.(3)政府行政监督部门的执行力度增加会不同程度地缩短系统趋稳时间,对两代河长均有显著影响.(4)绩效奖励额、绩效惩罚额以及级别工资变化会不同程度地影响系统趋稳时间,但与绩效奖惩的弹性相比,级别工资变化对两代河长治理策略的影响有限.(5)提高公众举报力度在一定程度上缩短了系统趋稳时间.该研究不仅丰富了政府官员代际责任与生态环境可持续治理理论的研究范畴,而且为城市内河生态可持续治理提供了理论借鉴和参考.

城市内河  /  可持续治理  /  河长代际责任  /  奖惩机制  /  演化博弈

In the context of the comprehensive advancement of the green water protection campaign, guiding river chiefs to effectively assume inter-generational responsibilities and promote the ecological sustainability of urban inland rivers is a critical practical challenge. This paper addresses the issues of "difficult inter-generational coordination of river chiefs and limited internal government supervision" within the sustainable governance framework of urban inland rivers. Utilizing evolutionary game theory, we develop a four-player evolutionary game model that includes the previous and next generations of river chiefs, government administrative supervision departments, and the public. By examining the strategic evolution of the system under various influencing factors, we explore how local government administrative supervision departments can collaborate with the public to establish an internal and external dual-layer multi-governance supervision system, thereby encouraging river chiefs to fulfill their inter-generational responsibilities. Our findings indicate that the influence between the two generations of river chiefs is asymmetric over time and space, with the governance strategy of the previous generation having a more significant impact on the next. As comprehensive management costs increase, both generations exhibit a tendency towards negative governance intentions. Reducing the cost-sharing ratio alleviates the burden on the previous generation but hinders the continuity of governance by the next, leading to interruptions in management efforts. Enhanced administrative supervision can accelerate system stabilization, significantly affecting both generations of river chiefs. However, relying solely on increased enforcement without adjusting rewards and penalties will gradually diminish its effectiveness. Changes in performance-based rewards, penalties, and base salaries affect system stability to varying degrees, but base salary adjustments have a limited impact compared to the responsiveness of performance incentives. Although increased public reporting intensity does not significantly alter the strategy choices of the two generations of river chiefs, it does contribute to reducing system stabilization time. This study not only enriches the theoretical understanding of inter-generational responsibilities of government officials and sustainable environmental governance but also provides a theoretical foundation for the sustainable ecological management of urban inland rivers. By analyzing the impact of various factors on the strategic choices of river chiefs across generations, it offers insights into the internal mechanisms of urban inland river ecological governance. Furthermore, it supports local government administrative supervision departments in collaborating with the public to build a dual-layer multi-governance supervision system, facilitating continuous improvements in the ecological environment of urban inland rivers.

urban inland rivers  /  sustainable governance  /  inter-generational responsibility of river chiefs  /  reward and punishment mechanism  /  evolutionary game
申婧, 文清, 张敏, 张阳, 詹瑞, 何理. 河长代际责任下城市内河可持续治理机制研究. 中国环境科学, 2025 , 45 (3) : 1731 -1744 .
Jing SHEN, Qing WEN, Min ZHANG, Yang ZHANG, Rui ZHAN, Li HE. Exploring the inter-generational accountability of river chiefs in the sustainable management of urban inland rivers: A mechanistic approach[J]. China Environmental Science, 2025 , 45 (3) : 1731 -1744 .
自十八大以来,中国中央和地方政府高度重视城市黑臭内河治理,致力于实现“长治久清”.河长作为治理的关键角色,面临跨代合作和责任落实的挑战.城市内河治理的长期性、动态性和复杂性要求多代河长共同努力[1].然而,河长可能因代际机会主义[2]和制度短板[3]而未能有效承担治水责任,导致治理脱节.为确保河长落实代际责任,监督考核与奖惩机制至关重要[4].目前,河长治理工作监督以政府内部监督为主,缺乏预防性监督,难以促进河长承担代际责任.公众环保意识的提升为内部监督提供了补充,有助于形成内外共治的监督体系[5].面对河长代际衔接和政府监管的局限,研究代际河长、政府监督部门和公众之间的互动机制,对于制定有效政策、实现城市内河生态的可持续治理具有重要意义.
