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    Carbon storage in biomass,litter,and soil of different native and introduced fast-growing tree plantations in the South Caspian Sea

    2018-03-19 05:08:28JamshidEslamdoustHormozSohrabi
    Journal of Forestry Research 2018年2期

    Jamshid Eslamdoust?Hormoz Sohrabi

    Introduction

    Forests store more carbon per unit area than any other terrestrial ecosystem(Daryaei and Sohrabi 2015;Temesgen et al.2015).However,exploitation of resources and conversion of forest to others land uses have contributed to the decline and degradation of temperate forests.Fortunately,reforestation projects have gained much interest worldwide:at present,about half of the overall increased area of tree plantations is on natural forest lands(Chen et al.2013).

    Planted forests(plantations)can produce wood material for industrial uses and fuel(Bargali et al.1992a,b,1993;Bargali and Singh 1991,1995).During the last two decades,in response to worldwide increase in wood demand,fast-growing species in plantations have gained large interest(FAO 2010).According to theMillennium Ecosystem Assessment,plantations ful fi ll more than one third of the world demand for wood products.Furthermore,the establishment of plantations can be proposed as a tool for forest restoration of degraded lands(Phongoudome et al.2012).

    In addition,plantations are ef fi cient sequesters of carbon and can mitigate the predicted rise in atmospheric CO2concentration and future climate change(Zhang et al.2012).According to FAO(2010),total present C storage in forest plantations is approximately 11.8 Gt with an increase of 0.178 Gt a-1(Phongoudome et al.2012).

    In Iran,initial reforestation projects were aimed at wood farming.These initial projects began as early as 1989.Because of the substantial number of monoclonal plantations in northern Iran,the nation was ranked tenth globally among other countries based on the size of planted forests(FAO 2006).Based on the of fi cial report of the Forests,Rangelands and Watershed Management Organization of Iran,to date,more than 158,650 hectares of plantations have been established.But still there is little information about the contribution of these plantations to carbon sequestration.

    Numerous factors affect the magnitude and progress in C storage,such as tree species,which can strongly affect the C accumulation of an ecosystem(Gao et al.2014).The growth rate of different trees,biomass allocation to different tree parts,and varying rates of carbon sequestration in ecosystem components can all affect the rate of carbon sequestration and longevity of carbon storage.Moreover,the portion of sequestered C in different components of trees,such as in the leaf,stem,or branch(referred to as allocation of biomass)can affect the ecosystem carbon cycle and longevity of carbon storage.For this reason,selecting a suitable species for cultivation is an important part of plantation projects.

    The objectives of this study were o characterize the storage and distribution of aboveground biomass and carbon in the bark,stems,branches and leaves of the trees.The results of this research will provide information for future site management strategies and species selection aimed to conserve site productivity or replenish soil fertility.

    Materials and methods

    Study area

    The study was conducted in two regions with same climatic conditions as the southern coast of the Caspian Sea,Mazandaran Province,Northern Iran:Klodeh(in 36°35′N,52°10′E)and Chamestan(in 36°29′N,51°59′E).These regions have a temperate climate(Fig.1),with a mean annual temperature of 16.9?C.The mean annual precipitation is 802–823.5 mm and most of precipitation falls between September and March.This region has a distinct dry season that stretches from April to August.The topography is characterized by fl at lands to low hills at an elevation of 5 and 100 m above sea level for the Klodeh and Chamestan sites,respectively.The site soil texture is silt-loam with poor drainage.The average pH ranges between 7.6 and 8.1.

    Fig.1 Location of study sites in northern Iran

    Historically,the study sites were occupied by a temperatedeciduousforestdominated byQuercuscastaneifoliaC.A.Meyer.,GleditschiacaspicaDesp.,Carpinus betulusL andParrotia persica.Three tree species includingAlnus subcordataC.A.Mey(three stands),Populus deltoidesBartr.Ex Marsh(three stands),andTaxodium distichum(L.)L.C.Rich(Two stands)were planted in 1992 after clear cutting with the aim of wood production.The plantations were established at an initial spacing of 625 trees ha-1.No thinning operations were made in these plantations.A description of the study sites is presented in Table 1.

