摘 要:【目的】樟子松為中國(guó)“三北”防護(hù)林建設(shè)工程主要樹(shù)種之一,具有重要的生態(tài)功能。探討樟子松樹(shù)體各器官含碳率及碳儲(chǔ)量,可為沙地樟子松碳儲(chǔ)量動(dòng)態(tài)的估算提供基礎(chǔ)數(shù)據(jù)?!痉椒ā客ㄟ^(guò)實(shí)地調(diào)查取樣、試驗(yàn)測(cè)定對(duì)11個(gè)胸徑徑階(10、12、14、16、18、20、22、24、26、28、30 cm)的20株沙地樟子松Pinus sylvestris var. mongolica各器官含碳率進(jìn)行測(cè)定分析。【結(jié)果】含碳率規(guī)律為:樹(shù)干(41.6%)>樹(shù)葉(39.2%)>樹(shù)枝(38.0%)>樹(shù)根(34.1%)。樟子松碳儲(chǔ)量主要來(lái)自樹(shù)干和樹(shù)根,二者碳儲(chǔ)量分別占總體39.08%和30.17%。樟子松通用含碳率(50%)會(huì)過(guò)量估算沙地樟子松人工林碳儲(chǔ)量。當(dāng)胸徑超過(guò)16 cm時(shí),樟子松總體及各器官碳儲(chǔ)量大幅增加,且碳儲(chǔ)量的增加主要為生長(zhǎng)的中后期。所建立的模型對(duì)樹(shù)干和樹(shù)根的擬合效果優(yōu)于樹(shù)枝和樹(shù)葉的擬合效果,在引入樹(shù)高變量之后,二元模型有效地提高了擬合效果和預(yù)測(cè)能力。【結(jié)論】同一樹(shù)種不同器官間含碳率存在差異,樟子松碳儲(chǔ)量主要集中在樹(shù)干和樹(shù)根,且隨樹(shù)木胸徑增大,樹(shù)干和樹(shù)根對(duì)整株碳儲(chǔ)量的貢獻(xiàn)增大。以胸徑和樹(shù)高為自變量的總體、樹(shù)干和樹(shù)根的模型擬合效果更好,樹(shù)枝和樹(shù)葉的擬合效果較差,引入樹(shù)高后的二元模型精度更高。
關(guān)鍵詞:含碳率;碳儲(chǔ)量;沙地人工林;CAR模型
中圖分類(lèi)號(hào):S718.55 文獻(xiàn)標(biāo)志碼:A 文章編號(hào):1673-923X(2024)12-0031-08
基金項(xiàng)目:國(guó)家自然科學(xué)基金項(xiàng)目(32071836);國(guó)家重點(diǎn)研發(fā)計(jì)劃專(zhuān)題(2022YFF1302505-02);國(guó)家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(SQ2023YFD1500036);遼寧省農(nóng)業(yè)科學(xué)院基本科研業(yè)務(wù)費(fèi)計(jì)劃項(xiàng)目(2021HQ1913)。
Component specific carbon contents and storage of Pinus sylvestris in Horqin sandy areas
LANG Minghan, ZHANG Risheng, JIANG Tao, HAN Hui, XIAO Wei, CHI Linlin, ZHANG Xiaoguang
(a. Liaoning Institute of Sandy Land Control and Utilization; b. Liaoning Zhanggutai Desert Ecosystem Research Station, Liaoning Academy of Agricultural Sciences, Fuxin 123000, Liaoning, China)
Abstract:【Objective】Pinus sylvestris is one of the main tree species in China’s “Three North” protective forest construction project, and has important ecological functions. Exploring the carbon content and carbon storage of various organs in the P. sylvestris can provide basic data for the estimation of carbon storage dynamics of P. sylvestris in sandy areas.【Method】Through on-site investigation, sampling, and experimental measurement, the carbon content of each organ of 20 P. sylvestris var. mongolica trees with 11 diameter stages (10, 12, 14, 16, 18, 20, 22, 24, 26, 28, and 30 cm) in sandy areas was measured and analyzed.【Result】The pattern of carbon content was: trunk (41.6%)>leaves (39.2%)>branches (38.0%)>roots (34.1%). The carbon storage of the trunk and roots of P. sylvestris var. mongolica accounted for 39.08% and 30.17% of the total carbon storage, respectively, and were the main sources of tree carbon storage. The general carbon content of P. sylvestris var. mongolica (50%) will overestimate the carbon storage of P. sylvestris plantations in sandy areas. When the diameter at breast height exceeds 16 cm, the overall carbon storage and various organs of P. sylvestris significantly increased, and the increase in carbon storage mainly occurred in the middle and later stages of growth. The established model had a better fitting effect on the trunk and roots than on the branches and leaves. After introducing the tree height variable, the binary model effectively improved the fitting effect and predictive ability.【Conclusion】Even for the same tree species, there are differences in carbon content among different organs of the tree. The carbon storage of P. sylvestris is mainly concentrated in the trunk and roots, and as the tree grows and develops, the contribution of the trunk and roots to the overall carbon storage becomes greater. The trunk and root models have better fitting effects, while branches and leaves have poorer fitting effects. The binary model with the introduction of tree height has higher accuracy.