有关河长代际责任的研究相对较少,但政府官员代际责任与生态环境可持续治理的关系被广泛关注.研究表明,政府官员承担代际责任对于实现生态环境治理和保护至关重要[6].政府官员代际责任缺失会导致治理不善[7-9],且由于环境问题的滞后性[10]和累积效应[11],治理成本会跨代转移[10],产生代际负外部性[12].城市内河治理尤其需要考虑这一点,因为上代河长治理不善的问题可能在下代河长任期内显现[13].学者们普遍认同政府官员代际责任的缺失主要源于代际间成本与收益分配的不均衡[14-15].因此,政府在履行环境管理职能时,应将代际责任作为核心,通过整合责任管理、绩效管理和代际管理,以促进生态环境的可持续性治理[16].
现有研究指出,城市内河生态治理中的河长制存在缺乏危机压力、监督机制不透明[17]、晋升激励不足等问题[18],导致河长责任缺失[19],难以实现多代协同治理.为解决这一问题,一些学者建议从政府主导角度出发,实施目标管理责任制[20]、权力清单制[21]、终身责任制[22]和考核奖惩制[23]等,以促进官员主动承担代际责任.然而,现行的监督考核机制主要关注短期绩效[24-25],忽视了代际责任转移的负外部性[12],导致政策效果不佳.另一些学者则强调社会主体参与的重要性,认为社会监督能够弥补政府内部监督的不足,降低监管成本[26],并将公众评价纳入官员绩效考核,以完善代际责任追溯和补偿机制,提升政策质量和治理水平[27].
面对复杂的生态治理决策和利益关系,演化博弈理论能有效分析各主体在不完全信息下的决策互动[28].早期研究主要关注中央政府、地方政府、政府官员和企业中两类或三类[29-30]主体间的博弈.然而,生态环境可持续治理的复杂性要求政府与社会主体的相互配合.于是,学者们转而研究包含公众参与的三或四类决策主体间的演化博弈[31-32].以上研究均证实公众作为社会主体的重要力量,其参与监督和治理将有力推进监督体系的构建和推动政府主体的环境治理[33].但面对城市内河生态可持续治理中河长代际治理矛盾、政府内部监督有限的难题,河长代际治理、行政部门监督与公众参与的多主体研究框架有待探寻.
通过对以往研究成果梳理发现,现有研究多从定性角度探讨官员责任缺失与代际公平失衡问题,但在城市内河生态治理领域,缺乏定量研究来引导河长承担代际责任及探究可持续治理机制.此外,尚未有研究将代际河长、政府行政监督部门和公众纳入同一博弈框架,定量分析监督机制及各主体策略选择的影响因素.为此,本文构建了包含上代河长、下代河长、政府行政监督部门和公众的四方演化博弈模型,通过仿真分析研究各方治理力度、行动力度、奖罚力度及举报力度对系统稳定的影响,揭示河长与行政监督部门、公众间的微观互动机制,旨在为我国生态环境可持续治理提供政策建议和经验借鉴.
上代河长作为城市内河生态治理先驱,有义务统筹协调水利、环保、建设、国土、财政等政府部门的治水工作,担负水污染防治、水环境治理、水资源保护、水岸环境改善等基本责任.下代河长作为城市内河生态治理延续,在承担基本责任基础上,通过责任递补机制完成上代河长的交接任务.地方政府行政监督部门监督河长政策执行、水污染治理等治河工作,制定河长工作评价的考核指标,考核结果反映河长任职绩效,并依据结果执行奖惩措施.公众作为环境污染的直接受害者和重要外部监督力量,会自发对政府及其工作人员污染治理行为进行监督[34],当公众发现水岸设施长期管护不善、黑臭水体未整治到位等河长消极治理所致问题时,会向地方政府举报,行政监督部门也因公众的外部监督获得更及时、更准确的河长治理表现,纳入绩效考核.为深入分析城市内河生态治理过程上代河长、下代河长、政府行政监督部门和公众的博弈关系,通过对杭州市内10余位区级、街道级、乡镇级河道河长开展调研,提出如下基本假设.
假设1:博弈参与方均为有限理性,各参与主体根据自身意愿进行策略选择.博弈中上代河长、下代河长、政府行政监督部门和公众四个决策主体的策略集依次为(积极治理,消极治理)、(积极治理,消极治理)、(积极执行奖惩措施,消极执行奖惩措施)和(举报,不举报).假设上代河长选择积极治理策略的意愿为x,选择消极治理策略的意愿为1−x;下代河长选择积极治理策略的意愿为y,选择消极治理策略的意愿为1–y;政府行政监督部门选择积极执行奖惩措施的意愿为m,选择消极执行奖惩措施的意愿为1−m;公众选择举报策略的意愿为z,选择不举报策略的意愿为1−zxymz∈[0,1].
