Carbon stocks of different land uses in the Kumrat valley,Hindu Kush Region of Pakistan

Adnan Ahmad?Syed Moazzam Nizami

Carbon stocks of different land uses in the Kumrat valley,Hindu Kush Region of Pakistan

Adnan Ahmad?Syed Moazzam Nizami

Changes in land use cover,particularly from forest to agriculture,is a major contributing factor in increasing carbon dioxide(CO2)level in the atmosphere. Using satellite images of1999 and 2011,land use and land use changes in the Kumrat valley KPK,Pakistan,were determined:a netdecrease of11.56 and 7.46%occurred in forest and rangeland,while 100%increase occurred in agriculture land(AL).Biomass in different land uses, forest land(FL),AL,and range land(RL)was determined by field inventory.From the biomass data,the amount of carbon was calculated,considering 50%of the biomass as carbon.Soilcarbon was also determined to a depth of0–15 and 16–30 cm.The average carbon stocks(C stocks)in all land uses ranged from 28.62±13.8 tha-1in AL to 486.6±32.4 tha-1in pure Cedrus deodara forest.The results of the study confirmed that forest soil and vegetation stored the maximum amount of carbon followed by RL.Conversion of FL and RL to AL notonly leads to total loss of about 56%(from FL conversion)and 37%(RL conversion)of soil carbon in the last decades but also the loss of a valuable carbon sink.In order to meet the emissions reduction obligations of the Kyoto Protocol,Conservation of forest and RL in the mountainous regions ofthe Hindu Kush will help Pakistan to meet its emissions reduction goals under the Kyoto Protocol.

Hindu KushKumrat valleyLand usesBiomassCarbon stocks

Introduction

Land-use,land-use change and forestry(LULUCF)contribute to ongoing anthropogenic climate change(Houghton 2003),and have consequently received increasing research attention over the lastdecade(Rokityanskiy etal. 2007;Running 2008;Smith 2008;Strassmann etal.2008; Zomer etal.2008).LULUCF is one of the five sources of greenhouse gases(GHGs)included in the United Nations Framework Convention on Climate Change(UNFCC) (UNFCCC 1992),and impact global GHGs emissions, biodiversity and land quality(Cowie etal.2007).However, LULUCF can also make a significant contribution to the reduction of GHGs,by increasing the carbon storage of terrestrial ecosystems(carbon sequestration),by conserving existing C stocks(e.g.by avoiding deforestation orland degradation),and by providing renewable energy(biomass production)(Andersson et al.2009).Such LULUCF activities are expected to provide a significant and costeffective way by which atmospheric CO2concentration can be reduced,at leastin the short-to medium-term(Nabuurs et al.2007).They can also assist countries in meeting part of their emissions reduction targets thatare being proposed for the years after the Kyoto Protocol’s first compliance period(2008–2012)(Gainza-Carmenates et al.2010). Furthermore,mitigation-driven LULUCF activities could have positive effects on the provision of other ecosystem services(Schroter et al.2005).

The effects of mitigation-driven LULUCF activities are expected to be regionally unique,as changes in C stocks depend on many regional factors including suitability for different land uses,and the effectiveness of policy for carbon sequestration(Nabuurs et al.2007).Detailed regional-level analyses are therefore needed to provide accurate estimates of LULUCF offsetpotentials,in orderto help achieve the GHGs targetreduction under a post-2012 climate agreement.Nevertheless,relatively few spatially explicit studies have been undertaken to date on the potential effects of land-use change on C stocks(Bolliger et al.2008;Tappeiner et al.2008).

The forests of Pakistan,especially the northern mountain forests,are rich in biodiversity and considered integral to the nationaleconomy.However they are under extreme threats from deforestation(Tanviretal.2007).The present study was carried out in the Kumrat valley of the Hindu Kush region.The aim of the study was to quantify C stock in differentland uses and to find outthe effectof land use conversion on C stocks.The objectives of the study were to estimate above-ground and below-ground biomass in different land uses and to estimate C stock in these land uses.

Materials and methods

Study area

The study was conducted in Kumratvalley Dir(U),Khyber Pukhtoonkhwa Khwa(KPK),which is located on the northwest side of KPK and to the north of Dir proper(Dir upper).The latitude and longitude of study area is 3532011.4400N 7213045.0100E.The elevation of the area ranges from 2,439 to 3,048 m.Average precipitation ranges from 1,200 to 600 mm.Major types of rocks in study area are granite,diorite,norites and schist.The soil is mostly loam or sandy loam.