Keywords: carbon content; carbon storage; plantation in sandy land; CAR model
全球氣候變化已成為不可否認(rèn)的事實(shí),大氣二氧化碳濃度增加導(dǎo)致的全球變暖是當(dāng)今世界的一個(gè)突出全球環(huán)境問(wèn)題[1]。根據(jù)報(bào)道,每天有大約8 800萬(wàn)噸CO2排放到大氣中,CO2的過(guò)度排放是導(dǎo)致大氣中溫室氣體增加、全球變暖和自然災(zāi)害頻發(fā)的重要原因之一[2]。森林生態(tài)系統(tǒng)是陸地生態(tài)系統(tǒng)的主體,也是陸地生態(tài)系統(tǒng)中最大的碳匯。有機(jī)碳占陸地生態(tài)系統(tǒng)有機(jī)碳總量的三分之二以上,既是“碳源”又是“碳匯”。森林在增加碳匯和減緩大氣溫室氣體濃度增加方面的作用日益突出[3-4]。根據(jù)《第九次森林資源清查報(bào)告》,我國(guó)具有全球最大面積的人工林。人工造林可以有效應(yīng)對(duì)全球氣候變化,中國(guó)森林碳匯為應(yīng)對(duì)氣候變化作出了巨大的歷史貢獻(xiàn)[5]。對(duì)人工林碳儲(chǔ)量的評(píng)估和預(yù)測(cè)有助于我國(guó)“雙碳”目標(biāo)的實(shí)現(xiàn)[6]。精準(zhǔn)評(píng)估和預(yù)測(cè)人工林生態(tài)系統(tǒng)碳儲(chǔ)量對(duì)理解碳循環(huán)過(guò)程具有極其重要的作用,同時(shí)也是研究氣候變化的關(guān)鍵問(wèn)題之一[7]。國(guó)內(nèi)外眾多學(xué)者對(duì)不同國(guó)家或區(qū)域的森林生態(tài)系統(tǒng)的碳匯、碳密度和碳儲(chǔ)存功能進(jìn)行了廣泛的研究[8]。學(xué)術(shù)界對(duì)森林生態(tài)系統(tǒng)碳儲(chǔ)量的估算存在著較大的爭(zhēng)議,主要原因是數(shù)據(jù)的時(shí)空差異、使用的估計(jì)方法不同以及森林生態(tài)系統(tǒng)在時(shí)間和空間上的復(fù)雜性[9]。目前,針對(duì)國(guó)家、區(qū)域尺度或者森林群落、森林生態(tài)系統(tǒng)尺度的碳儲(chǔ)量估算方法主要由含碳率與森林植被的生物量的乘積推算而來(lái)[10]。不同樹(shù)種的含碳率成為森林生態(tài)系統(tǒng)碳儲(chǔ)量估算的重要參數(shù),所以對(duì)不同植被含碳率的研究成為評(píng)估森林生態(tài)系統(tǒng)的重要基礎(chǔ)[11]。植被類(lèi)型、分布區(qū)域不同,其植被含碳率存在一定的差異。目前針對(duì)溫帶和北方溫度帶針葉樹(shù)種含碳率經(jīng)驗(yàn)值為47%~55%[12],因此利用通用含碳率對(duì)森林生態(tài)系統(tǒng)碳儲(chǔ)量進(jìn)行估算會(huì)導(dǎo)致對(duì)森林生態(tài)系統(tǒng)碳儲(chǔ)量及碳匯能力的估算結(jié)果產(chǎn)生較大的影響[13],因此準(zhǔn)確估計(jì)各地區(qū)森林植被的碳儲(chǔ)量需要不同研究區(qū)不同植被和器官的碳含量,以減少森林植被碳儲(chǔ)量的估計(jì)誤差[14]。
科爾沁沙地是我國(guó)面積最大的沙地,地處遼西平原,該地堆積了大約200 m厚的沙質(zhì)沉積物,生態(tài)環(huán)境十分脆弱,植被恢復(fù)困難。眾多學(xué)者對(duì)科爾沁沙地固沙林的研究大多聚焦在樟子松林[15]。樟子松是歐洲赤松Pinus sylvestris的地理變種之一,天然的分布區(qū)位于東北亞一帶[16],在中國(guó)大興安嶺北部、東部,黑龍江流域以及呼倫貝爾沙地地區(qū)為樟子松天然分布區(qū)[17]。20世紀(jì)50年代初,在遼寧省彰武縣章古臺(tái)鎮(zhèn)開(kāi)展了樟子松引種栽植試驗(yàn),經(jīng)對(duì)比,樟子松表現(xiàn)耐旱、耐寒等優(yōu)良的特性,是眾多固沙植物中綜合表現(xiàn)最好的[18],以防風(fēng)固沙為目的的中國(guó)第一片沙地樟子松人工林為全國(guó)植被治沙提供了樣板[19]。