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辽宁省海洋渔业碳收支及驱动因素分析

李源 李田慧 梁金水 李发祥 刘长发

李源, 李田慧, 梁金水, 李发祥, 刘长发. 辽宁省海洋渔业碳收支及驱动因素分析[J]. 中国生态农业学报 (中英文), 2023, 31(2): 253−264 doi: 10.12357/cjea.20220542
引用本文: 李源, 李田慧, 梁金水, 李发祥, 刘长发. 辽宁省海洋渔业碳收支及驱动因素分析[J]. 中国生态农业学报 (中英文), 2023, 31(2): 253−264 doi: 10.12357/cjea.20220542
LI Y, LI T H, LIANG J S, LI F X, LIU C F. Carbon budget and driving factors in marine fisheries in Liaoning Province, China[J]. Chinese Journal of Eco-Agriculture, 2023, 31(2): 253−264 doi: 10.12357/cjea.20220542
Citation: LI Y, LI T H, LIANG J S, LI F X, LIU C F. Carbon budget and driving factors in marine fisheries in Liaoning Province, China[J]. Chinese Journal of Eco-Agriculture, 2023, 31(2): 253−264 doi: 10.12357/cjea.20220542

辽宁省海洋渔业碳收支及驱动因素分析

doi: 10.12357/cjea.20220542
基金项目: 辽宁省高校优秀科技人才支持计划(LR2013035)资助
详细信息
    作者简介:

    李源, 主要从事生态资产研究。E-mail: dlouly5205@163.com

    通讯作者:

    刘长发, 主要从事污染物环境生物地球化学过程与控制研究。E-mail: liucf@dlou.edu.cn

  • 中图分类号: F326.4

Carbon budget and driving factors in marine fisheries in Liaoning Province, China

Funds: This study was supported by the Program for Liaoning Excellent Talents in University (LR2013035).
More Information
  • 摘要: 海洋渔业碳汇是海洋碳汇的主要组成部分, 是实现海洋碳增汇的有效途径之一。在碳达峰与碳中和背景下, 海洋渔业兼具“碳源”与“碳汇”的双重属性。利用《中国渔业统计年鉴》《国内机动渔船油价补助用油量测算参考标准》和《中国统计年鉴》数据, 计算了2006—2020年辽宁省渔业净碳汇量和渔业碳汇价值量; 运用时间序列三次指数平滑模型, 预测2021—2030年渔业碳汇量和渔业碳汇价值量; 基于灰色关联模型分析了辽宁省海洋渔业碳源碳汇量变化及其价值量变化的主要驱动要素。结果表明: 2006—2020年辽宁省海洋渔业碳汇收支盈余态势逐年减少, 海洋渔业碳汇赤字情况逐年加剧, 海洋渔业碳源碳汇最大顺差为256.36万t, 最大逆差29.99万t, 其平均差额为116.66万t·a−1。其中, 海洋捕捞鱼类碳汇总量3976.04万t, 但自2016年起急剧下降, 并呈持续下降趋势; 贝藻类碳汇总量241.67万t, 养殖占83%, 变化不大; 海洋捕捞碳排放量为164.52万t·a−1, 其中拖网捕捞渔业占比近50%。2017年后海洋捕捞碳汇量不能补偿碳排放量。辽宁省海洋渔业碳汇价值总量274.23亿元, 年均18.28亿元。辽宁省渔业碳汇总量和渔业碳汇价值总量持续下降, 碳汇价值量与碳汇量呈正相关。海洋渔业碳汇量与海洋捕捞渔获物产量、养殖贝藻类产量呈正相关。基于时间序列预测模型分析显示, 2020—2030年辽宁省海洋渔业碳汇赤字将持续加剧, 海洋渔业碳汇量逐年降低。辽宁省海洋渔业碳汇受国家政策、捕捞渔获物产量、从业人员数量、贝藻类养殖面积和海洋捕捞渔船总功率等因素影响。辽宁省海洋渔业碳源排放量受海洋捕捞渔船总功率、渔业专业户数量和技术推广机构数量影响明显。建议多种养殖方式深度融合, 减少高能耗、低产量捕捞作业方式, 保护海洋生物多样性, 并加强高排放渔船监管, 以促进辽宁省海洋渔业发展。
  • 图  1  辽宁省2006—2020年捕捞鱼类碳汇量

