Archer, Steven R.

Bai, E.

Boutton, Thomas W.

Liu, Feng

Wu, Xinyuan Ben

English

University of Kentucky

University of Kentucky UKnowledge International Grassland Congress Proceedings 21st International Grassland Congress / 8th International Rangeland Congress Spatial Pattern and Uncertainty of Soil Organic Carbon and Implications for Sampling Design Feng Liu Texas A&M University Xinyuan Ben Wu Texas A&M University E. Bai Texas A&M University Thomas W. Boutton Texas A&M University Steven R. Archer University of Arizona Follow this and additional works at: https://uknowledge.uky.edu/igc  Part of the Plant Sciences Commons, and the Soil Science Commons This document is available at https://uknowledge.uky.edu/igc/21/8-1/48 The 21st International Grassland Congress / 8th International Rangeland Congress took place in Hohhot, China from June 29 through July 5, 2008. Proceedings edited by Organizing Committee of 2008 IGC/IRC Conference Published by Guangdong People's Publishing House This Event is brought to you for free and open access by the Plant and Soil Sciences at UKnowledge. It has been accepted for inclusion in International Grassland Congress Proceedings by an authorized administrator of UKnowledge. For more information, please contact UKnowledge@lsv.uky.edu. 瞯 ]916　 瞯 　 Multifunctional Grasslands in a Changing World 　 Volume Ⅰ 　Grasslands/Rangelands Resources and Ecology ——— Climate Change and Impact on Grasslands/RangelandsSpatial pattern and uncertainty of soil organic carbon and implications for sampling designFeng L iu1 , X inyuan Ben Wu1 , E Bai1 , Thomas W . Boutton1 , Steven R . A rcher21 Department o f Ecosystem Science and Management , Texas A &M University , College S tation , TX 77843 , USA , E‐mail :xbw＠ tamu .edu , 2 School o f Natural Resources , University o f A rizona , Tucson , A Z 85721 , USAKey words : sampling design , soil carbon storage , spatial heterogeneity and uncertainty , woody invasionIntroduction Woody encroachment has occurred in many arid and semi‐arid ecosystems all over the world ( Archer １９９５ ) .Invasion of woody plants into grassland savanna has significant impacts on soil carbon storage and its spatial heterogeneity( Boutton et al . １９９８) . We have limited understanding on the pattern of special heterogeneity and uncertainty of soil carbon andits relationship to the spatial pattern of woody vegetation in savanna landscapes . This understanding is essential for effectiveassessment and monitoring of soil carbon in savanna landscapes . The goal of this study was to develop an understanding of thespatial pattern and uncertainty of soil organic carbon ( SOC ) and how they influence the effectiveness of SOC estimation insubtropical savanna landscapes . The specific objectives were to : (１) quantify the spatial uncertainty of SOC ; (２ ) evaluate theperformance of different point sampling designs in estimating SOC storage ; and (３) develop effective sampling strategies basedon the spatial pattern and uncertainty of SOC .Materials and methods This study was conducted at the Texas AgriLife Research La Copita Research Area (２７°４０′N , ９８°１２′W)in south Texas . The upland portions of the landscape are subtropical savanna parklands with discrete woody patches scatteredin a continuous C４ grassland matrix . Woody patches with honey mesquite canopy and understory shrubs were classified assmaller clusters (１‐１００ m２ ) and larger groves ( ＞ １００ m２ ) . A １６０m × １００m plot was established on the upland landscape with１０m × １０m grid cells . Soil samples were collected at ２ random points in each grid cell . Additional subplots on ３ groves , ５clusters and ３ grassland areas were also sampled with higher intensities . Soil samples were processed and SOC concentrationwas measured by combustion/ gas chromatography using a Carlo Erba EA‐１１０８ elemental analyzer . Aerial photo imagery wasclassified into either woody or non‐woody classes and the woody patches were identified as clusters or groves based on theirsizes . Kriging and conditional stochastic simulation approaches ( Goovaerts ２００１ ) were used to qualify the pattern of spatialuncertainty in SOC estimations . Based on the understanding of the pattern of spatial uncertainty , alternative sampling designswere developed and examined for their effectiveness measured as the estimation error as a function of sample density .Results Average SOC content was significantly different between vegetation types and decreased from groves to clusters andgrasslands ( １８３２ , １５００ , and １２８２ g C m‐２ ) . Spatial distribution of SOC based on kriging indicated that it was closely related tothe spatial distribution of woody vegetation density . Results of the conditional stochastic simulation showed significantly greaterlevels of uncertainty of SOC estimations in groves than in clusters and grassland . Consistent differences in estimation error werefound among the complete random sampling , stratified random sampling with even density , and stratified random samplingwith uneven density ( based on level of uncertainty ) . Stratified random sampling with unequal densities had the lowestestimation error while complete random sampling had the highest at all sampling density . Estimation errors of all three designsstarted to level off when sampling density was higher than １００ samples per hectare . Results of the complete random samplingexperiments with simulated landscapes showed that estimation errors increased with increasing woody vegetation cover for allsampling densities and both percentage of woody cover and relative abundance of clusters vs . groves influence the estimationerrors . Results of experiments also showed that structured sampling would be most effective for clusters given the strongpatterning from center to edge of the clusters .Conclusions The invasion of woody vegetation into grassland , deserts and savannas has profound impacts on both the magnitudeand spatial heterogeneity of SOC content . In order to evaluate effects of woody invasion on soil carbon at large spatial scales ,understanding of spatial uncertainty of SOC is essential in designing suitable sampling regimes to estimate SOC storage . Ourresults showed that SOC had higher spatial uncertainty as well as higher concentrations in woody patches than in the grassland .High uncertainty of SOC in woody patches was likely caused by complex canopy structure , root distribution and animaldisturbance . Assessment of alternative sampling designs demonstrated the effect of spatial uncertainty on estimation accuracy ofSOC storage and helped generating effective sampling strategies to improve SOC estimation accuracy . This understanding ofspatial uncertainty of SOC can also enable new approaches to estimate and monitor soil carbon storage over large landscapesbased on remote sensing .ReferencesArcher , S . １９９５ . T ree‐grass dynamics in a Prosop is‐thornscrub savanna parkland — reconstructing the past and predicting thefuture . Ecoscience ２ :８３‐９９ .Boutton , T . W . , S . R . Archer , A . J . Midwood , S . F . Zitzer , and R . Bol . １９９８ . delta C‐１３ values of soil organic carbonand their use in documenting vegetation change in a subtropical savanna ecosystem . Geoderma ８２ :５‐４１ .Goovaerts , P . ２００１ . Geostatistical modelling of uncertainty in soil science . Geoderma １０３ :３‐２６ .

Spatial Pattern and Uncertainty of Soil Organic Carbon and Implications for Sampling Design

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Spatial Pattern and Uncertainty of Soil Organic Carbon and Implications for Sampling Design

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