假设2:考虑责任河道上下两代河长的治理策略,两代河长为治理河道污染所共同付出时间、精力等综合成本C1(C1>0),分担比例为l(0<l<1),即上代河长积极治理成本为lC1,下代河长积极治理成本为(1-l)C1.借鉴孙伟增等[35]和陈婉婷等[36]的研究,参考台州市河长考核奖惩办法.若上代河长积极治理,取得良好治理效益,政府行政监督部门在年度考核中根据考核指标给上代河长打出较高考核评分,考核分反映河长的任职绩效并影响绩效奖励Vs(Vs>0),良好的任职绩效可能使上代河长在离任时得到晋升奖励,提高级别工资,记为收益R1(R1>0),以及社会收益E1.若上代河长消极治理,未改善水质,将得到较低考核评分,扣除基础绩效奖励Us(Us>0);并且不合格绩效可能使上代河长受到政治处罚,降低级别工资[37],记为损失S1(S1>0),以及社会声誉、公众信任损失H1.上代河长消极治理城市内河时,将治理成本用于其它在职工作可能获得机会成本T1;下代河长消极治理城市内河时,将治理成本用于其它在职工作可能获得机会成本T2.
假设3:由于上代河长和下代河长均可自由决定治理策略,策略组合会产生四种情境:
(1)情境PP(两代河长均积极治理):若上代河长积极治理,下代河长积极维系治理成效时因良好绩效得到较高考核评分,获得考核奖励,同时可能晋升带来级别工资收益R2(0<R2R1),以及社会收益E2.
(2)情境PN(上代河长积极治理,下代河长消极治理):若上代河长积极治理,而下代河长消极治理,导致责任河道“返黑返臭”,下代河长得到较低考核评分,扣除基础绩效奖励,并可能受到政治处罚,降低级别工资,记为损失S2(S2>0),以及社会声誉、公众信任损失H2.
(3)情境NP(上代河长消极治理,下代河长积极治理):若上代河长消极治理,而下代河长积极治理,下代河长为治理内河污染投入的力度为h,成本为hC1,解决污染问题在年度考核中得到较高考核评分,获得考核奖励,同时可能因晋升带来级别工资收益R3(R3>R2),以及社会收益E3(E3<E2).
(4)情境NN(两代河长均消极治理):若上代河长消极治理,未改善水质,而下代河长同样选择消极治理,导致责任河道污染加重,下代河长得到更低年度考核评分,扣除基础绩效奖励,并可能受到政治处罚,降低级别工资,记为损失S3(S3>0),以及社会声誉、公众信任损失H3(H3>H2).
假设4:政府行政监督部门执行监督、考核和奖惩措施成本为C2(C2>0),执行力度为q(0≤q≤1),用来衡量行政监督部门对奖惩力度的把控,当q=1时积极执行奖惩措施,行政监督部门积极执行时获得地方政府转移支付B[38].当公众举报时,河长被行政监督部门惩罚的力度提高至q'=q+a(1−q)[38];若河长消极治理且政府行政监督部门消极执行时被公众举报,政府行政监督部门公信力损失F.当河长积极治理时,政府行政监督部门享有环境收益E4;当河长消极治理时,政府行政监督部门承担环境损失H4.
假设5:公众作为城市内河生态环境污染的直接受害者,会自发对河流治理行为进行监督和举报,举报的时间、精力等成本为C3(C3>0).公众监督举报河长消极治理行为,监督部门给予其奖励R4;公众不举报将不会得到奖励.河长积极治理时,公众享有环境收益E5;河长消极治理时,公众承担环境损失H5.公众监督举报能有效提高政府行政监督部门信息收集的及时性和广泛性,增加河长惩罚力度,a为公众举报力度,0<a<1.
基于上述假设,构建上代河长、下代河长、政府行政监督部门和公众的四方演化博弈支付矩阵,如表1所示.