    Figure  1.  Carbon sink of fish catched in Liaoning Province from 2006 to 2020

    图  2  辽宁省2006—2020年不同种类(a)和不同生产方式(b)的贝藻类碳汇量

    Figure  2.  Carbon sinks of different species shellfish and macroalgae (a) with different production methods (b) in Liaoning Province from 2006 to 2020

    图  3  辽宁省2006—2020年海洋捕捞不同作业方式碳排放量

    Figure  3.  Carbon emissions of different marine fishing operations in Liaoning Province from 2006 to 2020

    图  4  辽宁省2006—2020年海洋捕捞碳源碳汇

    Figure  4.  Source and sink of carbon from marine fishing in Liaoning Province from 2006 to 2020

    图  5  辽宁省2006—2020年海洋渔业碳汇价值量

    Figure  5.  Economic values of carbon sequestration of harvested marine products in Liaoning Province from 2006 to 2020

    表  1  辽宁省海洋渔业碳汇计算公式

    Table  1.   Calculation formula of marine fishery carbon sink in Liaoning Province

    类别
    Category
    公式
    Formula
    符号说明
    Symbol description
    参考文献
    Reference
    贝类碳汇
    Carbon sink of shellfish
    1 Ci=Qi×γ×µ1×ρ1+Qi×
      γ×µ2×ρ2
    $ {C}_{i} $为第i种贝类碳汇量; $ {Q}_{i} $为第i种贝类年总产量; $ \gamma $为贝类干湿转换系数; $ {\mu }_{1} $为贝壳比; $ {\rho }_{1} $为贝壳固碳系数; $ {\mu }_{2} $为软组织比; $ {\rho }_{2} $为软组织固碳系数, 参数取值见表2
    $ {C}_{i} $ is the carbon fixed by i shellfish; $ {Q}_{i} $ is the annual yield of i shellfish; $ \gamma $ is the conversion coefficient wet to dry weight of shellfish; $ {\mu }_{1} $ is the ratio of shell to body weight; $ {\rho }_{1} $ is the carbon fixation coefficient of shell; $ {\mu }_{2} $ is the ratio of soft tissue to body weight; $ {\rho }_{2} $ is the carbon fixation coefficient of soft tissue, whose value is shown in the table 2
    [4]
    贝类碳汇总量
    Total carbon sink of shellfish
    2 ${C}_{{\rm{s}}}=\displaystyle\sum _{i=1}^{n}{C}_{i}$ ${C}_{{\rm{s}}}$为海水养殖贝类碳汇总量
    ${C}_{{\rm{s}}}$ is the total amount of carbon of maricultured shellfish
    藻类碳汇
    Carbon sink of macroalgae
    3 $ {C}_{{\rm{e}}}=\displaystyle\sum _{i=1}^{m}\left({P}_{i}\times {W}_{i}\right)\times 20 {\text{%}} $ $ {C}_{{\rm{e}}} $为不同种类藻类碳汇总量; $ {P}_{i} $为i种藻类的年总产量; $ {W}_{i} $为i种藻类的碳含量百分比, 参数取值见表3
    $ {C}_{{\rm{e}}} $ is the carbon fixed by maricultural macroalgae; $ {P}_{i} $ is the annual harvest of i macroalgae; $ {W}_{i} $ is the percentage of carbon by i macroalgae, whose value is shown in the table 3
    贝藻类碳汇总量
    Total carbon sink of shellfish and macroalgae
    4 $ C={C}_{{\rm{e}}}+{C}_{{\rm{s}}} $ $ C $为海水养殖贝藻类年碳汇总量
    $ C $ is the annual carbon totals by maricultural shellfish and macroalgae
    鱼类营养级
    Fish nutritional level
