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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。Abstract: Marine fisheries are valuable oceanic carbon sinks that store and sequester carbon. They act as both “carbon sources” and “carbon sinks”, and this is particularly important to achieve the established carbon peak and carbon neutrality goals. The amount of carbon sequestered by fisheries and its economic value in Liaoning Province from 2006 to 2020 were calculated based on the China Fisheries Statistical Yearbook, the Calculation Reference of Oil Consumption for Oil Price Subsidy of Domestic Fishing Vessels, and the China Statistical Yearbook. Then, a cubic exponential smoothing method was applied to a time-series forecasting model to predict the same parameters for 2021–2030, and the factors controlling the amount and economic value of carbon sequestered in fisheries in Liaoning Province were examined using gray correlation analysis. The results showed that 1) the surplus of income and expenditure for carbon sequestration in marine fisheries in the region decreased each year from 2006 to 2020, and the deficit is predicted to intensify in 2021–2030. 2) The maximum surplus of carbon (sequestration minus emissions) was 256.36×104 tons and the maximum deficit was 29.99×104 tons, with an average of 116.66×104 tons per year. 3) The total amount of carbon sequestered by shellfish and algae was 241.67×104 tons, 83% of which was attributed to the aquaculture industry, with little change. 4) The average amount of carbon emissions form marine fishing was 164.52×104 tons per year, almost 50% of which was attributed to trawling. The amount of carbon sequestered from marine fishing could not compensate for carbon emissions after 2017. 5) The total economic value of sequestered carbon of marine fisheries of Liaoning Province was 27.423 billion Yuan, with an annual average of 1.828 billion Yuan. 6) The total amount and economic value of carbon sequestered in marine fisheries continued to decline and were positively correlated. 7) The amount of sequestered carbon was also positively correlated with fishing yields, shellfish production, and macroalgal culture. The amount and economic value of carbon sequestered in marine fisheries in Liaoning Province were significantly influenced by national policies, fishing yield, number of employees, area of shellfish and macroalgal aquaculture sites, and the total power of fishing vessels (which determined the vessels’ carbon emissions). To protect marine biodiversity and promote the sustainable development of marine fisheries in the area, it is recommended to integrate multiple aquaculture systems, reduce high-energy-consuming fishing operations, and strengthen the monitoring of highly polluting fishing vessels.
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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 shellfish1 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 shellfish2 ${C}_{{\rm{s}}}=\displaystyle\sum _{i=1}^{n}{C}_{i}$ ${C}_{{\rm{s}}}$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 macroalgae3 $ {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 macroalgae4 $ 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 level5 ${T}_{i}=1+\displaystyle\sum _{j=1}^{n}{D}_{i j}\times {T}_{j}$ $ {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 prey6 ${B}_{j}={Y}_{0} /\left({E}_{ {L}_{0}-1}\times {E}_{ {L}_{0}-2}\right)$ ${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) $[14] 摄食浮游植物和有机碎屑的比例
Proportion of phytoplankton and organic detritus in diet7 1×Q+2×(100%−Q) =
L0−2, 即Q = 4−L0$ 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 diet8 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 phytoplankton9 $ {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 phytoplankton10 $ {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量