但目前針對(duì)沙地樟子松含碳率及單株尺度碳儲(chǔ)量的研究報(bào)道很少見(jiàn)。本研究以沙地樟子松人工林為研究對(duì)象,測(cè)定其各器官(樹(shù)根、樹(shù)干、樹(shù)枝、樹(shù)葉)含碳率,建立適合科爾沁沙地南緣樟子松人工林碳儲(chǔ)量模型,明晰碳在樟子松中的分割格局及其與胸徑、樹(shù)高的關(guān)系,進(jìn)而為沙地樟子松人工林碳儲(chǔ)量、碳匯強(qiáng)度精準(zhǔn)估算,提供了基礎(chǔ)的參數(shù)。
1 研究地區(qū)與研究方法
1.1 研究區(qū)概況
研究地位于遼寧省沙地治理與利用研究所實(shí)驗(yàn)基地—章古臺(tái)鎮(zhèn)(42°43′N(xiāo),122°22′E),屬于阜新市彰武境內(nèi),自然區(qū)域?qū)儆诳茽柷呱车貣|南部,溫帶半濕潤(rùn)大陸性季風(fēng)氣候,是遼河平原的邊緣地帶。年均氣溫6.3 ℃,歷年最高氣溫43.2 ℃,歷年最低氣溫-30.5 ℃,全年無(wú)霜期150~160 d,年均降水量500 mm,年均蒸發(fā)量1 550 mm,平均空氣濕度60.4%,年均風(fēng)速2.7 m?s-1。風(fēng)速大于3 m·s-1的日數(shù)平均為160 d,風(fēng)速大于10 m?s-1的日數(shù)平均為10 d,而起沙的風(fēng)速5 m?s-1全年高達(dá)240多次。土壤以風(fēng)沙土為主,沙層厚度為126~128 m,流動(dòng)風(fēng)沙土0~30 cm內(nèi)有機(jī)質(zhì)含量為3.3~3.6 g?kg-1,樟子松林地0~30 cm土層有機(jī)質(zhì)含量為4.2~5.0 g?kg-1。
1.2 研究?jī)?nèi)容
1.2.1 試驗(yàn)設(shè)計(jì)
2022年在遼寧省沙地治理與利用研究所實(shí)驗(yàn)樣地內(nèi)選取10~30 cm徑階區(qū)間(表1)20株樟子松樣木,樣木年齡主要查閱遼寧省沙地治理與利用研究所數(shù)據(jù)資料結(jié)合林相圖進(jìn)行判別,各樣木調(diào)查情況見(jiàn)表2。從樹(shù)干基部伐倒樣木后,測(cè)定胸徑及樹(shù)高,樹(shù)干按1 m的長(zhǎng)度切成多段,最后以不足1 m的部分作為梢頭,測(cè)定每段樹(shù)干的鮮質(zhì)量。在各段樹(shù)干的形態(tài)學(xué)上端位置、根頸位置(0 m)以及胸徑位置(1.3 m)分別截取一個(gè)厚度為3~5 cm的圓盤(pán)作為樣品。對(duì)于樟子松枝葉,在每輪的枝條中選取一個(gè)平均大小的枝條作為標(biāo)準(zhǔn)枝,將標(biāo)準(zhǔn)枝枝葉分離,分別稱(chēng)量其鮮質(zhì)量,取枝、葉樣品50 g。利用機(jī)械和人力結(jié)合的方法,將以樹(shù)根為中心5 m范圍內(nèi)的樹(shù)根全部挖掘出來(lái),根據(jù)根直徑的大小,將其分為大根(>5 cm)、中根(2~5 cm)和小根(<2 cm),分別測(cè)量其鮮質(zhì)量并選取50 g的樣品。將所有樹(shù)干、樹(shù)根、樹(shù)枝、樹(shù)葉樣品帶回實(shí)驗(yàn)室,于80 ℃下烘干至恒質(zhì)量,計(jì)算各器官干鮮質(zhì)量比,進(jìn)而得出解析木各器官的生物量,將各器官生物量進(jìn)行匯總后即可得到單木的總生物量。將烘干至恒質(zhì)量的樟子松各器官(樹(shù)干、樹(shù)根、樹(shù)枝、樹(shù)葉)樣品粉碎、研磨、過(guò)篩,最后采用全自動(dòng)固體總有機(jī)碳分析儀(Vario TOC Select)測(cè)定含碳率。
2 結(jié)果與分析
2.1 樟子松各器官碳分布格局