    5 ${T}_{i}=1+\displaystyle\sum _{j=1}^{n}{D}_{i j}\times {T}_{j}$ $ {T}_{i} $为生物i的营养级; $ {T}_{j} $为生物i摄食的食物j的营养级; ${D}_{i j}$为食物j在生物i的食物中所占的比例
    $ {T}_{i} $ is the trophic level of i fish; $ {T}_{j} $ is the trophic level of j organism being fed on i fish; ${D}_{i j}$ is the proportion of j prey in the food of i predator
    [29]
    被捕食者生物量
    Biomass of prey
    6 ${B}_{j}={Y}_{0} /\left({E}_{ {L}_{0}-1}\times {E}_{ {L}_{0}-2}\right)$ ${B}_{j} $为被捕食者的生物量; $ {Y}_{0} $为渔获量; $ {L}_{0} $为渔获物平均营养级; $ {E}_{{L}_{0}-1} $为营养级$ ({L}_{0}-1) $的生态转换效率; $ {E}_{{L}_{0}-2} $为营养级$ ({L}_{0}-2) $的生态转换效率
    ${B}_{j} $ is the biomass of the prey; $ {Y}_{0} $ is the yield; $ {L}_{0} $ is the average trophic level in catch; $ {E}_{{L}_{0}-1} $ is the ecological conversion efficiency of trophic level $ ({L}_{0}-1) $; $ {E}_{{L}_{0}-2} $ is the ecological conversion efficiency of trophic level $ ({L}_{0}-2) $
    [14]
    摄食浮游植物和有机碎屑的比例
    Proportion of phytoplankton and organic detritus in diet
    7 1×Q+2×(100%−Q) =
      L0−2, 即Q = 4−L0
    $ Q $为摄食浮游植物和有机碎屑的比例; L0为渔获物平均营养级
    $ Q $ is the proportion of phytoplankton and organic detritus in diet. L0 is the average trophic level in catch
    摄食浮游植物和有机碎屑的生物量
    Biomas of phytoplankton and organic detritus in diet
    8 B0=(B1×Q)+B1×
      (100%−Q)/EL=1
    $ {B}_{0} $为摄食浮游植物和有机碎屑的生物量; $ {E}_{L=1} $为初级消费者摄食浮游植物和有机碎屑的生态转换效率
    $ {B}_{0} $ is the biomass of phytoplankton and organic detritus in diets; $ {E}_{L=1} $ is the ecological conversion efficiency of primary consumers to ingest phytoplankton and organic detritus
    被捕食的浮游植物碳含量
    Carbon content of phytoplankton
    9 $ {C}_{1}=4.49 {\text{%}}\times {B}_{0} $ $ {C}_{1} $被捕食的浮游植物的现存碳含量
    $ {C}_{1} $ is the carbon content of phytoplankton
    [30]
    摄食浮游植物固碳量
    Carbon sequestration by feeding phytoplankton
    10 $ {C}_{\mathrm{T}}=45\times {C}_{1} $ $ {C}_{\mathrm{T}} $摄食浮游植物的固碳量
    $ {C}_{\mathrm{T}} $ is the carbon sequestration by feeding phytoplankton
    [31]
    化石燃料燃烧排放CO2
    CO2 emissions from fossil fuel combustion
    11 $ {G}_{k}={T}_{k}\times f\times h $ $ {G}_{k} $为渔船燃烧k燃料时的碳排放量; $ {T}_{k} $为消耗k燃料的量; f为有效氧化分数, h为燃料k的平均含碳量
    $ {G}_{k} $ is the carbon emissions of fishing vessels burning k fuel; $ {T}_{k} $ is the amount of k fuel consumed; f is the effective oxidation fraction; h is the average carbon content of k fuel
    [32]
    海洋渔船产碳量
    Carbon production of marine fishing vessel
    12 ${G}_{n}={T}_{n}\times s\times w\times z\times \varphi$ $ {G}_{n} $为渔船燃烧碳量; $ {T}_{n} $为渔船作业燃油消耗量; s为折标准煤系数1.4571; w为有效氧化分数0.982; z为每吨标煤含碳量0.732 57; $\varphi$为0.813, 即在获得相同热能的条件下, 燃油释放CO2与燃煤释放CO2之间的比值