CO2 emissions from fossil fuel combustion11 $ {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 vessel12 ${G}_{n}={T}_{n}\times s\times w\times z\times \varphi$ $ {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 vessels13 ${C}_{ {\mathrm{c}\mathrm{o} }_{2} }={G}_{n}\times \partial$ $ {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 consumption14 $ {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 fisheries15 ${Y}_{t+T}={A}_{t}+{B}_{t}+{C}_{t}\times {T}^{2}$ $ {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 sink16 ${O}_{_ {\rm{CSV} } }={O}_{_ {\rm{FS} } }\times {C}_{ {\rm{rec} } }$ ${O}_{_ {\rm{CSV} } }$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 coefficient17 $\delta_{i j}=\dfrac{\min _j \times \min _k \times \Delta_{i j}(k)+\beta \times \max _j \times \max _k \times \Delta_{i j}(k)}{\Delta_{i j}(k)+\beta \times \max _j \times \max _k \times \Delta_{i j}(k)}$ $\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 correlation18 $ {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
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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 Oyster 65.10 6.14 93.86 45.89 12.68 贻贝 Mussel 75.28 8.47 91.53 44.40 11.76 扇贝 Scallop 63.89 14.35 85.65 43.90 11.40 蛤 Clam 52.55 1.98 98.02 44.90 11.52 蛏 Razor clam 70.48 3.26 96.74 44.90 13.24 其他贝类 Other shellfish 64.21 11.41 88.59 43.87 11.44
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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 Kelp 31.20 裙带菜 Wakame 26.40 其他藻类 Other algae 27.76
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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 polyactis 1017.49 14 竹筴鱼 Trachurus japonicus 28.05 2 鲅鱼(蓝点马鲛) Scomberomorus niphonius 835.27 15 沙丁鱼 Sardina pilchardus 23.08 3 鳀鱼 Engraulis japonicus 620.17 16 白姑鱼 Argyrosomus argentatus 19.64 4 鲐鱼(日本鲭) Scomber japonica 479.91 17 鮸鱼 Miichthys miiuy 10.03 5 大黄鱼 Larimichthys crocea 295.22 18 金枪鱼 Thunnus thynnus 9.18 6 带鱼 Trichiutus lepturus 228.94 19 马面鲀 Navodon modestus 8.45 7 梭鱼 Liza haematocheila 107.48 20 海鳗 Muraenesox cinereus 7.19 8 梅童鱼 Collichthys lucidus 64.92 21 鳓鱼 Ilisha elongata 3.85 9 玉筋鱼 Ammodytes personatus 61.83 22 金线鱼 Nemipterus virgatus 2.14 10 鲻鱼 Mugil cephalus 39.91 23 方头鱼 Branchiostegus japonicus 1.83 11 黄姑鱼 Nibea albiflora 38.51 24 鲷鱼 Pagrus pagrus 0.93 12 石斑鱼 Epinephelus sp. 36.79 25 蓝圆鯵 Decapterus maruadsi 0.24 13 鲳鱼 Pampus gargenteus 34.80 26 鲱鱼 Clupea pallasi 0.17
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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 value0.938 1 捕捞产量
Catch yield0.950 1 海洋捕捞渔船总功率
Total power of marine fishing vessels0.935 2 技术推广机构数量
Number of technology extension agencies0.888 2 渔业专业户数量
Number of specialized fishery households0.919 3 海洋捕捞渔船总功率
Total power of marine fishing vessels0.862 3 专业从业人员数量
Number of employees0.889 4 渔业专业户数量
Number of specialized fishery households0.862 4 技术推广机构数量
Number of technology extension agencies0.856 5 专业从业人员数量
Number of employees0.851 5 海水养殖面积
Mariculture area0.848 6 渔业占农业产值比重
Proportion of fishery in agricultural output value0.845 6 渔业经济总产值
Gross economic output value of fisheries0.847 7 海水养殖面积
Mariculture area0.811 7 渔民人均纯收入
Net income per fisherman0.828 8 渔业经济总产值
Gross economic output value of fisheries0.794 8 捕捞产量
Catch yield0.796 9 渔民人均纯收入
Net income per fisherman0.770 9 技术推广经费
Technology promotion funds0.704 10 技术推广经费
Technology promotion funds0.682 10 家庭总收入
Total household income0.630 11 家庭总收入
Total household income0.623 11
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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 yield0.952 1 渔民人均纯收入
Net income per fisherman0.922 1 技术推广机构数量
Number of technology extension agencies0.883 2 渔业经济总产值
Gross economic output value of fisheries0.896 2 海洋捕捞渔船总功率
Total power of marine fishing vessels0.854 3 渔业占农业产值比重
Proportion of fishery in agricultural output value0.859 3 渔业专业户数量
Number of specialized fishery households0.852 4 海洋捕捞渔船总功率
Total power of marine fishing vessels0.857 4 专业从业人员数量
Number of employees0.843 5 海水养殖面积
Mariculture area0.844 5 渔业占农业产值比重
Proportion of fishery in agricultural output value0.837 6 渔业专业户数量
Number of specialized fishery households0.837 6 海水养殖面积
Mariculture area0.804 7 技术推广机构数量
Number of technology extension agencies0.827 7 渔业经济总产值
Gross economic output value of fisheries0.788 8 专业从业人员数量
Number of employees0.818 8 渔民人均纯收入
Net income per fisherman0.763 9 捕捞产量
Catch yield0.779 9 技术推广经费
Technology promotion funds0.677 10 技术推广经费
Technology promotion funds0.773 10 家庭总收入
Total household income0.619 11 家庭总收入
Total household income0.696 11
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