Characterization of soil erosion and its implication to forest management

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1 Journal of Envronmental Bology Aprl 7, 8() 85-9 (7) Trven Enterprses, Lucknow (Inda) For personal use only Free paper downloaded from: www. jeb.co.n Commercal dstrbuton of ths copy s llegal Characterzaton of sol eroson and ts mplcaton to forest management Nuray Msr*, Mehmet Msr, Uzay Karahall and Hakk Yavuz Faculty of Forestry, Karadenz Techncal Unversty, Trabzon-6 8, Turkey (Receved: November 5, 5 ; Revsed receved: June 5, 6; Re-revsed receved: July, 6; Accepted: August, 6) Abstract: Forests have tradtonally been managed to maxmze tmber producton or economc proft, completely neglectng other forest values. Nowadays, however, forests are beng managed for multple uses. The basc requrement of multple use forestry s to dentfy and quantfy forest values and to determne management objectves. The prortes of management objectves, however, must be decded. In ths study, a model predctng the sol loss for mult objectve forest management was developed. The model was based on data from remeasurement of permanent sample plots. The data were gathered from sample plots. Approxmately 8% of the observatons were used for model development and % for valdaton. The model was desgned for even aged and uneven aged forests, as well as for forests wth mxed and pure speces composton. The explcatory varables n the model were mean dameter and number of trees. All parameter estmates were found hghly sgnfcant (p<.) n predctng sol loss. The model ft and valdaton tests were farly good. The sol loss model presented n ths paper was consdered to have an approprate level of relablty. It can be used n the overall mult-objectve forest management plannng, but, t should be lmted to the condtons for whch the data were gathered. Key words: Forest values, Sol loss, Regresson analyss, Multobjectve plannng Introducton Nowadays, multobjectve plannng s necessary n forestry because of ncreased and vared demand for forest products and servces. Management objectve such as producton of qualty potable water, aesthetc, recreaton and communty health n forest especally adjacent to bg ctes are of great mportance. Forests have managed to produce wood products at varous dameters and qualty classes as the socety demanded overtme. Afterwards, the mportance of these objectves has gradually dmnshed and overwhelmed by other management objectves such as conservaton of water resources, preventon of sol eroson, creaton of landscape aesthetc, camouflagng mltary facltes and allocaton of land for recreaton (Asan, 99). Eroson, the detachment of sol partcles, occurs by the acton of water, wnd or glacal ce. Such background sol eroson has been occurrng for some 5 mllon years, snce the frst land plants formed the frst sol. Only eroson caused by water wll be consdered here. Water related eroson occurs when randrops, sprng runoff or floodwaters wear away and transport sol partcles. Sol eroson by water and wnd affects both agrculture and the natural envronment, and s one of the most mportant of today s envronmental problems. It sn t easy to fnd comprehensve nformaton about eroson, as the subject s multdscplnary nvolvng geomorphologsts, agrcultural engneers, sol scentsts, hydrologsts and others and s of nterest to polcy-makers, farmers, envronmentalsts and many other groups. Sol loss estmaton: Gven the mportance of sol eroson, characterzaton of sol loss s equally mportant. In eroson control plannng, sol loss estmates for a partcular ste are determned usng a predcton model and compared wth a T-value for that ste (Schmt et al., 98). The Unversal Sol Loss Equaton (USLE) s an example of a model used extensvely to predct eroson from croplands and rangelands (Wschmeer and Smth, 978). Untl recently, predcton of sol loss rates on Natonal Forest lands nvolved usng the USLE(Wschmeer and Smth, 978; Dsmeyer and Foster, 98). Sol losses were evaluated n the context of potental sol losses, natural sol losses, current sol losses and tolerable sol losses. Potental losses were those that would occur after complete removal of the vegetaton and ltter. Natural losses were assocated wth the potental natural vegetaton communty. Current losses were those occurrng wth current management. Tolerable loss was assumed to be the rate that can occur whle sustanng nherent ste productvty (Megahan, 99). Sol loss rates have been generally estmated n agrcultural areas up to now. Varous USLE and GIS combnatons have been used to estmate sol loss n forest land. But n these studes, sol loss was determned quanttatvely. Forest values ncludng sol protecton functon need to be determned quanttatvely n multobjectve forest management plannng. Relatonshps between sol loss and stand structure on a partcular ste must be determned before ncorporaton of sol *Correspondng author: E-Mal: nuray@ktu.edu.tr, Tel.: , Fax: Journal of Envronmental Bology Aprl, 7