    $ {G}_{n} $ is the amount of carbon burned by n fishing vessels; $ {T}_{n} $ is the fuel consumption of fishing vessel n operation; s is the standard coal coefficient (1.4571); w is the effective oxidation fraction (0.982); z is the carbon content per ton of standard coal (0.732 57); $\varphi$ is 0.813, the ratio of CO2 released between from fuel oil and from coal under the same thermal energy conditions
    [33]
    海洋捕捞渔船CO2排放量
    CO2 emissions from marine fishing vessels
    13 ${C}_{ {\mathrm{c}\mathrm{o} }_{2} }={G}_{n}\times \partial$ $ {C}_{{\mathrm{c}\mathrm{o}}_{2}} $为$ {\mathrm{C}\mathrm{O}}_{2} $排放量; $ \partial $为碳换算为CO2的常数(3.67)
    $ {C}_{{\mathrm{c}\mathrm{o}}_{2}} $ is the $ {\mathrm{C}\mathrm{O}}_{2} $ emission; $ \partial $ is the constant from carbon to carbon dioxide (3.67)
    燃油消耗量
    Fuel consumption
    14 $ {T}_{n}={\displaystyle\sum }_{j=1}^{m}\left({P}_{j}{\times F}_{j}\right) $ $ {P}_{j} $为海洋捕捞$\mathrm{作}\mathrm{业}\mathrm{功}\mathrm{率},{F}_{j}$为海洋捕捞作业${用}{油}{系}{数}$
    $ {P}_{j} $ is the power of j marine fishing operation; $ {F}_{j} $ is the oil consumption coefficient of j marine fishing operation
    渔业碳汇价值量预测
    Prediction of economic value of carbon sink by fisheries
    15 ${Y}_{t+T}={A}_{t}+{B}_{t}+{C}_{t}\times {T}^{2}$ $ {Y}_{t+T} $为碳汇量预测值; T为预测期数; $ {A}_{t} $、$ {B}_{t} $、$ {C}_{t} $分别为t年预测系数; $ {L}_{t}^{\left(1\right)} $、$ {L}_{t}^{\left(2\right)} $、$ {L}_{t}^{\left(3\right)} $分别为t年一次、二次、三次平滑预测值; $ \omega $为平滑系数; $ {X}_{t} $为t年碳汇量原始值; $ {L}_{0}^{\left(1\right)} $、$ {L}_{0}^{\left(2\right)} $、$ {L}_{0}^{\left(3\right)} $分别为$ {L}_{t}^{\left(1\right)} $、$ {L}_{t}^{\left(2\right)} $、$ {L}_{t}^{\left(3\right)} $的初始值
    $ {Y}_{t+T} $ is the predicted value of carbon sinks; T is the forecast period; $ {A}_{t} $, ${B}_{t}\;and\;$ $ {C}_{t} $ are t year prediction coefficients; $ {L}_{t}^{\left(1\right)} $, $ {L}_{t}^{\left(2\right)} $ and $ {L}_{t}^{\left(3\right)} $ are the first, second and third smoothing predictions in t year, respectively; $ \omega $ is the smoothing coefficient; $ {X}_{t} $ is the original value of the carbon sink in t year; $ {L}_{0}^{\left(1\right)} $, $ {L}_{0}^{\left(2\right)} $, and $ {L}_{0}^{\left(3\right)} $ are the initial values of $ {L}_{t}^{\left(1\right)} $, $ {L}_{t}^{\left(2\right)} $, and $ {L}_{t}^{\left(3\right)} $, respectively
    [34-35]
    $ {A}_{t}=3{L}_{t}^{\left(1\right)}-3{L}_{t}^{\left(2\right)}+{L}_{t}^{\left(3\right)} $