Land use and land use cover change assessment

To assess land use and land use cover change,temporal images from 1999 and 2011 were downloaded from the website of US Geological Survey departmenthttp://glovis. usgs.gov/.These images were of 30 m spatial resolution. The images were putin ERDAS Imagine software and the area of interestwas clipped from a complete scene.Image enhancement techniques,such as NDVI(Normalized Difference Vegetation Index),was applied to enhance the vegetation.Then signatures for different classes,including forests,agriculturallands,range lands(RLs),barren lands, and water bodies were taken in the software ERDAS. Using these signatures,the entire study area was organized into defined classes and then the classified images were imported to ArcGIS.The area for each class of each year was calculated in ArcGIS and two maps(1999 and 2011) were prepared(Fig.1).In addition,forest maps,topographic sheets,and the 1995 working plan of the Upper Dir KPK were also used for land-use assessment.

Field enumeration in each land use

Overall60 plots(10 plots each in RL and agriculturalland, while 40 plots in forest land(FL)use;Fig.1)were laid out according to terrain,time,and budgetconstraint.The size of each plotwas 1 ha in FL,while in agriculture and RL,the size ofeach plotwas 0.1 ha.Plots were randomly located in study area(Fig.1).In each plotofFL,tree height(m),tree diameter (cm)atbreastheight(dbh)wasmeasured.Treeheight(m)was measured by Abney’s level.Tree volume(m3ha-1)of all sampling sites in each foreststand was calculated as:

where SV is stem volume(m3);h is the heightof the tree in meters;d2is the square of bdh and f is form factor.The calculated volume(m3ha-1)in each stand was multiplied with the basic wood density(kg m-3)of respective tree species to calculate total stem biomass.Wood density of the respective tree species was sourced from the available literature(Haripriya 2000).

where SB is the stem biomass(kg),SV is the stem volume, and WD is the wood density

Biomass expension factors(BEF)of the respective species were sourced from available literature(Haripriya 2000).The BEF was used to calculate the total biomass of an entire forest.In order to calculate the biomass of understory vegetation(Usv),rangeland,and AL,10 sub plots of 1 m2were laid outin each sample plot,then the vegetation was harvested and put in bags and their fresh weight was determined.The samples were dried in an oven at 72C for 48 h to obtain their dry weight.

Calculation of C stocks in each land use

The total C stock in each land use was calculated from total biomass.The totalbiomass of each land use was multiplied with conversion factor of 0.5 that has been used globally (Roy et al.2001;Brown and lugo 1982;Malhi et al.2004; Nizami2012).

Soil sampling and analysis

To calculate soil carbon,soil samples were taken from all sample plots of the respective land uses.Three soilsamples from each plot,at depths of 0–15 and 16–30 cm,weretaken by auger yielding soil cores of known volume 198.29 cm3(height=7.25 cm and diameter=5.9 cm). The weight of each sample was determined and the soil bulk density was calculated by dividing the weight of soil (gm)with the volume(cm3)of the core.Soil carbon was calculated,using the Walkley and Black method(1934). Total soil in tha-1was calculated by using the following formula(Nizami 2012).

Fig.1 Classified Image of the study area in years 1999 and 2011

where SC means Soil carbon(t ha-1),SOC-soil organic carbon(t ha-1),SBD-Soil Bulk density(gm cm-3),THThickness of horizon(cm).

Results

Land use and land use cover change

Based on satellite images from 1999 and 2011,land use and land use cover changes were determined,including the totalarea of each land use(Table 1).In 2011,four overall land uses—water bodies,FL,barren lands,and RLs—were identified in addition to one new land use,agriculture. Based on ground verification and surveys,FL was further classified into pure Pinus wallichiana forest(PPWF),pure Cedrus deodara forest(PCDF),pure Abies pindrow forest (PAPF),and mixed conifer forest(MCF).Stem density,stem volume,stem biomass,and totaltree biomass in FL

Table 1 Land use in 1999 and2011 in the study area

Table 2 Average stem density(D),basalarea(BA),volume(V),stem biomass(STB),totaltree biomass(TTBM)and totalbiomass(TBM)in each forest stand(FS)

In each forest,the stem density(No.of trees ha-1),stem volume(m3ha-1),upper-story vegetation biomass (USVB),and under-story vegetation biomass(uSVB; t ha-1)was calculated(Table 2).Stem density was maximum in MCF and minimum in PCDF.Stem density decreased with increases in diameter(Fig.2).The maximum basal area(m2ha-1)and volume(m3ha-1)was recorded in PCDF,followed by PAPF.The minimum basal area(m2ha-1)and volume(m3ha-1)was recorded in PPWF.The average stem biomass in the foreststand ranges from 304.2±37.7 to 548.33±36(t ha-1).The highest stem biomass was recorded in PCDF and lowest in PPWF.