    Experimental design,sampling and laboratory analysis

    In 2014,48 sampling plots(16×16 m)were set up in eight stands replication of the three species(6+6+6 forA.subcordataandP.deltoides,and 6+6 forT.distichum)based on a systematic random design.To estimate tree biomass,the diameter at breast height(DBH,at 1.3 m)and total height of all individual trees on plots was measured by caliper and Haglo f-VERTEX IV hypsometer,respectively.Three quadrants of shrubs(at 2×2 m each)and three quadrants of herbaceous vegetation and litter(at 1×1 m each)were established diagonally within each sampling plot(He et al.2013).In each quadrant,main species of shrubs and herbs were recorded based on canopy coverage and all were harvested.Additionally,all litter was were collected from the quadrants.Samples of litter and understory vegetation were taken to the laboratory and dried at 65°C to a constant weight for determination of dry matter and carbon fraction.The carbon concentrations of allsamples including aboveground components were measured by the dry combustion method.

    Table 1 Site properties and three plantation stand characteristics in the study area

    Mineral soil samples were taken from depths up to 100 cm in six plots from each stand.At each plot,three soil samples were extracted from fi ve depths(0–20,20–40,40–60,60–80 and 80–100 cm)using a soil corer.Soil samples from the same layer were mixed and one representative sample was taken to the laboratory.In addition,from each soil layer in the three plots of each stand,three samples were taken to determine the bulk density of soil.Soil samples were air dried and sieved with a 2 mm sieve and analyzed for total soil carbon concentration by Walkley–Black method.

    Destructive tree sampling

    Based on the DBH and height of the surveyed trees,we selected 36 trees(4+4+4 forA.subcordataandP.deltoides,and 6+6 forT.distichum)in different diameter classes,which were harvested during the summer.The trunks were marked in three parts(bottom,middle,and top),cut into 2 m sections,and weighed.The total weight of each stem was then calculated by adding up the component masses for all sections.At the end of each trunk section,we cut a 5 cm-thick disk.We then transferred samples to the laboratory and measured wood density,using the water replacement method.

    For each stem disk,we used hand tools to separate the bark and then measured fresh weight for the wood and bark of each stem disc to determine the portion of bark.We collected and separated branches,twigs,and leaves as well.We measured the fresh weight of each component(branch,twig,and leaf)to the nearest 0.1 kg in the fi eld.Approximately 300 g of fresh sample of each tree component was collected;this quantity was randomly collected for moisture and carbon content determination.Allsampleswerelabeledandtransportedinplasticbagsto the laboratory.Samples of each component were weighed the same day on an electronic balance(accuracy 0.1 g),and dried at 70°C until they reach a constant weight.The total dry biomass for each component was calculated by multiplying the fresh weight by the dry/wet ratio.Total abovegroundbiomassforeachtreewascalculatedbysummingthe biomass of its trunk,branch,twig,and leaf.

    Data analysis

    In determining the independent variable for allometric equations,we multiplied the square of DBH by the tree’s total height.We employed curve fi t analysis to drive the equations between biomass and an independent variable,and we selected optimum allometric equations to calculate the component biomass of other trees in the plots.We calculated carbon storage of both understory and litter by multiplying the carbon fraction with component biomass.We calculated soil carbon storage from the carbon fraction by multiplying by the bulk density,and the thickness of the soil layer.To assess the differences in carbon content and storage of among different tree components as well as different plantations,we applied a one-way analysis of variance(ANOVA),and we carried out multiple comparisons using Duncan’s method,with differences in theP<0.05 signi fi cance level.

    Results

    Biomass and carbon storage of tree level

    Tree biomass of different plantations was estimated based on the component allometric equations(Table 2).Interspeci fi c differences in tree biomass were signi fi cant(F=45.96,P<0.001),and the order of individual tree biomass wereasfollows:P.deltoides>A.subcordata>T.distichum(Table 3).Annual biomass increments were 11.23±2.39, 7.77±2.75, 6.17±1.49 kg tree year-1,respectively.With all species,the trunk of the trees account for the largest proportion of aboveground tree biomass while the leaves represent the smallest proportion,particularly forP.deltoides,with the trunk and leaves representing 81.58% and 2.28 of the total biomass,respectively.

    The results of a two-way analysis of variance showed thatthe carbon fractions among the tree species(F=30.58,P<0.001)as well as the separate tree components(F=94.35,P<0.001)were signi fi cantly different.Based on multiple comparisons of means,the carbon fraction ofA.subcordatawas signi fi cantly higher than others,but there were no signi fi cant differences betweenP.deltoidesandT.distichum.Also,the carbon fraction of the different components decreased following the order of wood>twig>bark>leaf(Table 4).