    $B_t={\dfrac{\omega }{2\left(1-\omega \right)^2 }}$$\left[\left(6-5\omega \right){L}_{t}^{\left(1\right)}-2\left(5-4\omega \right){L}_{t}^{\left(2\right)}+\left(4-3\omega \right){L}_{t}^{\left(3\right)}\right] $
    $ {C}_{t}=\dfrac{\omega ^2}{2\left(1-\omega \right)^2}\left[{L}_{t}^{\left(1\right)}-2{L}_{t}^{\left(2\right)}+{L}_{t}^{\left(3\right)}\right] $
    $ {L}_{t}^{\left(1\right)}=\omega {\times X}_{t}+\left(1-\omega \right)\times {L}_{t-1}^{\left(1\right)} $
    $ {L}_{t}^{\left(2\right)}=\omega {\times L}_{t}^{\left(1\right)}+\left(1-\omega \right)\times {L}_{t-1}^{\left(2\right)} $
    $ {L}_{t}^{\left(3\right)}=\omega {\times L}_{t}^{\left(2\right)}+\left(1-\omega \right){\times L}_{t-1}^{\left(3\right)} $
    $ {L}_{0}^{\left(1\right)}={L}_{0}^{\left(2\right)}={L}_{0}^{\left(3\right)}=\dfrac{{X}_{1}+{X}_{2}+{X}_{3}}{3} $
    渔业碳汇价值
    Economic value of fishery carbon sink
    16 ${O}_{_ {\rm{CSV} } }={O}_{_ {\rm{FS} } }\times {C}_{ {\rm{rec} } }$ ${O}_{_ {\rm{CSV} } }$为渔业碳汇价值量, ${O}_{_ {\rm{FS} } }$为渔业碳汇量, $ {C}_{{\rm{rec}}} $为单位的碳减排经济成本价值
    ${O}_{_ {\rm{CSV} } }$ is the value of fishery carbon sink; ${O}_{_ {\rm{FS} } }$ is the amount of fishery carbon sink; $ {C}_{{\rm{rec}}} $ is the economic cost value of carbon emission reduction per unit
    [36-39]
    关联系数
    Correlation coefficient
    17 $\delta_{i j}=\dfrac{\min _j \times \min _k \times \Delta_{i j}(k)+\beta \times \max _j \times \max _k \times \Delta_{i j}(k)}{\Delta_{i j}(k)+\beta \times \max _j \times \max _k \times \Delta_{i j}(k)}$ $\delta_{i j} $为灰色关联系数; $\Delta_{ i j}\left(k\right)={x}_{i}\left(k\right)-{x}_{j}\left(k\right)$为序列i$ \left\{{x}_{i}\left(k\right)\right\} $与序列j$ \left\{{x}_{j}\left(k\right)\right\} $在第k点的绝对差; ${\min}_{j}\times{\min}_{k}\times{\Delta }_{ij}\left(k\right)$为两极最小差; ${\max}_{j}\times{\max}_{k}\times{\Delta }_{ij}\left(k\right)$为两极最大差; $ \beta $为分辨系数, 其值为 0~1, 取$ \beta $ = 0.5
    $\delta_{i j} $ is grey correlation coefficient; $\Delta_{ i j}\left(k\right)={x}_{i}\left(k\right)-{x}_{j}\left(k\right)$ is the absolute difference between sequence i$ \left\{{x}_{i}\left(k\right)\right\} $ and sequence j$ \left\{{x}_{j}\left(k\right)\right\} $ at point k; ${\min}_{j}\times{\min}_{k}\times{\Delta }_{ij}\left(k\right)$ is the minimum difference between two poles; ${\max}_{j}{\max}_{k}{\Delta }_{ij}\left(k\right)$ is the maximum difference between the two poles; $ \beta $ is the resolution coefficient, whose value is 0.5
    [40-41]
    灰色关联度
    Grey correlation
    18 $ {R}_{ij}=\dfrac{1}{n}\displaystyle\sum _{k=1}^{n}{\delta }_{ij}\left(k\right)k=\mathrm{1,2},3,\cdots ,n $ Rij为灰色关联度
    Rij is the grey correlation degree
    下载: 导出CSV