为简化运算,令:
上代河长选择积极治理的期望效用、消极治理的期望效用和种群效用分别为:
下代河长选择积极治理的期望效用、消极治理的期望效用和种群效用分别为:
政府行政监督部门选择积极执行奖惩措施的期望效用、消极执行奖惩措施的期望效用和种群效用分别为:
公众选择举报的期望效用、不举报的期望效用和种群效用分别为:
在演化博弈中,根据Malthusian方程,上代河长选择积极治理策略的增长率F(x)与它的相对期望效用和种群效用差成正比,得上代河长的复制动态方程.同理可得下代河长、政府行政监督部门和公众的复制动态方程,联立得四维动力系统(I):
根据四维动力系统(I),令F(x)=0,F(y)=0,F(m)=0,F(z)=0,可得到系统(I)的16个四种群纯策略均衡点,分别为(0,0,0,0)、(0,0,0,1)、(0,0,1,0)、(0,1,0,0)、(1,0,0,0)、(1,1,0,0)、(1,0,1,0)、(1,0,0,1)、(0,1,1,0)、(0,1,0,1)、(0,0,1,1)、(1,1,1,0)、(1,1,0,1)、(1,0,1,1)、(0,1,1,1)、(1,1,1,1)和一个可能存在的混合策略均衡点(x*y*m*z*),其存在条件为:x*y*m*z*∈(0,1).但由于演化稳定策略是渐进稳定策略的充要条件,为严格纳什均衡[39],而严格纳什均衡必须是纯策略均衡[40],故不对混合策略均衡做过多赘述.
根据Friedman提出的渐进稳定性分析方法,将系统(I)中各项复制动态方程分别xymz求一阶偏导得到系统(I)的Jacobian矩阵J,见(14).由李雅普诺夫稳定性理论可知,Jacobian矩阵的特征值可判断系统均衡点的渐进稳定性,当且仅当detJ>0和trJ<0时,该平衡点是(渐进)局部稳定的,即演化稳定策略(ESS),各均衡点所对应的雅克比矩阵特征值及其稳定性如表2所示.
为便于分析,令:
进一步假设l<l3为上代河长承担低治理成本,l3<l<l2<l1为上代河长承担较低治理成本,l3<l2<l<l1为上代河长承担较高治理成本,l>l1为上代河长承担高治理成本.
命题1:若l>l3,当−C3+R4<0且−(1−l)C1+E2+H2T2+<0时,系统演化稳定点为(1,0,0,0);当−[−(1−l)C1+E2+H2T2+<0时,系统演化稳定点为(1,1,0,0).此时−C2+B+qC2<0.
推论1:当上代河长承担低治理成本时,若下代河长积极治理可能获得的绩效奖励、提高的级别工资、社会收益与治理成本之差,大于消极治理时治理成本、损失之差,积极治理相对净收益大于0,下代河长会趋向于选择积极治理,反之,其会趋向于选择消极治理.说明下代河长的策略选择主要与自己的治理收益和机会成本有关.此时政府行政监督部门策略为消极执行奖惩措施,上代河长的积极治理策略并不会改变下代河长的策略选择,反而会增加其治理成本.因此,较高的治理成本和不确定的治理奖励和惩罚,无法激发两代河长治理热情,此时应该在制度层面鼓励行政监督部门开展考核和奖惩工作,充分调动河长治理积极性.
命题2:若l3<l<l2<l1,当−(1−l)C1+E2+<0时,系统演化稳定点为(1,0,0,1).若−(1−l)C1+E2+H2T2+<0,当−(−C2+B+qC2)<0且−C3+R4<0时,系统演化稳定点为(1,0,1,0);当−(−C2+B+qC2+F)<0且−(−C3+R4)<0时,系统演化稳定点为(1,0,1,1).若−[−(1−l)C1+E2+H2T2+R2+<0且−(−C2+B+qC2)<0,系统演化稳定点为(1,1,1,0).
推论2:当上代河长承担较低治理成本时,获得的绩效奖励、提高的级别工资、社会收益与积极治理成本之差,大于消极治理时较低的成本与扣除的绩效奖励、降低的级别工资、社会损失和公信力损失之差,积极治理相对净收益大于0,会趋向于选择积极治理.此时系统达到稳定点(1,1,1,0),这是由于政府行政监督部门积极监管并执行奖惩措施,基本形成较为完善的“积极治理—积极奖励、消极治理—积极惩罚”奖惩体系.在长期演化过程中,下代河长可能先选择消极治理以减少治理成本,但发现行政监督部门和公众建立起较为严格的奖惩体系后,消极治理会影响个人政治收益、经济收益和社会收益,因此从长远角度看,两代河长均会选择积极治理策略.结合情境PP,在此情况下,上代河长、下代河长和政府行政监督部门利益得以最大化,社会效益最高,城市内河生态环境得到有效改善和保护,公众享受到更美好的城市内河生态环境需要,倾向于不举报策略,是最理想的稳定状态.