In the present study,two forests(PCDF and PAPF) consist of old-age trees with large diameters,which resulted in more basal area,stem volume,and stem biomass as compared to PPWF and MCF.Stem volume and stem biomass has a direct relationship with basal area.In each foreststand,the relation of stem volume and biomass with basal area is given in Figs.3,4).In PPWF and MCF, there were fewer old-age trees.Total tree biomass in each forest was calculated using the allomatric equations.The value of above and below-ground biomass was calculated as 459.2.9±56.9 t ha-1in PPWF to 827.9±55.4 tha-1in PCDF.

Understory vegetation(uSV)in each foreststand mainly consisted of various grasses,forbs and shrubs.Among grasses Cynodon dacttylon,Agropyron dentatum,A.canaliculatum and Poa species dominates while major forbs are Caltha alba,Bergenia ciliate,Rumux dentatus,Pomi emodia,and Plantago major.In PPWF,the dominant uSV were grasses with an average understorey biomass equals to 1.69 t ha-1.The mean biomass of uSV in PCDF was 1.1 t ha-1.The mean uSV biomass in MCF and PAPF was 1.6 and 2.6 t ha-1.In PPWF and MCF,the USV mainly consisted of grasses with associated woody shrubs and forbs,which resulted more biomass as compared to PCDF and PAPF.

Fig.2 Relationship between stem density(No.of trees ha-1)and stem diameter(cm)in pure Pinus wallichiana forest(PPWF),pure Abies pindrow forest(PAPF),pure Cedrus deodara forest(PCDF), mixed conifer forest(MCF),respectively

Total biomass in agricultural land(AL)and rangeland (RL)

The mean biomass of AL was 2.91±0.870 t ha-1.The mean biomass of RL was 5.86±2.788 t ha-1.In RL, grasses were the dominant vegetation.Species like Artemisia spp,Indigofera wallichiana,Rosa webbiana and Berberis lyceum were also found in RL.

Fig.4 Relationship between stem biomass and basal area in pure Pinus wallichiana forest(PPWF),pure Abies pindrow forest(PAPF),pure Cedrus deodara forest(PCDF),mixed conifer forest(MCF),respectively

Calculation of C stocks in each land use

C stock in each land use was calculated from the total biomass.Details of C stocks in each land use are given in Table 3.The study revealed that among the different land uses FL holds maximum C stocks followed by RL.The forests of the study sites consisted of mature trees.The value of%CV in case of PCDF and PAPF yielded little variation as compared to PPWF and MCF.In PCDF and PAPF,the uniform nature(same age and diameter)of vegetation resulted in little variation.In RL,the sample plots where the vegetation was mixed(grasses,forbs andwoody spp)had more biomass and higher value of C stocks.The sites where dominant vegetation was either grasses or forbs contained a minimum value of carbon. Similarly in AL in some sites,the contribution of weed biomass was greater,which gave higher values of biomass and carbon,while on other sites,the weed contribution in biomass was less,therefore responsible forminimum value of biomass and carbon.

Table 3 C-stocks and total ecosystem C-stocks in each land use

Soil carbon calculation in all land uses

The mean soil carbon in PPWF,PAPF,PCDF,MCF,AL and RL was 63.3,72.12,75.03,71.4 and 27,47.1 t ha-1, respectively.Among allland uses,FL holds the maximum soil carbon(70.78 tha-1),followed by RL(47.05 tha-1) while the AL hold minimum soil carbon of 28.62 tha-1. FL,particularly PPWF and RL,were converted to AL in last 10 years.It can be concluded from the present study that forest and RL conversion to AL resulted in a loss of 43.78 t ha-1atthe rate of 3.46 t ha-1a-1in the forestand 20.05 t ha-1(at the rate of 1.673.46 t ha-1a-1)in rangeland from 1999 to 2011.

Total C stocks in allland uses

The total C stocks in each land use was determined from respective componentsofcarbon.Thecomponentsofcarbon in each land use were the totalbiomassofvegetation and soil carbon(Table 3).Among the land uses,FL hold the maximum amountofcarbon of349.84±30.79 t ha-1,followed by RL(50±6.5 t ha-1).Minimum carbon stocksamong all land was recorded in AL(28.62±13.85 tha-1).Itcan be concluded from the results of presentstudy thatforestsoil and vegetation stored the highest level of carbon as compared to otherland uses.Deforestation in the study area not only caused an addition release ofcarbon to the atmosphere butalso destruction ofvaluable sink ofcarbon.