    表  2  海水养殖贝类固碳计算参数

    Table  2.   Calculation parameters of carbon sequestration in mariculture shellfish

    种类
    Shellfish
    干重比
    Dry weight ratio (%)
    质量比 Mass ratio (%)碳汇系数 Carbon sink coefficient (% dry weight)
    软体组织 Soft tissue贝壳 Shell软体组织 Soft tissue贝壳 Shell
    牡蛎 Oyster65.106.1493.8645.8912.68
    贻贝 Mussel75.288.4791.5344.4011.76
    扇贝 Scallop63.8914.3585.6543.9011.40
    蛤 Clam52.551.9898.0244.9011.52
    蛏 Razor clam70.483.2696.7444.9013.24
    其他贝类 Other shellfish64.2111.4188.5943.8711.44
    下载: 导出CSV

    表  3  海水养殖藻类固碳计算参数(藻类干重比为20%)

    Table  3.   Calculation parameters of carbon sink in mariculture macroalgae (dry weight ratio of algae is 20%)

    种类
    Macroalgae
    碳汇系数
    Carbon sink coefficient (% dry weight)
    海带 Kelp31.20
    裙带菜 Wakame26.40
    其他藻类 Other algae27.76
    下载: 导出CSV

    表  4  辽宁省2006—2020年不同鱼类碳汇量

    Table  4.   Carbon sinks of different fish species catched in Liaoning Province from 2006 to 2020

    次序
    Order
    鱼类
    Fish species
    碳汇量
    Carbon sink
    次序
    Order
    鱼类
    Fish species
    碳汇量
    Carbon sink
    ×104 t 
    1小黄鱼 Larimichthys polyactis1017.4914竹筴鱼 Trachurus japonicus28.05
    2鲅鱼(蓝点马鲛) Scomberomorus niphonius835.2715沙丁鱼 Sardina pilchardus23.08
    3鳀鱼 Engraulis japonicus620.1716白姑鱼 Argyrosomus argentatus19.64
    4鲐鱼(日本鲭) Scomber japonica479.9117鮸鱼 Miichthys miiuy10.03
    5大黄鱼 Larimichthys crocea295.2218金枪鱼 Thunnus thynnus9.18
    6带鱼 Trichiutus lepturus228.9419马面鲀 Navodon modestus8.45
    7梭鱼 Liza haematocheila107.4820海鳗 Muraenesox cinereus7.19
    8梅童鱼 Collichthys lucidus64.9221鳓鱼 Ilisha elongata3.85
    9玉筋鱼 Ammodytes personatus61.8322金线鱼 Nemipterus virgatus2.14
    10鲻鱼 Mugil cephalus39.9123方头鱼 Branchiostegus japonicus1.83
    11黄姑鱼 Nibea albiflora38.5124鲷鱼 Pagrus pagrus0.93
    12石斑鱼 Epinephelus sp.36.7925蓝圆鯵 Decapterus maruadsi0.24
    13鲳鱼 Pampus gargenteus34.8026鲱鱼 Clupea pallasi0.17
    下载: 导出CSV