命题3:若l3<l2<l<l1,当B+qC2C2<0且R4C3<0时,若–hC1+E3+H3T2+q(R3+)<0,系统演化稳定点为(0,0,0,0);若<0,系统演化稳定点为(0,1,0,0).当B+qC2+FC2 <0且−(−C3+R4 )<0时,若<0,系统演化稳定点为(0,0,0,1);若<0,系统演化稳定点为(0,1,0,1).
推论3:当上代河长承担较高治理成本时,若积极治理相对净收益小于0,会趋向于选择消极治理.以(0,0,0,0)为例,此时为情境NN,上代河长和下代河长没有得到积极治理的反馈或实质性奖励,出现“得不偿失”局面.虽然此时系统也可达到理想稳定点(1,1,1,0),且条件与命题2一致,但在公众举报力度提高时,能更快达到稳定点.因此,地方政府要助力行政监督部门奖惩开展工作,给予足够经费支持和财政补贴,促使行政监督部门完善考核评价体系,做到奖罚分明,提高两代河长均积极治理的意愿,同时借助公众力量完善监督奖惩制度.
命题4:若l>l1,当−hC1+E3+H3T2+R3+<0时,若−(−C2+B+qC2)<0且−C3+R4<0时,系统演化稳定点为(0,0,1,0);若−(−C2+B+qC2+F)<0且−(−C3+R4)<0时,系统演化稳定点为(0,0,1,1).当时,若−(−C2+B+qC2)<0且−C3+R4<0时,系统演化稳定点为(0,1,1,0);若−(−C2+B+qC2+F)<0且−(−C3+R4)<0时,系统演化稳定点为(0,1,1,1).
推论4:当上代河长承担高治理成本时,其积极治理相对净收益小于0,会趋向于选择消极治理,公众环境收益降低,下代河长治理成本升高,但在监管体系、奖惩体系逐渐完善下,下代河长有可能选择积极治理以避免过多损失,甚至得到治理收益.因此,河长必须为其消极治理行为付出更高代价,避免这一行为持续影响后代河长,引致后代河长更高的治理成本和更低的环境效益、社会效益.政府行政监督部门也应为此设立责任追究制度,为受影响的下代河长提供必要的保障来打破两代河长均消极治理的僵局.
如上文所述,城市内河生态可持续治理发展演化路径受上代河长、下代河长、政府行政监督部门与公众四方之间的多重策略情形选择及其参数变化影响,对此在Matlab R2022a环境下进行数值仿真.
假设上代河长、下代河长、政府行政监督部门和公众分别选择积极治理、积极治理、积极执行奖惩措施和举报策略的概率为[0.5,0.5,0.5,0.5],横坐标代表时间t,纵坐标代表各主体选择各自策略的概率p.模型需要赋初值的参数包括各博弈参与方的成本、不同情境下的绩效奖励、惩罚和级别工资等,其中C1C2RSVU是影响演化稳定的主要参数,其余参数可根据与主要参数的关系,以及相应的稳定性条件确定.参考梁平汉等[41]的研究,令内河综合治理成本C1=8.根据《杭州市财政局部门决算》数据,取2017~2021年5a一般行政管理事务支出数据的算术平均值作为C2的仿真初始值,令C2=19.8.根据《国务院关于改革公务员工资制度的通知》,取职级工资的差额平均值赋值,令R1=2,S1=2,根据《党政领导干部生态环境损害责任追究办法(试行)》和《浙江省公务员考核实施细则(试行)》,采用两级职级工资的差额平均值赋值,R2=1.5,R3=2,S2=1.5,S3=2.5,为了计算简便,本文不考虑任职年限等资历工资的影响.参考水利部《河长湖长履职规范(试行)》、《浙江省河湖长履职综合评价管理办法(试行)》和《台州市河长考核奖惩办法》,以考核激励金额和考核评价分为依据,结合研究假设和稳定性条件,令Vs=3,=3,=6,Us=1.5,=1.5,=2.根据稳定性条件,令C3=1,R4=2,B=10.5,F=2.