2 86 protecton values nto multobjectve forest management plans. So far, very lttle nformaton has been found about the characterzaton of sol loss wth respect to stand structure on varous stes. The am of the present study was to develop sol loss model applcable for mult objectve forest management plannng. The model should nclude regular sol loss estmaton (not floods). It should be applcable to both even aged forest as well as forest wth mxed and pure domnated spruce speces. Snce the sol loss model also should be applcable to large scale forestry scenaro analyss n practcal management plannng, the modelng was restrcted to nclude only explcatory varables that drectly and ndrectly are avalable from practcal forest nventory data (ncludng sol data). Materals and Methods Ths study was conducted n Blacksea regon n Trabzon, Turkey. Alttude of ths area ranges from m to m. Hgh productve forest study area s 5.5 ha of whch 7 ha s unproductve hgh forest, 8 ha s coppce forest and 56.5 ha s unproductve coppce. Data were collected from permanent sample plots, dstrbuted to study area wth m x m ntervals. Sample plots were taken from pure and mxed spruce stands n Karadenz Techncal Unversty, Faculty of Forestry. Plots were taken from thnned stands and located on fve dfferent stes. Areas of rectangular plots vared from m to 8 m. For each plots, all trees were measured for dameter at breast heght (dbh), dameter at stump level, total heght, age and crown dameter n 997. For each plots slope, alttude and aspect were also measured. In sample plots n forested area, dbh and heghts of all commercal trees over 8 cm dbh were measured. Number of trees per hectares, basal area, stand volume, quadratc mean dameter, and mean heght were calculated for each sample plots. These values were calculated to be (zero) for sample plots taken from bare land. Stand characterstcs were computed from ndvdual tree measurements n the plots. Volume per hectare (V), basal area (BA), basal area mean dameter ( d q ), mean heght weghted by basal area ( h q ), stand densty ndexes (Curts et al., 98; Reneke, 9; Drew and Flewellng, 977), Tree Area Rato Densty Index (Chsman and Schumacher, 9) and number of trees per hectare (N), some sol and physographc propertes and observed sol loss amounts are gven n Table. Table - : Statstcal evaluaton of stands n the study area Stand parameters/ Mn Max Mean S.D.* Characterstcs Sol loss (ton/ha/year) (A) Mean dameter ( d q (cm)) Mean heght ( h q (m)) Age (t (year)) Volume (V (m /ha)) Basal area (BA (m /ha)) Number of trees (N) Relatve densty (Curts et al.,98) Relatve stand densty (Drew and Flewellng, 977) Relatve stand densty (Reneke, 9) Tree area rato densty Index Sand % Slt % Clay % Crown closure Organc matter Permeablty Alttude 98.5 Slope (º) * Standart devaton Msr et al. In ths study, the sol loss expressed as ton ha - year - for the study area was determned usng the Unversal Sol Loss Equaton (USLE). A = R K L S C P () Sol samples were collected from plots (9 of whch were located n forested area and n bare land) and analyzed n a laboratory for sol propertes ncludng; slt %, sand %, clay %, organc matter %, and classes for structure and permeablty (Altun, 995). The sol erodblty factor K values of sol samples were calculated usng the followng equaton (Wschmeer and Smth, 978): Journal of Envronmental Bology Aprl, 7