由表3可知,樟子松各器官組分平均含碳率為29.6%~42.2%,變異系數(shù)為0.106~0.211,標(biāo)準(zhǔn)差為0.037~0.088。碳在樹(shù)根的分布規(guī)律:細(xì)根含碳率最低(29.6%),低于中根(35.2%)和粗根(37.4%);碳在樹(shù)枝的分布規(guī)律為下層枝>中層枝>上層枝,含碳率隨著樹(shù)體高度的增加而增加;碳在樹(shù)干的分布規(guī)律為下層(42.2%)>上層(41.6%)>中層(40.9%);碳在樹(shù)葉的分布規(guī)律為中層(40.7%)>下層(38.7%)>上層(38.3%)。
由圖1可知,樟子松樹(shù)根、樹(shù)干、樹(shù)枝及樹(shù)葉含碳率隨胸徑的增加而增加,但其增長(zhǎng)的程度不同,根、干和枝擬合公式的斜率分別為0.003 4、0.007 2、0.005 6,樹(shù)干含碳率隨徑階增加而提升的幅度最大,其次是枝、根。樹(shù)葉擬合公式的斜率為-0.000 4,表明樹(shù)葉含碳率隨徑階的增加而降低。
2.2 樟子松各器官碳儲(chǔ)量分布格局及其與胸徑的關(guān)系
根據(jù)不同徑階全樹(shù)及各器官沙地樟子松碳儲(chǔ)量數(shù)據(jù)分析,結(jié)果表明:樹(shù)干碳儲(chǔ)量最高,占比最大(39.08%),其次是樹(shù)根(30.17%)、樹(shù)枝(18.72%),樹(shù)葉碳儲(chǔ)量最低,占比最?。?2.03%)(圖2)。由各器官碳儲(chǔ)量隨胸徑變化圖2可知,從各組分來(lái)看,隨著胸徑的增長(zhǎng),樟子松各組分碳儲(chǔ)量均有不同程度的增長(zhǎng),但增長(zhǎng)的幅度不同,當(dāng)胸徑徑階為10~16 cm時(shí),樟子松器官各組分碳儲(chǔ)量增長(zhǎng)程度較小,且存在碳儲(chǔ)量降低的現(xiàn)象;當(dāng)胸徑徑階超過(guò)16 cm,全樹(shù)各器官?gòu)诫A、碳儲(chǔ)量關(guān)系曲線斜率大幅增加,意味著當(dāng)胸徑超過(guò)16 cm后,全樹(shù)及各器官碳儲(chǔ)量開(kāi)始快速積累。由各器官碳儲(chǔ)量比例對(duì)胸徑變化圖2可知,不同器官碳儲(chǔ)量在全樹(shù)碳儲(chǔ)量中的占比規(guī)律存在較大差異,樹(shù)根、樹(shù)干碳儲(chǔ)量占比隨胸徑徑階的增加逐漸增加,樹(shù)枝、樹(shù)葉碳儲(chǔ)量占比隨胸徑徑階的增加逐漸減小,表明樹(shù)干和樹(shù)根是樟子松中后期碳儲(chǔ)量主要來(lái)源。
2.3 樟子松各器官碳儲(chǔ)量的估算模型
基于相對(duì)生長(zhǎng)方程式CAR模型形式,建立生長(zhǎng)因子胸徑、樹(shù)高與樟子松各組分碳儲(chǔ)量的碳儲(chǔ)量模型,結(jié)果(表4)表明:樹(shù)枝和樹(shù)葉生物量模型R2為0.706~0.761,樹(shù)干和樹(shù)根生物量模型R2均大于0.9,樹(shù)干、樹(shù)根、全樹(shù)生物量模型擬合效果更好。從表4中的檢驗(yàn)指標(biāo)可以看出,全樹(shù)及其各器官碳儲(chǔ)量CAR模型2、CAR模型3兩種二元模型優(yōu)于一元模型CAR模型1,即增加樹(shù)高作為自變量有利于提高碳儲(chǔ)量模型預(yù)測(cè)精度。在根、干、枝、葉器官模型檢驗(yàn)指標(biāo)中,根、干檢驗(yàn)效果良好,其數(shù)值更接近0。由圖3可知,3種模型下根、干散點(diǎn)更加靠近Y=X分割線,枝和葉散點(diǎn)更加分散。散點(diǎn)越接近Y=X分割線表明模擬值與實(shí)測(cè)值越接近,證明模型擬合效果越好。綜上所述,二元碳儲(chǔ)量模型CAR模型1和CAR模型2精度高于一元碳儲(chǔ)量模型CAR模型1,模型對(duì)干、根的預(yù)測(cè)精度更高(圖3)。
3 討 論
3.1 樟子松含碳率的分布格局