本文模型的关键模拟参数包括ahlq,取值范围均为[0,1],其中系数参数ahq按0.1的步长进行仿真,参数l按0.25的步长进行仿真.初始状态系统演化博弈仿真如图1所示,并以此图为基准.
可以发现,上代河长初期向消极治理方向演化,可能由于此时政府行政监督部门监督考核体系不完善、奖惩措施执行力度低及公众举报概率低,上代河长作为地方政府官员更愿意发展经济而忽略城市内河环境治理,但随着行政监督部门考核体系的完善和奖惩措施执行力度的增加,上代河长积极治理的概率迅速增加,并于t=8时接近稳定状态.政府行政监督部门向积极执行奖惩措施方向演进,可能考虑到为实现社会效益、环境收益最大化和作为行政监督部门的自觉性,积极执行奖惩措施以促进河长积极治理的概率逐渐升高,并于t=7时接近稳定状态.下代河长关注到上代河长治理绩效和政府行政监督部门奖惩措施的落实,首先即向积极治理方向演进,并于t=2时接近稳定状态.公众在上代河长消极治理的时段内会提高举报概率,但当其他主体都向良好方向发展时,公众逐渐倾向于不举报,系统于t=10时最终达到(积极治理,积极治理,积极执行奖惩措施,不举报)的理想稳定状态.
不同主体初始参与意愿变化对系统演化的影响均不同,图2表示各主体初始意愿由0.5提高至0.7和0.9时,对系统演化过程的影响.
上代河长初始意愿的提高使公众更快达到稳定点,但减缓了政府行政监督部门演化速度;下代河长初始意愿的提高仅降低公众举报概率,对其他主体达到稳定点的时间影响较小;政府行政监督部门初始意愿的提高加快了上代河长、下代河长和公众达到稳定点的时间,当政府行政监督部门的初始意愿大于0.9时,上代河长不会向消极治理策略进行演化,直接向积极治理策略演进;公众初始意愿的提高对其他主体的影响较小,仅略微加快了上代河长演化速度.
其余参数不变,改变两代河长积极治理责任河道的综合治理成本C1,分别令C1=5和C1=11,策略演化博弈过程及结果如图3所示.
图3(b)显示C1=8时的初始策略仿真,对比图3(a)和图3(b)可知,随着C1的减少,上代河长和公众趋向积极治理的时间缩短,分别于t=4时和t=7时接近稳定状态,下代河长向积极治理的趋势少许加快,政府行政监督部门趋向积极执行奖惩措施的时间少许延长,于t=8时接近稳定状态,加快达到情境PP.
对比图3(b)和图3(c)可知,随着C1的增加,上代河长改变自身策略选择消极治理,下代河长向积极治理的趋势少许减缓,政府行政监督部门趋向积极执行奖惩措施的时间略有缩短,于t=3时接近稳定状态,公众改变自身策略选择举报,出现情境NP.因此,根据污染状况合理安排河长任期治理任务,控制河长治河成本,及时根据治理需要为其提供政策资源;并完善奖惩措施,促使情境NP向情境PP转换,有利于系统整体长远的发展.
其余参数不变,仅改变成本分担比例l和下代河长治理力度h,成本分担比例体现代际合作治理中的代际公平,下代河长治理力度是为体现上代河长未积极治理时,下代河长治污投入力度,令l分别为0.25、0.5、0.75,并在图3(c)情境NP时,令h分别为0.1、0.5、0.9,策略演化博弈过程及结果如图4图5所示.
图4显示l从0.25~0.75时的策略仿真,随着l的提高,上代河长由积极治理转向消极治理,下代河长由消极治理转向积极治理,政府行政监督部门策略基本不变,公众举报概率随河长趋向消极治理而上升.结合图5,当上代河长消极治理时,下代河长治理污染需投入的力度h越多,下代河长趋于稳定的时间越长,且由于上代河长消极治理带来的公信损失,公众一直趋向举报策略.
其余参数不变,改变政府行政监督部门执行力度q,行政监督部门执行力度体现在对两代河长治理工作监督考核评价的全面性和奖惩措施的落实程度,分别令q=0.3和q=0.7,策略演化博弈过程及结果如图6所示.