3 Integratng sol eroson to forest management 87. M K =. ( OM ) +.5 ( S - ) +.5 ( P - ) () where OM s sol organc matter content, M s (%slt + %very fne sand)x(-%clay), S s sol structure code and P s permeablty class. If sol organc matter content was greater or equal to %, OM was consdered constant at %. The ranfall erosvty obtaned from average annual ranfall erosvty map (There are no long term meteorologcal data or another study for the country to calculate the R factor. So, erosvty maps of 976 have been used) for Turkey s 7. (Dogan and Gucer, 976). The slope length factor L, accounts for ncreases n runoff volume as downslope runoff lengths ncrease. The slope stepness factor S accounts for ncreased runoff velocty as stepness ncreases. These factors were obtaned from dgtzed topographc maps of study area. For drect applcaton of the USLE a combned slope length and slope stepness (LS) factor was evaluated for each sample plots as (Arnoldus, 977):.5 LS = l ( S +.8 S ) () where l s runoff length (meter), S s slope (percent) Crop and management factor (C) s the sol loss from an area wth specfed cover. Assgnng a proper value to cover management factor (C) n the USLE s a problem, however. Tree categores of woodland are consdered separately: ) undsturbed forest land, ) woodland that s grazed, burned, or selectvely harvested and ) forest lands whch have had ste preparaton treatments for reestablshment after harvest. Factor C for undsturbed forest land may be obtaned from Table (Wschmeer and Smth, 978). In ths study, the values of C factor were consdered as.,.,.6, and.9 for 7-%, -7%, -% and -% crown closure, respectvely. Table - : Factor C for undsturbed forest land Percent of area covered by canopy of trees Factor C The conservaton practce factor P, s determned by the extend of conservaton practces such as strp, croppng, contourng, and terracng practces, whch tend to decrease the erosve capabltes of ranfall and runoff. Values of P range from zero to one. Snce such methods are not used n study area, the value of P was assumed to be. The conservaton practce factor (P); descrbes the reducton n sol eroson from conservaton technques. (P) also can be descrbed as ncorporatng the eroson control management practces. When there sn t any protectve measures P factor can be determned as (Schwab et al., 99). In the study area, no eroson control practce s specfcally adopted so n ths analyss (P) factor equal to. was used. Data analyss: The canddate varables for the sol loss models were numerous and dverse. Hartanto et al. (), classfed such varables n four groups: Sol characterstcs, physographc propertes, clmatc propertes and stand characterstcs. The canddate varables of present study were dvded n to two groups: () measures of physographc structure and () measures of the stand level of structure and densty. Alttude, exposton, aspect, slope and exposure length were used as measures of physographc structure. Mean heght, mean dameter, crown closure and stand densty ndexes were used as measures of the stand level of structure n the present study. Several possbltes exst to descrbe stand densty. Hamlton (986); Ojansuu et al. (99); Vanclay (99) and Tuhus (997), all used BA, and Burgman et al. (99) have used N, to provd examples of models wth stand densty parameters as explcatory varables n modelng. Snce N and BA were drectly determned, and dd not rely on functonal relatonshps, as opposed to volume (V), not only these two varables were selected for testng n the present study, but also the others (Curts et al., 98; Reneke, 9; Drew and Flewelng, 977; Chsman and Schumacher, 9) were tested. The sol loss model should be applcable to dfferent stand structures. Therefore, all varables were tested. Based on the dscusson above, the followng sol loss model was hypotheszed: Aˆ = β + β S + β S + β S () where S s the physographc structure (alttude, exposton, aspect, slope and exposure length), S s the stand structure ( d q, hq and crown closure) and S s the stand densty (Curts et al. (98); Drew and Flewellng (977); Reneke (9) and Chsman and Schumacher (9). Relatonshp between magntude of sol loss obtaned from sample plots and stand characterstcs have been used to model sol protecton value, usng stepwse procedure n Regresson Analyss Method the sgnfcance of parameter estmates was tested by means of t=b/ase, where b s the parameter estmate and ASE s the asymptotc standard error. The parameters of the model for the data were determned usng Stepwse Regresson Analyss n SAS software (SAS Insttute Inc., 999). Only were varables whch were sgnfcant (p<.) ncluded n the equaton. The assumpton of homoscedastcty was tested usng the Durbn Whatson test. A sol loss model was constructed based on some ste and stand characterstcs as a predctor and possble nsgnfcant Journal of Envronmental Bology Aprl, 7