各器官含碳率從大到小依次為樹(shù)干(41.6%)、樹(shù)葉(39.2%)、樹(shù)枝(38.0%)、樹(shù)根(34.1%),樟子松各器官含碳率隨著樹(shù)齡的增加緩慢增加,隨著樹(shù)齡的增加,樹(shù)枝的含碳率增長(zhǎng)程度最大。與樹(shù)根、樹(shù)枝、樹(shù)葉相比,樹(shù)干中木質(zhì)素含量更高,因此樹(shù)干的含碳率高于其他器官,這與現(xiàn)有的研究結(jié)論一致,植物本身構(gòu)造特點(diǎn)決定著不同器官含碳率的差異[20-21]。隨著胸徑的增加,樹(shù)齡逐漸增加,樹(shù)枝木質(zhì)化速率最快,木質(zhì)素合成速率更快,因此其含碳率增速更大。樹(shù)葉含碳率僅次于樹(shù)干,該器官內(nèi)部發(fā)生一系列的生化反應(yīng),合成了可供植物生存的各種有機(jī)物,因此該器官含碳率也較高[22]。樹(shù)根吸收土壤中的水分和無(wú)機(jī)鹽,二者協(xié)調(diào)配合保證了植物生存,處于營(yíng)養(yǎng)運(yùn)輸體系中最末端導(dǎo)致了其含碳率最小[22],與李春平等[23]研究結(jié)果一致。大多數(shù)研究者采用通用平均含碳率50%或者45%估算森林生態(tài)系統(tǒng)碳儲(chǔ)量[24],即使針對(duì)同一種植物,其生長(zhǎng)地點(diǎn)海拔、氣候,植株年齡、起源,含碳率必定存在著差異。在大尺度區(qū)域范圍內(nèi)采用通用含碳率估算碳儲(chǔ)量對(duì)其結(jié)果的影響誤差較小,因此采用通用碳率是可行的。當(dāng)研究區(qū)為林分尺度時(shí),采用通用含碳率估算碳儲(chǔ)量會(huì)對(duì)結(jié)果造成較大的誤差。本文測(cè)算的樟子松全樹(shù)加權(quán)平均含碳率為39.2%,明顯低于通用含碳率。采用通用含碳率50%計(jì)算沙地樟子松林碳儲(chǔ)量,會(huì)高估沙地樟子松林25%左右的碳儲(chǔ)量。為了減小估算沙地樟子松林碳儲(chǔ)量的誤差,應(yīng)根據(jù)不同氣候條件、林分起源、海拔等條件調(diào)整參數(shù)[14]。水分限制可能是引起沙地樟子松含碳率偏低的主要原因,研究區(qū)氣候干旱,其蒸散系數(shù)(PE/P)較高[25],這種水分虧缺的氣候條件極有可能限制植株有機(jī)物的積累,因此研究區(qū)樟子松含碳率較低。
3.2 樟子松碳分布規(guī)律及其與胸徑的關(guān)系
樟子松各器官碳儲(chǔ)量在全樹(shù)種中的占比順序?yàn)闃?shù)干(39.08%)>樹(shù)根(30.17%)>樹(shù)枝(18.72%)>樹(shù)葉(12.03%),樹(shù)干和樹(shù)根碳儲(chǔ)量占全樹(shù)碳儲(chǔ)量比例高達(dá)70%,意味著沙地樟子松碳主要貯存在樹(shù)干和樹(shù)根中。其原因在于樹(shù)干、樹(shù)根生物量具有隨樹(shù)齡增加而穩(wěn)定增加的特征。樹(shù)冠下部樹(shù)枝會(huì)進(jìn)行自然整枝[26]、樟子松一般持有4齡針葉[19],樹(shù)枝和樹(shù)葉兩個(gè)器官生物量累積穩(wěn)定性相對(duì)較差,因此隨著樹(shù)齡的增加,生物量累積穩(wěn)定性更高的樹(shù)干和樹(shù)根生物量占比越來(lái)越高,穩(wěn)定性較差的樹(shù)枝和樹(shù)葉生物量占比越來(lái)越低。本研究中胸徑16 cm為碳儲(chǔ)量隨徑階變化曲線的臨界點(diǎn),且不僅樟子松具有在臨界點(diǎn)前后各器官碳儲(chǔ)量增幅變大的規(guī)律,徐期瑚等[14]在研究廣東樟樹(shù)各器官碳儲(chǔ)量也發(fā)現(xiàn),全樹(shù)及各器官碳儲(chǔ)量增加幅度具有差異,樟樹(shù)胸徑2~8 cm時(shí)碳儲(chǔ)量增加幅度較小,當(dāng)胸徑超過(guò)12 cm后,碳儲(chǔ)量增加幅度較大。這種樹(shù)木前中期碳儲(chǔ)量快速增加的規(guī)律符合其生長(zhǎng)規(guī)律,意味著樹(shù)木生長(zhǎng)從生長(zhǎng)初期進(jìn)入到速生期[27]。
3.3 樟子松各器官碳儲(chǔ)量的估算模型