图6(b)显示q=0.5时的初始策略仿真,对比图6(a)和图6(b)可知,随着q的减少,政府行政监督部门趋向消极执行奖惩措施,于t=3时接近稳定状态,上代河长和下代河长改变自身策略选择消极治理,分别于t=2时和t=9时接近稳定状态,公众改变自身策略选择举报,出现情境NN.
对比图6(b)和图6(c)可知,随着q的提高,政府行政监督部门趋向积极执行奖惩措施的时间明显缩短,于t=1时接近稳定状态,上代河长和下代河长趋向积极治理的速度明显加快,分别于t=6和t=2时接近稳定状态,此时能更快达到情境PP.原因在于政府行政监督部门提高工作效率,以更完善的考核评价体系检查河长治理工作并严格落实奖惩措施,会增加震慑力,使河长自觉加大治理力度.
其余参数不变,改变公众举报力度a,公众举报力度体现在公众参与外部监督的程度和积极性,令a=0.9,策略演化博弈过程及结果如图7所示.
图7显示a从0.5变化至0.9时的策略仿真,随着a的提高,上代河长趋向积极治理的速度加快,公众举报峰值降低,有助于达到情境PP.但图8显示公众不举报时其余主体策略向数值1演进,说明公众举报对系统演化的影响和作用有限,这符合实际情况,这是因为单一民众力量薄弱,必须依靠其他主体才能实现诉求.
其余参数不变,分别仅改变上代河长的绩效奖励Vs和级别工资R1,令Vs=4,R1=3;仅改变下代河长的绩效奖励和级别工资R2,令=4,R2=2.5;以及在图3(c)情境NP时,仅改变下代河长的绩效奖励和级别工资R3,令=7,R3=3,策略演化博弈过程及结果如图9所示.
图9(a)显示仅提高Vs至4,R1至3时的策略仿真,上代河长趋向积极治理的速度显著加快,于t=3时接近稳定状态,而下代河长和政府行政监督部门的演化趋势却有所放缓,公众举报峰值降低.结合图9(b),仅提高至4,R2至2.5时,上代河长、政府行政监督部门和公众的演化趋势未见明显变化,下代河长趋向积极治理的速度略微加快.图9(c)显示情境NP下仅提高至7,R3至3时的策略仿真,明显可见下代河长趋向积极治理的速度有所加快.因此,在上代河长消极治理时,一定程度增加下代河长的绩效奖励和级别工资能有效激励下代河长积极治理,是破解情境NP的关键.
其余参数不变,分别仅改变上代河长的绩效扣除Us和级别工资S1,分别令Us=3,S1=3;在图4(a)情境PN时,仅改变下代河长的绩效扣除和级别工资S2,分别令=3,S2=3;以及在图6(a)情境NN时,仅改变下代河长的绩效奖励和级别工资S3,分别令=4,S3=4,策略演化博弈过程及结果如图10所示.
图10(a)显示仅提高Us至3,S1至3时的策略仿真,上代河长趋向积极治理的速度显著加快,于t=2.5时接近稳定状态,下代河长和政府行政监督部门的演化趋势有所放缓,公众举报峰值明显降低.图10(b)显示情境PN下仅提高至3,S2至3时的策略仿真,上代河长演化趋势未见明显变化,下代河长由消极治理转向积极治理,公众由举报转向不举报,政府行政监督部门的演化趋势有所放缓.结合图10(c),情境NN下仅提高至4,S3至4时,上代河长和政府行政监督部门演化趋势未见明显变化,下代河长由消极治理转向积极治理.由此可见,下代河长的治理策略并不会对上代河长造成影响,而无论上代河长的治理策略如何,提高下代河长消极治理的惩罚,能促使下代河长积极治理,但由于仅提高惩罚,未提高奖励激发下代河长治理积极性,达到理想状态的时间有所延长,这也证明仅提高惩罚较为片面,应奖惩结合.
