Photosynthesis And Fluorescence Characteristics Of Coastal Wetland Vegetation

Coastal wetland ecosystem is one of the most powerful ecosystem of carbon sink in the world because of its strong photosynthetic capacity and small decomposition.Therefore,coastal wetland restoration and sink increase can be one of the effective ways to serve the strategic goal of carbon neutrality and cope with global climate change.Plant photosynthesis is an important part of coastal wetland carbon cycle,and is also an important driving force of coastal wetland blue carbon.However,the dynamic changes and internal mechanism of photosynthesis and fluorescence characteristics of coastal wetland vegetation are still unclear.At the same time,the research of wetland greenhouse gas is also one of the key points of coastal wetland blue carbon research.Therefore,in this study,Spartina alterniflora,Phragmites australis and Kandelia candel in the salt marsh ecosystem and mangrove ecosystem of coastal wetland were selected as the research objects.In situ,LI-6800F portable automatic photosynthetic fluorescence measurement system,MC-100 chlorophyll meter,LI-2200 canopy analyzer and portable greenhouse gas analyzer were used to monitor the dynamic changes of photosynthesis and fluorescence characteristics of coastal wetland plants at leaf scale and canopy scale,as well as the dynamic changes of greenhouse gas in coastal wetland,to explore the internal relationship between photosynthesis and fluorescence characteristics at different spatial scales,as well as the internal relationship between photosynthesis,chlorophyll fluorescence at leaf scale and wetland greenhouse gas emissions.The results can provide theoretical basis and technical support for comprehensive assessment of coastal wetland blue carbon and further understanding of coastal wetland carbon cycle.The main results are as follows:(1)The diurnal variation trends of net photosynthetic rate(A),transpiration rate(E)and stomatal conductance(Gsw)of plants(Phragmites australis,Spartina alterniflora and Kandelia candel)were single peak(except that Phragmites australis in July and August);The diurnal variation trend of intercellular CO₂ concentration(Ci)was U-shaped.The seasonal variation trend of A,E,Gsw,P_max and V_cmax was single peak;The seasonal variation trend of Ci was U-shaped,and the photosynthetic parameters of upper leaves were generally higher than those of lower leaves.(2)The seasonal variation trend of chlorophyll concentration in different canopy levels of different vegetation was asymmetric single peak.There was a significant positive correlation between the concentration of chlorophyll of different determination methods(R²>0.7,p<0.05).Therefore,the chlorophyll meter can be used to monitor the dynamic changes of chlorophyll in vegetation leaves to a certain extent.In addition,the seasonal variation trend of leaf specific weight at different canopy levels was basically the same,but the vertical differentiation was not obvious.There was a significant positive correlation between chlorophyll concentration and photosynthesis(R²>0.60,p<0.05),while the correlation between specific leaf weight and photosynthesis was weak(R²<0.50,p>0.05).(3)The daily variation trend of Actual photochemical efficiency(?PSII)and photochemical quenching(qP)was U-shaped,and there was a negative correlation between?PSII,qP and A.Specifically,in Spartina alterniflora and Kandelia candel,the correlation between qP and A was not significant only in December(p>0.05),but was significantly negative in other months(p<0.05);In Phragmites australis,qP was negatively correlated with A in June,July,September and October(p<0.05),but not in August(p>0.05).Except that The relationship between?PSII and A of Spartina alterniflora was not significant in December(p>0.05),?PSII was negatively correlated with A(p<0.05).In addition,through the RBF neural network model,the validation shows that PAR,?PSII and qP were significantly correlated with net photosynthetic rate(R²>0.97,p<0.05)The RBF neural network model constructed by?PSII,qP and PAR could also accurately predict the net photosynthetic rate of coastal wetland vegetation leaves(R²>0.5,p<0.05).(4)The seasonal variation of?PSII and qP was similar to that of chlorophyll concentration,which was a single peak type with asymmetry,and?PSII and qP were higher than those in the lower layer.However,the seasonal variation trend of leaf maximum photochemical efficiency(F_v/F_m)and chlorophyll concentration was not completely consistent,showing that the change was small in the early and middle growth stages,which was stable around 0.8,and only decreased significantly in the late growth stage.There was no significant vertical difference in F_v/F_m of leaves at different positions.Through the linear regression analysis,it is found that there was a significant positive correlation between?PSII,qP and chlorophyll concentration(p<0.05);There was a significant positive correlation between F_v/F_m and chlorophyll concentration in Kandelia candel(p<0.05),but no significant correlation between F_v/F_m and chlorophyll concentration in Spartina alterniflora and Phragmites australis(p>0.05).In addition,comparing different vegetation,we found that Spartina alterniflora leaves?PSII and qP were significantly higher than those of Phragmites australis and Kandelia candel.The difference of?PSII and qP between Phragmites australis and Kandelia candel was relatively small.(5)The seasonal variation trends of?PSII,qP and A were basically the same.However,the seasonal variation trends of NPQ and A were not consistent,which showed that NPQ fluctuated between 2-4 in the first and middle stages,and increased significantly in the later stage.The results of linear regression analysis showed that there was a significant positive correlation between qP,?PSII and A(p<0.05),but not significant correlation between NPQ and A(p>0.05).(6)The seasonal changes of primary productivity(GPP)and daily induced chlorophyll fluorescence(SIF)at canopy scale showed a trend of first increasing and then decreasing,and there was a significant correlation between GPP and SIF(p<0.05).In addition,there was a significant positive correlation between leaf scale photosynthesis and GPP in Kandelia candel(p<0.05),but not significant in Phragmites australis(p>0.05);There was a significant positive correlation between fluorescence parameters(qP,?PSII)and SIF(p<0.05).Therefore,SIF could track not only the changes of GPP,but also the changes of chlorophyll fluorescence at leaf scale.(7)In midsummer,the diurnal variation of CO₂ emission was U-shaped,which was negative,while CH₄ emission had no obvious diurnal variation,which was positive.Among them,the amount of CO₂ absorbed by Spartina alterniflora wetland was the highest,followed by Kandelia candel wetland;The amount of CH₄ emission from Spartina alterniflora wetland was the highest,followed by Kandelia candel wetland.CO₂ emission flux of wetland changed seasonally with plant phenology;The CH₄emission flux of wetland is relatively high in summer,but relatively low in other seasons.The seasonal variation trend of SGWP in Spartina alterniflora wetland was W-shaped,while that in Kandelia candel wetland was U-shaped.In addition,the average SGWP of Kandelia candel wetland was lower than that of Spartina alterniflora wetland,indicating that the blue carbon sink capacity of Kandelia candel wetland was relatively high.Linear regression analysis showed that there was a significant positive correlation between leaf photosynthesis and CH₄ emission flux(Spartina alterniflora R²=0.68,Kandelia candel R²=0.20,p<0.05);Leaf fluorescence parameters?PSII and qP were significantly positively correlated with SGWP(R²?0.6,p<0.05),which could track the change of SGWP to a certain extent.