4 88 predctor were excluded. The predcted varable n the sol loss model was annual sol loss amount, whch resulted n a lnear relatonshp between the dependent and ndependent varables. The predctors of a sol loss model were chosen from stand level characterstcs. All of them had to be sgnfcant at the p<.5 level wthout any systematc errors n resduals. Model valdaton: The sol loss model was evaluated quanttatvely by examnng the magntude and dstrbuton of resduals to detect any obvous patterns and systematc dscrepances, and by testng for bas and precson to determne the accuracy at model predctons (Vanclay, 99; Soares et al., 995; Gadow and Hu, 998; Mabvurra and Mna, ). Reltve bas and root mean square error were calculated as follows: n ( A A ) ˆ = Bas = n RMSE = n = ( A Aˆ ) n p where n s the number of observatons, p s the number of parameters n the model, A and  are observed and predcted values, respectvely In addton, the models were further valdated by an ndependent control data set. The valdaton of a model should nvolve ndependent data. The data were parttoned n two ndependent groups, one for model development of sol loss estmaton and the other set for valdaton. The data set used for model development of sol loss estmaton comprsed approxmately 8% of the plots (), whle the remanng % of the plots () were used for valdaton. Although the number of sample plots determned for development of sol loss estmaton was made relatvely large n order to provde suffcent data for model development phase, the number of sample plots n the test data stll should be large enough for valdaton and approprate statstcal test. The devatons between predcted and observed values were tested by Student s Pared t test. Results and Dscusson Parameter estmates of the sol loss model are logcal and sgnfcant at the. level (Table ). The adjusted R value was.6. The number of trees and quadratc mean dameter are the strongest predctors of the sol loss model, explanng 6% of the relatonshps whle quadratc mean dameter and number of trees were able to explan only % and %of the relatonshp, respectvely. The mean sol loss for the total materal was.865 ton/ha/year. All descrptve factors for sol loss were evaluated (5) (6) Msr et al. through a lnear regresson analyses. The results of the regresson analyses are therefore shown n Table. Table - : Estmates of the parameters and varance components of the sol loss model (Eq.) Varable Estmate Standard Beta t-value p-value error Intercept N Adjusted R.6 Multple correlaton analyss showed that d q and N are the true key factors whch explan sol loss estmaton. In a multple regresson analyses between sol loss and the number of trees, mean dameter, tree-area rato, basal area, volume, dfferent stand densty ndexes performed usng a stepwse procedure (Haan, 986), the quadratc mean dameter and the number of trees were the only parameters chosen as statstcally sgnfcant. The best regresson equaton s: A ˆ = d q. N (7) In the analyses, the number of trees and quadratc mean dameter were the varables wth most sgnfcant effect, n spte of the rather small coeffcents of -.96 and.. Other stand densty ndcators dd not show any sgnfcant effect. The assumpton of homoscedastcty was tested usng the Durbn Whatson test. The test ndcated homogenous varances over the full range of predcted values at p<.5 level. Sol loss equaton has the flexblty to assume varous shapes wth dfferent parameter values and produce satsfactory relatonshps under most crcumstances. The relatonshp s bologcally reasonable n such that unrealstc sol loss predctons do not occur beyond the range of the emprcal observatons. The bas of the fxed part of the sol loss model was examned by plottng the resduals as a functon of the predcted values and predctors of the model (Fg. ). The resduals of the fxed model part are correlated wthn each ste and stand hamperng the drect use of Fg. for model evaluaton (part of the resdual varaton s explaned by the random ste and stand factors). However, t s evdent that there s no notceable trend between the resduals of the sol loss model and ndependent varables (Fg. ). On the other hand, the resduals of the sol loss model do not have a heterogeneous varance as a functon of predcted sol loss. Fg. and show predcted and observed sol loss [model data set (a), control data set (b)] plotted over d q and N, respectvely. The predcted mean values of the fgures were Journal of Envronmental Bology Aprl, 7