结合博弈提出的河长代际治理基本假设,构建上代河长、下代河长、政府行政监督部门和公众的四方博弈模型,探究初始策略和不同代际情境下,各参数变化对两代河长治河的影响及程度大小.研究结论如下:(1)调节博弈方的参与意愿能够影响系统趋稳时间.相比于下代河长,上代河长的行为受政府行政监督部门意愿的影响较大;两代河长在时空演进下对彼此的影响不对称,下代河长对上代河长的意愿变化尤为敏感.(2)过高的治理成本和不合理的成本代际分担比,会影响两代河长的策略选择.随着治理成本的增加,上代河长和下代河长均呈现出消极治理意愿.成本分担比例的减少虽然减轻上代河长治理负担,但会促使下代河长选择消极治理策略,造成治理断档现象.(3)政府行政监督部门执行力度增加会不同程度地缩短系统趋稳时间,对两代河长均影响显著.(4)绩效奖励额、绩效惩罚额以及级别工资变化会不同程度地影响系统趋于稳定的时间.绩效奖励额和绩效惩罚额的增加对两代河长均影响显著,但相比于绩效奖惩的弹性,级别工资变化对两代河长策略选择影响有限.(5)提高公众举报力度对两代河长策略选择影响虽不显著,但在一定程度上缩短系统趋稳时间.
第一,完善监督考核机制,强化考核应用.地方政府行政监督部门应加强监督人员培训,提高监管专业化水平;加强与河长制办公室、环保部门和执法部门等部门的配合并建立互联互通的信息共享网络,加强事前事中监督;通过考核评分与绩效奖金和任职绩效的联立强化考核结果运用,并完善终身责任制的追责形式(图11),在制度上杜绝河长在任期内出现的不担当、不作为.同时,地方政府应支持行政监督部门的工作,提高对行政监督部门的专项资金支持,也应加强信息公开,推动监督机制的透明化和公开化,拓宽公众举报渠道、提高公众举报奖励,重视公众在外部监督中发挥的重要作用,完善现有监督体系.
第二,积极建立奖惩机制,激发河长治理积极性.绩效奖励应体现在事前事中事后全过程监管和如何保证代际延续治理上,根据河长任期内具体任务和考核指标制定绩效奖励,提高上代河长消极治理而下代河长积极治理时下代河长的奖励额度.行政监督部门须遵从“奖罚分明”的原则,在处罚方面,构建完善的考核评分和相应评价等级,依据等级确定处罚类型,且设定较高的处罚成本.对于治理绩效略低的河长选择扣除绩效处罚,对治理绩效较差,产生严重不良后果和影响下代河长治理的河长除扣除绩效处罚外,应进行政治处罚,降低级别,发挥惩罚制度的震慑作用.同时进一步加大激励支持力度,充分激发和调动河长工作的积极性、主动性和创造性,尤其对治理绩效突出的河长在绩效奖励时予以适当倾斜,增强激励效果.
第三,建立健全责任递补机制和交接班制度,构建城市内河生态长效治理格局.每代河长应在自身任期内基于生态现状挖掘城市内河污染深层次原因;行政监督部门联合河长制办公室引导每代河长治水策略的制定,尤其是上代河长在预期宏观目标下制定科学准确的治理方案,能为下代河长治理提供基本方向,实现代际责任递补.同时,以交接班制度为“纽带”引导上代河长将整治方案、修复进度等工作情况移交给下代河长,而下代河长在此基础上基于生态现状和治理经验调整行动布局、更新治理理念(图11),以局部代际响应形成基于河长代际责任的城市内河生态可持续治理机制.
本文在处理复杂的河长代际责任关系时,未从不同社会群体参与程度和影响差异这一视角出发,考虑不同社会群体对河长承担代际责任的影响,可能无法准确反映公众在实际治理中的动态作用.因此,引入不同社会群体作为博弈主体将是未来进一步研究的方向.
  • 浙江省哲学社会科学规划课题资助项目(20NDQN295YB)
  • 浙江省哲学社会科学规划课题资助项目(20NDQN296YB)
  • 国家自然科学基金资助项目(72104225)
  • 国家自然科学基金资助项目(72004212)
  • 国家重点研发计划项目(2023YFC3705900)
  • 国家社会科学基金资助项目(24BJY127)
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2025年第45卷第3期
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  • 接收时间:2024-08-09
  • 首发时间:2026-03-18
  • 出版时间:2025-03-20
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  • 收稿日期:2024-08-09
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浙江省哲学社会科学规划课题资助项目(20NDQN295YB)
浙江省哲学社会科学规划课题资助项目(20NDQN296YB)
国家自然科学基金资助项目(72104225)
国家自然科学基金资助项目(72004212)
国家重点研发计划项目(2023YFC3705900)
国家社会科学基金资助项目(24BJY127)
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    1.中国计量大学经济与管理学院,浙江 杭州 310018
    2.天津大学,水利工程仿真与安全国家重点实验室,天津 300072

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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