    表  5  辽宁省2006—2020年海洋渔业碳源和碳汇的驱动要素

    Table  5.   Driving factors for carbon sources and carbon sinks of marine fisheries in Liaoning Province from 2006 to 2020

    碳源 Carbon source碳汇 Carbon sink
    评价项
    Evaluation item
    关联度Correlation排名Ranking评价项
    Evaluation item
    关联度 Correlation排名Ranking
    渔业占农业产值比重
    Proportion of fishery in agricultural output value
    0.9381捕捞产量
    Catch yield
    0.9501
    海洋捕捞渔船总功率
    Total power of marine fishing vessels
    0.9352技术推广机构数量
    Number of technology extension agencies
    0.8882
    渔业专业户数量
    Number of specialized fishery households
    0.9193海洋捕捞渔船总功率
    Total power of marine fishing vessels
    0.8623
    专业从业人员数量
    Number of employees
    0.8894渔业专业户数量
    Number of specialized fishery households
    0.8624
    技术推广机构数量
    Number of technology extension agencies
    0.8565专业从业人员数量
    Number of employees
    0.8515
    海水养殖面积
    Mariculture area
    0.8486渔业占农业产值比重
    Proportion of fishery in agricultural output value
    0.8456
    渔业经济总产值
    Gross economic output value of fisheries
    0.8477海水养殖面积
    Mariculture area
    0.8117
    渔民人均纯收入
    Net income per fisherman
    0.8288渔业经济总产值
    Gross economic output value of fisheries
    0.7948
    捕捞产量
    Catch yield
    0.7969渔民人均纯收入
    Net income per fisherman
    0.770 9
    技术推广经费
    Technology promotion funds
    0.70410技术推广经费
    Technology promotion funds
    0.68210
    家庭总收入
    Total household income
    0.630 11家庭总收入
    Total household income
    0.62311
    下载: 导出CSV

    表  6  辽宁省2006—2020年贝藻类以及捕捞渔业碳汇关联度排名

    Table  6.   Ranking of gray correlation between shellfish, capture fisheries and carbon sink in Liaoning Province from 2006 to 2020

    捕捞渔业 Capture fisheries贝藻类 Shell algae
    评价项
    Evaluation item
    关联度Correlation排名Ranking评价项
    Evaluation item
    关联度 Correlation排名Ranking
    捕捞产量
    Catch yield
    0.9521渔民人均纯收入
    Net income per fisherman
    0.9221
    技术推广机构数量
    Number of technology extension agencies
    0.8832渔业经济总产值
    Gross economic output value of fisheries
    0.8962
    海洋捕捞渔船总功率
    Total power of marine fishing vessels
    0.8543渔业占农业产值比重
    Proportion of fishery in agricultural output value
    0.8593
    渔业专业户数量
    Number of specialized fishery households
    0.8524海洋捕捞渔船总功率
    Total power of marine fishing vessels
    0.8574
    专业从业人员数量
    Number of employees
    0.8435海水养殖面积
    Mariculture area
    0.8445
    渔业占农业产值比重
    Proportion of fishery in agricultural output value
    0.8376渔业专业户数量
    Number of specialized fishery households
    0.8376
    海水养殖面积
    Mariculture area
    0.8047技术推广机构数量
    Number of technology extension agencies
    0.8277
    渔业经济总产值
    Gross economic output value of fisheries
    0.7888专业从业人员数量
    Number of employees
    0.8188
    渔民人均纯收入
    Net income per fisherman
    0.7639捕捞产量
    Catch yield
    0.7799
    技术推广经费
    Technology promotion funds
    0.67710技术推广经费
    Technology promotion funds
    0.77310
    家庭总收入
    Total household income
    0.61911家庭总收入
    Total household income
    0.69611
    下载: 导出CSV
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  • 收稿日期:  2022-07-14
  • 录用日期:  2022-11-30
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