Discussion

The value oftotalbiomass in the presentstudy ranged from 437.76±76 tha-1MCF to 809.91±76.03 tha-1PCDF. Thehighestlevelofbiomasswasrecorded in PCDF followed by PAPF.Thesebiomassvaluesarecomparablewith thosein Gupta and Sharma(2011)in India.The forest stand was comprised of old age trees with high tree density(fully stocked),which resulted in more biomass and C stocks. PCDF and PAPF stored more carbon compared to othertwo forests(PPWF and MCf)thatcontained 405.77±38.24 and 266.50±19.tha-1,respectively.Similarresultsin Cedrus deodara and Abies pindrow forest have been reported by Gupta and Sharma(2011).Old growth foresthad more carbon stocks because of more tree layer biomass,which is a time-dependentaccretion of carbon(Zang etal.2012).

Soil carbon is an integral part of a particular ecosystem. Soilcarbon ranged from 35.033 t ha-1(AL)to 70.78 tha-1(FL).The presentstudy revealed thatamong differentland uses,FL had more soilcarbon followed by RL.The resultsof the presentstudy also showed thatin allfour foreststands, PAPF held the maximum soilcarbon(75.02 t ha-1).Gupta and Sharma(2011)reported soil carbon of 132±22.73, 120.35±25.86,and 85.67±30.20 t ha-1in the Abies pindrow and Picia smithina mixed forest,Cedrus deodara and Pinus wallichiana forests of India respectively.In FL, they estimated an average soilcarbon as78.49 tha-1,while in horticulture and grassland,they estimated an average soil carbon of 45.13±27.25 and 75.76±44.00 tha-1, respectively.The presentstudy also showed the same pattern of higher soil carbon in respective forest stands and other land uses.The conversion of forestand RL to agricultural land can be linked to the rapid increase in population and migration of people to upland area.The present study revealed that the area was under high pressure from local people regarding forestand RL degradation and conversion to AL.The results indicated thatFL stored the highestlevel ofcarbon followed by RL.These differencesin totalcarbon in each land use confirmed thatconversion of FL and RL to AL caused enormous carbon losses.Across the land uses, totalmean C stocks range from 28.62±13 t ha-1in AL to 477.82±39.5 t ha-1in PCDF.The differences of C stocks in different land uses are consistent with Sharma and Rai (2007).

Land use change,particularly from forest to AL,is the most significant factor in terms of change in C stocks around the globe(Lietal.2008).Forests have the ability tostore 20 to 100 times more carbon ha-1than cropland and upon conversion of forest to agricultural land(Houghton 2003).The same results were recorded in the present study where the PCDF contain about 20 times more carbon as compare to AL.

Zang etal.(2012)pointed outthat soildisturbance due to site preparation and tree planting reduces soil carbon. Sharma and Rai(2007)reported that soil carbon loss is greater(92%)in cropped areas as compared to forests due to disturbances.The grass land conversion to cropland decreases carbon content in soil(Yan et al.2009).Conversion of forest into cropland reduced the amount of soil carbon by 32%over 15 years(Fantaw etal.2007).Similar results were found in the present study.Conversion of FL resulted in a loss of56%ofsoilcarbon ata depth of30 cm over the lastdecade.The conversion of RL to AL resulted loss of 37%of soil carbon at a depth of 30 cm.Agricultural practices like cultivation,removal of vegetation cover,and exposure of soilto erosion caused a significant reduction in soil carbon.

The results of the present study corroborated that forest soil and vegetation sustained more carbon than AL.Similarly,RL soil and vegetation hold more carbon than AL, soiland vegetation.The results of the study confirmed that conversion of FL and RL to AL caused loss of 29.15 and 4.16 t ha-1a-1carbon from 1999 to 2011 respectively. Afforestation,reforestation,and rehabilitation of degraded forest and RL can play in important role in mitigation of atmospheric carbon dioxide.The area has greatpotentialin term of carbon trading under CDM of Article 12 of Kyoto protocol.Proper management of land,control of deforestation,reforestation of degraded land,and rehabilitation of degraded RL can be significant steps for carbon sequestration in the study area and inclusion in carbon trading.

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15 August 2013/Accepted:24 January 2014/Published online:8 January 2015

The online version is available at http://www.springerlink.com

Corresponding editor:Hu Yanbo

A.Ahmad

Shaheed Benazir Bhutto University,Sheringal,KPK 18050, Pakistan

S.M.Nizami(&)

Arid Agriculture University,Rawalpindi,Punjab 46300, Pakistan

e-mail:moazzam.nizami@uaar.edu.pk