基于CAR公式的生物量模型形式,以胸徑、樹(shù)高為變量,以全樹(shù)及各器官碳儲(chǔ)量為因變量進(jìn)行回歸分析,獲得沙地樟子松全樹(shù)及各器官碳儲(chǔ)量回歸方程。樹(shù)枝、樹(shù)葉模擬精度過(guò)低的原因有兩個(gè),一是出現(xiàn)異常的大枝,導(dǎo)致模型擬合過(guò)程中出現(xiàn)異常值[28];二是本研究樣地為樟子松人工林,造林格局相同,同時(shí)胸徑與樹(shù)齡成正比,低樹(shù)齡樟子松樣木種內(nèi)競(jìng)爭(zhēng)相對(duì)高樹(shù)齡樟子松樣木更低,樹(shù)齡較小時(shí)期,樹(shù)枝、樹(shù)葉生長(zhǎng)發(fā)育受種內(nèi)影響較小,隨著林齡的增加,各植株生長(zhǎng)發(fā)育受其他樟子松影響限制程度逐漸增加,因此樹(shù)枝、樹(shù)葉碳儲(chǔ)量占比不穩(wěn)定,進(jìn)而導(dǎo)致模型精度下降[29-30]。今后應(yīng)加大樣本單元數(shù)量,以減小平均相對(duì)誤差絕對(duì)值和平均誤差絕對(duì)值,進(jìn)而提高模型擬合精度。
4 結(jié) 論
本研究以沙地樟子松為研究對(duì)象,采用解析木法對(duì)沙地樟子松樹(shù)體碳分布狀況以及碳儲(chǔ)量與生長(zhǎng)因子間的關(guān)系進(jìn)行了研究。結(jié)果表明:
1)各器官含碳率從大到小依次為樹(shù)干(41.6%)、樹(shù)葉(39.2%)、樹(shù)枝(38.0%)、樹(shù)根(34.1%)。因此對(duì)全樹(shù)含碳率的分析應(yīng)按照器官分類(lèi),全面考慮。使用單獨(dú)器官作為全樹(shù)含碳率會(huì)不可避免地過(guò)高或過(guò)低估算其碳儲(chǔ)量。
2)沙地樟子松全樹(shù)平均含碳率為39.2%,低于通用含碳率(50%),采用通用含碳率會(huì)過(guò)高估算25%的碳儲(chǔ)量。
3)沙地樟子松碳集中在樹(shù)干和樹(shù)根,各器官碳儲(chǔ)量大幅增加的胸徑突變值為16 cm,碳儲(chǔ)量的增加主要在生長(zhǎng)的中后期。
4)自變量選擇樹(shù)木胸徑和樹(shù)高,建立的一元、二元建模各有利弊。二元模型精度更高,但樹(shù)高測(cè)量誤差較大,數(shù)據(jù)可信度較差;一元自變量較為單一,模型精度較差,但胸徑測(cè)量誤差較小,數(shù)據(jù)可信度較高。因此一元模型適合針對(duì)大尺度的碳儲(chǔ)量估算;二元模型適合林分尺度的碳儲(chǔ)量估算。
參考文獻(xiàn):
[1] FENG J J, DAN X M, CUI Y K, et al. Integrating evolutionary genomics of forest trees to inform future tree breeding amidst rapid climate change[J]. Plant Communications,2024,101044.
[2] 孫清芳,王明強(qiáng),馬艷娥.黑龍江省造林樹(shù)種含碳率與土壤性質(zhì)研究[J].森林工程,2018,34(4):40-44. SUN Q F, WANG M Q, MA Y E. Study of carbon rate and soil properties of afforestation tree species in Heilongjiang Province[J]. Forest Engineering,2018,34(4):40-44
[3] PAN Y D, BIRDSEY R A, FANG J Y, et al. A large and persistent carbon sink in the world’s forests[J]. Science,2011,333(6045): 988-993.
[4] HOUGHTON R A, HALL F, GOETZ S J. Importance of biomass in the global carbon cycle[J]. Journal of Geophysical Research, 2009,114(G2): G00E03.
[5] SHUIFA K, ZHANG Z, WANG Y M. China’s forest carbon sinks and mitigation potential from carbon sequestration trading perspective[J]. Ecological Indicators,2023,148:110054.