5 Integratng sol eroson to forest management calculated usng actual values of the explcatory varables for each observaton. In general, the sol loss ftted well over the explcatory varables n the model data set. For the test data set, when all varables were not ncluded n the model, the devatons between predcted and observed sol loss were somewhat larger. Model valdaton: The reftted model ncludng only quadratc mean dameter and number of trees showed small RMSE and approxmately homogenous varances over the full range of Sol Sol Loss Loss (ton/ha/year) 6 5 Predcted 89 Bas (ton/ha/year) Bas (ton/ha/year) a) Bas b) Bas Bas c),5,5,5 -,5,8,6,, -, -, -,6 -,8 - -,8,6,, -, -, -,6 -,8 -,5,5,5,5 Predcted Predcted Sol Sol Loss Loss (ton/ha/year) (ton/ha/year) Dbh (cm) Number of of Trees Fg. : Mean bas of the sol loss model as a functon of predcted sol loss (a), mean dameter (b) and number of trees (c) bold lnes ndcate the standard error predcted varables (Table, Fg. ), ndcatng equal varances and reasonable model specfcaton. The resdual plots also ndcated that sol loss was well predcted across d q and N. The resdual plots aganst the predcted sol loss clearly show that the functon approprately fts the data. The sol loss model was tested usng Student s Pared t test by an ndependent control data set ( sample plots). The a) Sol Sol Loss (ton/ha/year) b) Dameter Daterer Class Classes (cm) (cm) Dameter Daterer Classes (cm) (cm) model presented n ths study was consdered to have an approprate level (p<.5) of relablty (Table 5). Whle very few sol loss models were developed so far (Msr and Msr, ; Karahall, ), none of them were statstcally examned for the applcablty of the model to estmate the sol loss n real scenaro. Table - : Bas and RMSE values of the sol loss models Predcted Fg. : Predcted and observed sol loss (ton/ha/year) over dameter classes for both model data set (a) and control data set (b) Crtera The sol loss model Sol loss model (mm ton/ha/year) ncludng all varables Bas.. ton/ha/year RMSE ton/ha/year Our results ndcated that d q and N were sgnfcant varables n predctng sol loss. The transformatons seemed to behave bad over mean dameter,.e. from a relatvely fast declne of sol loss for the smallest dameters to a more moderate declne for larger dameters (Fg. a). The model gave decreased sol loss wth ncreased dameter and was accepted because of the expected logcal behavor. As expected, the devatons between predcted and Journal of Envronmental Bology Aprl, 7

6 9 observed sol loss over dameter classes were generally larger for the control data compared to the model data. Some of the largest devatons for the control data, however, are probably concdencal because of few observatons n some dameter classes (Fg. b). Therefore, large data set coverng enough number of trees for each dbh class would be needed for better assessments of sol loss. Physographc characterstcs (sol and physographc) shown no sgns of sgnfcant effects n the present data. Stand densty ndex N,.e. number of trees, was hghly sgnfcant (p<.) n predctng sol loss (Table ) as would be expected. The parameter estmate of N was negatve. Ths means that as the sol loss decreases N ncreases. The model behavor Sol Loss (ton/ha/year) a) Sol Sol Loss Loss (ton/ha/year) b),5,5,5,5,5,5,5,5, N Classes Predcted Predcted N N Classes Classes Fg. : Predcted and observed sol loss (ton/ha/year) over the number of trees classes for both model data set (a) and control data set (b) Table - 5: Results of Student s Pared-t test Bas Mean -.86 Pared S.D..69 dfferences S.E.mean.97 %95 Conf. Int. Lover -.8 of the dfference Upper.89 t-value -.97 Df 9 p-value.6 Msr et al. over N (Fg. a) seemed good. A smlar pattern was not detected n the control data, though (Fg. b). N, BA, volume, relatve densty (Curts et al., 98), relatve stand densty (Reneke, 9; Drew and Flewellng, 977) and Tree Area Rato Densty Index (Chsman and Schumacher, 9) were tested as measures for stand densty and the only one of them was found sgnfcant. The parameter estmate was negatve,.e. sol loss amount decreases as the N ncreases. Ths s consstent wth the fact that sol loss changes accordng to the number of trees. In the present data the densty seemed too much correlated wth N, to be ncluded n the models. When the predcted and observed sol loss of the test data set were tested Student s Pared t-test, no evdence of lack of ft was found (Table 5). Mean heght, mean dameter and crown closure were tested as measures for stand structure, but only one of them, mean dameter, was hghly sgnfcant n predctng sol loss because the parameter estmate was sgnfcant and negatve,.e. sol loss amount decreases