    Based on analysis of variance,signi fi cant interspeci fi c differences were found between the stand tree biomass(F=15.62,P<0.001)and carbon storage(F=14.81,P<0.001).The biomass storage ofP.deltoides(206.6±47.8 Mg ha-1)was higher than the others,while there was no signi fi cant difference betweenA.subcordata(134.5±55.0 Mg ha-1) andT.distichum(123.3±29.7 Mg ha-1).Tree carbon storage decreased in this order:P.deltoides>A.subcordata>T.distichum(Fig.2).

    Table 2 Allometric equation for different component of the planted tree species

    Table 3 Biomass of component(kg per tree)of different tree species

    Biomass and carbon storage of understory

    There was no signi fi cant difference between the biomass of understory vegetation(including shrubs and herbs)ofA.subcordataandP.deltoidesand there was no vegetation coverage observed beneath theT.distichumplantation.The biomass of litter signi fi cantly differed among the three plantations(F=18.24,P<0.001).TheT.distichumplantation had signi fi cantly higher litter biomass(8.49±3.71 Mg ha-1)than the other two plantations.The amount of biomass of litter was statistically the same forP.deltoides(2.27±1.11 Mg ha-1) andA.subcordata(3.12±0.70 Mg ha-1)(Fig.3).

    Since the species composition of understory vegetation ofP.deltoidesandA.subcordataplantations were the same,we measured the carbon fractions together.Based on the results,there was no signi fi cant difference between the carbon fraction ofshrubs (45.2±0.02)and herbs(45.4±0.03).Litter carbon fraction was signi fi cantly different among plantations(F=97.7,P<0.001)and their order deceased in this manner:P.deltoides>A.subcordata>T.distichum(Table 5).

    Table 4 Tree componentC fraction (%)in three plantation(mean±SD)

    Fig.2 Tree biomass and carbon storage of different plantations.Note:signi fi cant differences in tree biomass or carbon storage among plantations are indicated with lowercase letters(P<0.05).Vertical lines are SD

    Fig.3 Component biomass of different plantation.Note:signi fi cant differences among plantations are indicated with lowercase letters(P<0.05).Vertical lines are SD

    Despite the high variability between the plantations in terms of carbon storage of different components of the understory,there was no signi fi cant difference among the plantations for the total carbon stored in the understory.Additionally,there was a common tendency among all species,that the litter represented a large proportion of the understory carbon storage;especially forT.distichum,where there was nothing but litter beneath the trees.P.deltoidesandA.subcordataplantations displayed a similar pattern for the proportion of the stored biomass in the understory components(Fig.4).

    Soil carbon fraction and storage

    The mean values of carbon fraction decreased with increasing of soil depth.The rate of this decline showed a sharp change in 0.5 m depth of the soil;the carbon fraction decreased by 50%from 20–40 to 40–60 cm.These patterns were the same for all plantations.The soil pro fi le indicated that the carbon fractions of soil were statistically similar for the different plantations(Fig.5).The amount of carbon stored per hectare was obtained considering soil depth(cm),bulk density(g cm-2)and carbon fraction of each depth.A.subcordatahad the highest soil carbon storage(555.51±52.3 Mg ha-1),while there was no signi fi cant difference betweenT.distichum(425.17±44.2 Mg ha-1)andP.deltoides(440.12±25.7 Mg ha-1)plantation for carbon storage(Fig.6).

    Forest ecosystem carbon storage

    Figure 6 summarizes the carbon storage of the different components of each ecosystem and the total ecosystem carbon storage in the three plantations.Based on the results,carbon storage in ecosystem is ranked in the order of soil>living aboveground biomass>litter.Also,there were signi fi cant differences in forest ecosystem carbon storage among plantations(F=13.73,P<0.001).The total ecosystem carbon storage ofA.subcordata(626.57±80.96 Mg ha-1)was higher thanP.deltoides(542.90±49.24 Mg ha-1)andT.distichum(486.76±59.66 Mg ha-1).