[6] 閆德仁,閆婷,趙春光.草原天然植被和草原造林固碳儲(chǔ)量的對(duì)比研究[J].內(nèi)蒙古林業(yè)科技,2011,37(1):5-8. YAN D R, YAN T, ZHAO C G. Comparative study on carbon stocks of natural vegetation and plantation in grasslands[J]. Journal of Inner Mongolia Forestry Science Technology, 2011,37(1):5-8
[7] 閆婷,閆德仁,袁立敏,等.沙地楊樹(shù)、樟子松人工林固碳特征研究[J].內(nèi)蒙古林業(yè)科技,2012,38(2):14-18. YAN T, YAN D R, YUAN L M, et al. Carbon fixation characteristics of Populus L. planatation and Pinus sylvesrtris var. mongolica Litv. planatation in sandy land[J]. Journal of Inner Mongolia Forestry Science Technology,2012,38(2):14-18.
[8] STEFFI R, KARSTEN D, GERALD K, et al. Comparison of calculation methods for estimating annual carbon stock change in German forests under forest management in the German greenhouse gas inventory[J]. Carbon Balance and Management, 2016,11(1):12.
[9] 吳慶標(biāo),王效科,段曉男,等.中國(guó)森林生態(tài)系統(tǒng)植被固碳現(xiàn)狀和潛力[J].生態(tài)學(xué)報(bào),2008,28(2):517-524. WU Q B, WANG X K, DUAN X N, et al. Carbon sequestration and its potential by forest ecosystems in China[J]. Acta Ecologica Sinica, 2008,28(2):517-524.
[10] 劉學(xué)龍,賴(lài)日文,汪琴,等.森林碳儲(chǔ)量遙感估測(cè)模型構(gòu)建研究:以閩江流域杉木林為例[J].中南林業(yè)科技大學(xué)學(xué)報(bào), 2014,34(6):76-80. LIU X L, LAI R W, WANG Q, et al. Research on remote sensing model of forest carbon storage: a case study of Chinese fir in Minjiang watershed[J]. Journal of Central South University of Forestry Technology,2014,34(6):76-80.
[11] 徐期瑚,林麗平,薛春泉,等.廣東木荷各器官含碳率及碳儲(chǔ)量研究[J].中南林業(yè)科技大學(xué)學(xué)報(bào),2018,38(10):71-78.XU Q H, LIN L P, XUE C Q, et al. Component specific carbon contents and storage of Schima superba in Guangdong Province[J]. Journal of Central South University of Forestry Technology, 2018,38(10):71-78.
[12] LAMLOM S H, SAVIDGE R A. A reassessment of carbon content in wood: variation within and between 41 North American species[J]. Biomass Bioenergy,2003,25(4):381-388.
[13] 黃從德,張健,楊萬(wàn)勤,等.四川省及重慶地區(qū)森林植被碳儲(chǔ)量動(dòng)態(tài)[J].生態(tài)學(xué)報(bào),2008,28(3):966-975. HUANG C D, ZHANG J, YANG W Q, et al. Dynamics on forest carbon stock in Sichuan Province and Chongqing City[J]. Acta Ecologica Sinica,2008,28(3):966-975.
[14] 徐期瑚,林麗平,薛春泉,等.廣東樟樹(shù)各器官含碳率及碳儲(chǔ)量[J].浙江農(nóng)林大學(xué)學(xué)報(bào),2019,36(1):70-79. XU Q H, LIN L P, XUE C Q, et al. Component specific carbon content and storage of Cinnamomum camphora in Guangdong Province[J]. Journal of Zhejiang A F University,2019,36(1): 70-79.
[15] 高海燕,楊制國(guó),張勝男,等.科爾沁沙地油松人工林林齡對(duì)土壤酶活性及化學(xué)性質(zhì)的影響[J].中南林業(yè)科技大學(xué)學(xué)報(bào), 2024,44(2):108-117. GAO H Y, YANG Z G, ZHANG S N, et al. Effects of stand age on soil enzyme activity and chemical properties of Pinus tabulaeformis plantation in Horqin sandy land[J]. Journal of Central South University of Forestry Technology,2024,44(2):108-117.
[16] LIU Y Y, WANG A Y, AN Y N, et al. Hydraulics play an important role in causing low growth rate and dieback of aging Pinus sylvestris var. mongolica trees in plantations of Northeast China[J]. Plant Cell and Environment,2018,41:1500-1511.
[17] 劉桂豐,楊傳平,楊書(shū)文,等.樟子松引種適生范圍的研究[J].東北林業(yè)大學(xué)學(xué)報(bào),1990,18(增刊2):122-128. LIU G F, YANG C P, YANG S W, et al. The adaptative range of Pinus sylvestris var. mongolica as exotic species[J]. Journal of Northeast Forestry University,1990,18(Suppl.2):122-128.
[18] 郎明翰,張日升,凡勝豪,等.科爾沁沙地南緣樟子松人工林碳匯及對(duì)氣候因子的響應(yīng)[J].水土保持學(xué)報(bào),2024,38(4): 236-245. LANG M H, ZHANG R S, FAN S H, et al. Carbon sequestration function of Pinus sylvestris var. mongolica plantation and its responses to climate factors on the douthern edge of Horqin sandy land[M]. Journal of Soil and Water Conservation,2024,38(4): 236-245.