as d q ncreases. Ths s n correspondence wth the nature and, t was possble to detect n the data. The data used n the present study was n general substantal. The number of observatons was relatvely large (Table ). The dsperson of practcal forest treatments under dfferent condtons was also ncluded. The large sample plot sze was an advantage n the analyss. A plot sze of 8 m means that a relatvely large number of the trees are not affected by the forest condtons outsde the plot. In other words, a relatvely few number of trees are affected by the forest condtons nsde the plot. Plots that were subjected to any harvestng operatons between the measurement perods were excluded from the data materal because of nsuffcent nformaton about the treatments. If the harvest on these plots were a result of regular management practces, there would be no problems related to the excluson. However, f the harvest were a result of an extraordnary stuaton (.e. floods), excluson of the plots would lead to an underestmated sol loss amount. The am of the present work has been to create models applcable for forest management scenaros. Although stands or sample plots are commonly used as the basc calculaton unts n such analyses, the target levels wth respect to accuracy of the predctons are usually dependent on purpose. Detaled studes of forest structures at the stand level are seldom an mportant part of such analyses. The uncertantes related to the sol loss models should be seen n ths perspectve. Sol loss s an mportant varable used n forest management plannng wth the sustanablty of multple values Journal of Envronmental Bology Aprl, 7

7 Integratng sol eroson to forest management n focus. Measurng sol loss s costly, however. Foresters usually welcome an opportunty to estmate the sol loss wth an acceptable accuracy. Mssng sol losses may be estmated usng a sutable sol loss equaton. Based on a comprehensve data set whch ncludes very dfferent stands, such sol loss equaton was ftted for a major tree speces n complex stands of Turkey. The ft statstcs ndcated that the sol loss model s most sutable for predctng sol losses. The parameter estmates wll provde reasonable precson and therefore the model can be recommended for thnned spruce stands n Turkey. Due to the data knd of the used, the suggested sol loss equaton (Eq. 7) should not be used n un-thnned stands and n model predctons whch do not contan any of these treatments. The stand locaton and stand densty measures used n ths study and varables entered nto the sol loss model can easly be obtaned from and are avalable n current forest nventores. Where possble, the use of the sol loss model wth these attrbutes s suggested. In summary, the suggested model mproves the accuracy of sol loss predcton, ensures compatblty among the varous estmates n a forest management scenaro, and mantans projectons wth reasonable bologcal lmts. Lnear models for predcton of sol loss for stand level, desgned for use n large scale forestry scenaro models and analyses have also been developed. The model was developed from a substantal data set representng the entre dsperson of condtons and treatments of the Black Sea Regon Spruce productve and nonproductve forest area. Although sol loss a phenomenon s complcated to model, the model ft and the valdaton tests turned out satsfactory, n spte of several uncertan topcs revealed from the work. Gven the uncertantes of large scale forestry scenaros, the presented sol loss model seems to hold an approprate level of relablty, and we feel that t can be appled n forest management scenaros, ncludng sol loss estmaton and control. The model can be revsed or calbrated when new measurements from the forest permanent sample plots of the research area obtaned n next perod. Acknowledgment We are grateful to Lokman Altun for provdng hs data set used n ths manuscrpt. References Altun, L.: Macka orman sletmes ormanustu sersnde sletme brmlernn ayrlmas ve hartalanmas uzerne arastrmalar, Karadenz techncal unversty, Trabzon, Turkey (995). Arnoldus, H.M.J.: Predctng sol losses due to sheet and rll eroson. FAO conservaton gude no.. Gudelnes for watershed management, Rome, Italy (977). 9 Asan, U.: Isletme snf ayrmnda fonksyonel yaklasm. Orman Muhendslg Dergs, 5, - (99). Burgman, M., W. Incoll, P. Ades, I. Ferguson, T. Fletcher and A. Wholers: Mortalty models for mountan and Alpne Ash. For. Ecol. 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