    Table 5 Carbon fraction(%)of understory in three plantation(mean±SD)

    Fig.4 Understory carbon storage of different plantations.Note:signi fi cant differences among plantations are indicated with lowercase letters(P<0.05).Values in parenthesis are percentages of component to the total understory biomass.Vertical lines are SD

    Discussion

    Tree biomass and carbon at tree and stand level

    Biomass production of fast-growing trees could be proposed as an economic and ecological solution to meet the demand for energy and shortage of raw materials for woodbased industries(Licht and Isebrands 2005).Also,they can be considered as a high potential for mitigation of greenhouse gases and for carbon sequestration(Baishya and Barik 2011).Since both area and budget for plantations are always limited,selecting the best species for producing more wood and for storing more carbon is a challenging topic.In our research,we tried to address this challenge to present the best fast-growth species for plantation in temperate ecosystems.

    To calculate the biomass of standing trees,most scholars have used the variables DBH,tree height,or a combination for predicting the biomass(Rance et al.2012).Here,tree diameter and tree height were used for predicting the biomass.The goodness-of- fi t of the equations was satisfactory,because the power functions,using a combination of DBH and H,could explain more than 98% of the variability in the observed total aboveground tree biomass of all species.Arora et al.(2014)developed allometric equations to estimate biomass and biomass carbon in different tree components ofPopulus deltoides,which had adjusted R squares greater than 94%.

    Because of inherent variation in growth rate(Fonseca et al.2012;Nelson et al.2012),interspeci fi c differences in tree biomass among different species grown in similar conditions can be expected(Gao et al.2014).In this study,tree biomass was signi fi cantly different among the three plantations in thatP.deltoideshad higher amount of tree biomass than other two species.

    Fig.5 Changes of soil carbon fraction(a)and soil carbon(b)in different depth(0–100 cm)of different plantations.Note:vertical lines are SD

    Fig.6 Ecosystem carbon storage of different plantations.Note:signi fi cant differences in aboveground live biomass,litter,soil and ecosystem carbon storage among plantations are indicated with lowercase letters(P<0.05).Vertical lines are SD

    The pattern of biomass allocation also varies among planted species.P.deltoeidesallocated more biomass and carbon to the stem(81%).Since poplars usually do not produce large branches or a large amount of leaves,its main stem contributes most to the aboveground biomass.This characteristic also provides a good potential for industrial wood production.Similar results have also been reported by Mishra et al.(2010)is semi-arid zone of India.

    Per-hectare tree biomass and carbon accumulation ofP.deltoideswas also higher than other two species.The rate of this production is a multiplication of tree growth rate and survival.Since the survival rate ofP.deltoideswas 100%and its growth rate was higher than other two species,a higher rate of per hectare biomass and carbon accumulation could be expected.Previous research has shown advantages of poplar species for biomass and carbon storage over other species:poplars thrive in a large range of climate conditions and soil types(Zabek and Prescott 2006).

    Carbon fraction and biomass allocation

    Much of the literature usually estimates carbon content in biomass by using a standard carbon proportion of 50% of dry weight,butrecentresearchhasshownthattheCconcentration of tree components or tree species may be either above or below 50%(e.g.Herrero et al.2011;Fonseca et al.2012).

    We analyzed the carbon content in all components and found a mean value of 48.0%(±1.6),46.4%(±2.3),and 46.2%(±2.0)forA.subcordata,P.deltoidesandT.distichum,respectively.Our results were consistent with Ragland and Aerts(1991),who reported concentrations of carbon in hardwood species of between 47 and 50% of dry weight.Tillmanetal.(1981)reportedaveragesof50.2%carbonfor11 hardwoods and 52.7%carbon for softwoods,while Lamlom and Savidge(2003)showed that the carbon content ranged from46.27to49.97%andforhardwoodand47.21–55.2%for softwood species.Mandre et al.(2012)determined C content ofPopulustremulaandP.tremuloidesonplantationsatRapla andKunda46.26and46.74%,respectively.Aroraetal.(2014)reported mean carbon concentration in the aboveground componentsofP.deltoidesvariedfrom39.7to51.7%inTarai ForestDivisioninUttarakhand,India.However,speciestype,analysis method,stand age,ecological conditions,section of the tree sampled,and the tree’s origin are considered as potential causes of this inconsistency.

    C storage and C fraction of vegetation understory

    Understory plays a major role in forest fl uxes and stocks balances.Generally,development of understory vegetation biomass and biodiversity depends on various factors including plantation age,light intensities under different canopies,the undergoing operations,site fertility(nutrient availability),soil moisture,landscape position(alluvial vs.upland),and rotation length.Species selection can affect growth and diversity of understory plant biomass because different species have different growth rates and tree architecture that,in turn,may affect light availability in the understory(Fortier et al.2010).In our study,no understory vegetation was observed on theT.distichumplantation’s ground.Very low canopy openness,chemical properties,and secondary chemicals(high concentrations of tannins and phenolics in its leaves)and thickness of litter layer explain the cause of extremely poor development of vegetation understory biomass in theT.distichumplantation.