[19] 黨宏忠,張學(xué)利,韓輝,等.樟子松固沙林林水關(guān)系研究進(jìn)展及對(duì)營(yíng)林實(shí)踐的指導(dǎo)[J].植物生態(tài)學(xué)報(bào),2022,46(9):971-983. DANG H Z, ZHANG X L, HAN H, et al. Research advances on forest-water relationships in Pinus sylvestris var. mongolica plantations for sand dune immobilization and guidance to forest management practices[J]. Chinese Journal of Plant Ecology, 2022,46(9):971-983.
[20] 田大倫,王新凱,方晰,等.喀斯特地區(qū)不同植被恢復(fù)模式幼林生態(tài)系統(tǒng)碳儲(chǔ)量及其空間分布[J].林業(yè)科學(xué),2011,47(9): 7-14. TIAN D L, WANG X K, FANG X, et al. Carbon storage and spatial distribution in different vegetation restoration patterns in Karsts Area, Guizhou province[J]. Scientia Silvae Sinicae,2011,47(9):7-14.
[21] 王春梅,邵彬,王汝南.東北地區(qū)兩種主要造林樹(shù)種生態(tài)系統(tǒng)固碳潛力[J].生態(tài)學(xué)報(bào),2010,30(7):1764-1772. WANG C M, SHAO B, WANG R N. Carbon sequestration potential of ecosystem of two main tree species in Northeast China[J]. Acta Ecologica Sinica,2010,30(7):1764-1772.
[22] 倪添,謝龍飛,董利虎.黑龍江省樟子松人工林含碳量估算方法的比較[J].生態(tài)學(xué)雜志,2023,42(7):1774-1782. NI T, XIE L F, DONG L H. Comparison of carbon estimation approaches for Pinus sylvestris var. mongolica plantation in Heilongjiang Province[J]. Chinese Journal of Ecology,2023,42(7): 1774-1782.
[23] 李春平,吳斌,張宇清,等.山東鄆城農(nóng)田防護(hù)林楊樹(shù)器官含碳率分析[J].北京林業(yè)大學(xué)學(xué)報(bào),2010,32(2):74-78. LI C P, WU B, ZHANG Y Q, et al. Carbon content of poplar in shelterbelt at Yuncheng County, Shandong Province[J]. Journal of Beijing Forestry University,2010,32(2):74-78.
[24] WIDAGDO F, LI F R, ZHANG L J, et al. Aggregated biomass model systems and carbon concentration variations for tree carbon quantification of natural Mongolian oak in Northeast China[J]. Forests,2020,11:397.
[25] 郎明翰,張日升,韓輝,等.科爾沁沙地南緣樟子松人工林對(duì)土壤水鹽的影響[J].水土保持學(xué)報(bào),2023,37(5):370-376. LANG M H, ZHANG R S, HAN H, et al. Effects of Pinus sylvestris var. mongolica plantation on soil water and salt in southern edge of Horqin sandy land[J]. Journal of Soil and Water Conservation, 2023,37(5):370-376.
[26] 玉寶.興安落葉松天然林自然整枝特征及其影響因子[J].浙江農(nóng)林大學(xué)學(xué)報(bào),2023,40(1):209-216. WANG B. Characteristics and impact factors of self-pruning in natural Larix gmelinii forest[J]. Journal of Zhejiang A F University,2023,40(1):209-216.
[27] 叢健,沈海龍.東北東部山區(qū)樟子松人工林生長(zhǎng)階段劃分和生長(zhǎng)進(jìn)程分析[J].森林工程,2016,32(3):16-20,26. CONG J, SHEN H L. Growth period division and growth rhythm analysis for trees in plantation of Pinus sylvestris var. mongolica in eastern maintain area of Northeast China[J]. Forest Engineering, 2016,32(3):16-20,26.
[28] 董利虎,李鳳日,賈煒瑋,等.含度量誤差的黑龍江省主要樹(shù)種生物量相容性模型[J].應(yīng)用生態(tài)學(xué)報(bào), 2011,22(10):2653-2661. DONG L H, LI F R, JIA W W, et al. Compatible biomass models for main tree species with measurement error in Heilongjiang Province of Northeast China[J]. Chinese Journal of Applied Ecology, 2011,22(10):2653-2661.
[29] ZOU W T, ZENG W S, ZHANG L J, et al. Modeling crown biomass for four pine species in China[J]. Forests,2015,6: 433-449.
[30] ZHAO D H, KANE M, TESKEY R, et al. Modeling aboveground biomass components and volume-to-weight conversion ratios for loblolly pine trees[J]. Forest Science,2016,62(5):463-473.
[本文編校:戴歐琳]