    Based on our fi eld observations,this species produces a thicker canopy cover that limits light penetration.This stand characteristic can limit growth and development of understory layer.Since the decomposition rate ofT.distichumlayer is slow,the tree leaves of this species pile up and produce a very thick layer of litter which signi fi cantly limits the germination and growth of any vegetation.

    In this study,understory vegetation does not signi ficantly contribute as an additional carbon pool(less than 3%).Generally,plantation understory particularly in younger stands is not well developed.

    C storage and C fraction of litter layer

    Decomposition of plant litter is closely determined by its litter quality(C/N ratio)(Thomas and Williams 2014).Because of the high concentration of soluble carbohydrates and low concentration of lignin,the decomposition rate of the deciduous leaf litter is greater than other trees.Based on the lower rate of decomposition ofT.distichum’s leaves,higher amounts of litter carbon storage forT.distichumplantations could be expected.Berg(2000)stated that conifer litter contains more components that are diffi cult to decompose than broadleaf litter,resulting in a higher rate of litter accumulation on the forest fl oor.Sun et al.(2004)and Bradford et al.(2008)also reported that forest fl oor C accumulation of conifers is greater than that of broadleaf.

    Also,our analysis highlights the fact that litter carbon does not contribute signi fi cantly to the overall aboveground carbon budget(1.94,1.03,and 4.99%forA.subcordata,P.deltoidesandT.distichum,respectively).This is mainly because the stands are not still well developed.

    The mean C concentrations of litter layer ranged from 36%inT.distichumstand to 43%inP.deltoids,which is within the range reported by earlier researchers.Therefore,applying standard C concentrations of 45–50%may cause signi fi cant errors in the upscaling of C pools.

    C storage of soil

    Litterfall and rhizodeposition are two main inputs for the increasing proportion of soil carbon,while the decomposition of soil organic matter mainly decreases soil carbon(Lee et al.2015).Carbon stocks are determined by the balance between these input or output patterns—which,in similar environmental conditions,are controlled mainly by tree species.Tree species determine the composition of the litter and the abundance and activity of soil microbes,fauna and fl ora.Also,the allocation strategy of different species can result in different patterns,rate,quality,and quantity of organic carbon input to the soil.

    In our study,A.subcordata(519.1 Mg ha-1)had the highestrateofsoilcarbonstorage.Onereasonforthehighrate is the higher rate of leaf production in this species.Based on our fi ndings,itproducesfourto fi vetimesmoreleavesthanthe other two species.In addition,the carbon content of biomass forA.subcordatawas higher in comparison to other species.

    Forest ecosystem C storage

    Based on our fi ndings,soil carbon(SC)storage was the largest carbon pool in the ecosystem throughout the three plantations(78–87% of ecosystem carbon storage).The differences in ecosystem C storage among plantations were mainly determined by the magnitude of SC pool.On the global scale,forest soils hold about twice as much carbon as tree biomass(Chen et al.2013).However,C storage in forest ecosystems,offer a lot of goods and services such as restoration/rehabilitation of degraded lands,wildlife habitat,watershed,soil protection,and scenic views beside timber production(Redondo-Brenes 2007).

    Results of the present research demonstrate that changes in tree species can highly affect carbon-storage values.Also,we fi nd that broad leaves can store more carbon in soil and living biomass than conifers.But it should be pointed out the choice of species for plantation projects should generally not be made with reference to carbon storage alone,but instead also in consideration of other factors such as biodiversity and recreation values.

    AcknowledgementsThe trees sampled were provided by Klodeh plantation in northern Hyrcanian forests.We thank Eng.Bahram Naseri and Ehsan Fakour for their valuable help in fi eldwork.Also,we greatly appreciate the help of Laura Clark Briggs(Middle Tennessee State University)for fi nal editing of the English text.

    Author’s contributionJE Field works and collecting the data,the laboratory analysis,running the data analysis,and writing the paper.HS Designing the experiment,supervising the work,running the data analysis,and writing the paper.

    Compliance with ethical standards

    Con fl ict of interestThe authors declare that they have no con fl ict of interest.

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