Abstract
In this research, optimal spatial networks designed for second-phase sampling of soil organic carbon were found based on the spatial information obtained during a first-phase sampling. The study was carried out in soils of tropical crops, forests and pastures in an area of about 1,310 ha located in the foothills situated to the east of the Colombian Andes mountains. Mean soil organic carbon content in the upper 1 m in the study area was 18.9 t ha−1. Additional points supplementing the existing initial sampling set were allocated, in random and regular configurations, following two different approaches: sequential and simultaneous addition. The search for the optimal set of additional points was performed using an evolutionary optimization technique known as genetic algorithms. Results showed that random schemes allocated following the simultaneous addition approach were more efficient than regular schemes. Besides, the sequential addition produced suboptimal solutions, becoming less efficient than the simultaneous addition when the number of additional points to be allocated was increased. The optimization technique used in the study, the genetic algorithms, proved to be effective to find optimal spatial networks designed for second-phase sampling of the variable of interest.
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References
Banjevic M (2004) Optimal network designs in spatial statistics. PhD dissertation, Department of Statistics, Stanford University, Stanford, CA
Borgoni R, Radaelli L, Tritto V, Zappa D (2013) Optimal reduction of a spatial monitoring grid: proposals and applications in process control. Comput Stat Data Anal 58:407–419
CORPOICA (1995) CORPOICA en la Orinoquia Colombiana. Boletín Divulgativo. CORPOICA, Villavicencio
Cressie N (1993) Statistics for spatial data. Wiley, New York
Delmelle E (2005) Optimization of second-phase spatial sampling using auxiliary information. PhD dissertation, Department of Geography, State University of New York, Buffalo, NY
Delmelle E, Goovaerts P (2009) Second-phase sampling designs for non-stationary spatial variables. Geoderma 153(1–2):205–216
Fleming P, Purshouse R (2002) Evolutionary algorithms in control systems engineering: a survey. Control Eng Pract 10:1223–1241
Guo L, Gifford R (2002) Soil carbon stocks and land use change: a meta analysis. Glob Chang Biol 8:345–360
Kirschbaum M (2000) Will changes in soil organic carbon act as a positive or negative feedback on global warming? Biogeochemistry 48:21–51
Lal R (2004) Soil carbon sequestration to mitigate climate change. Geoderma 123:1–22
Lin Y, Yeh M, Deng D, Wang Y (2008) Geostatistical approaches and optimal additional sampling schemes for spatial patterns and future sampling of bird diversity. Glob Ecol Biogeogr 17(2):175–188
Malagón C (1995) Suelos de Colombia: origen, evolución, clasificación, distribución y uso. Instituto Geográfico Agustín Codazzi, Bogotá
Reed P, Kollat J, Devireddy V (2007) Using interactive archives in evolutionary multiobjective optimization: a case study for long-term groundwater monitoring design. Environ Model Softw 22(5):683–692
Santacruz A (2011) Optimización evolutiva de redes espaciales de muestreo: Una aplicación de los algoritmos genéticos y la geoestadística al monitoreo del carbono orgánico del suelo. Editorial Académica Española, Saarbrücken
Solomon D, Fritzsche F, Lehmann J, Tekalign M, Zech W (2002) Soil organic matter dynamics in the subhumid agroecosystems of the Ethiopian highlands: evidence from natural 13C abundance and particle-size fractionation. Soil Sci Soc Am J 66:969–978
Sommer R, Denich M, Vlek P (2000) Carbon storage and root penetration in deep soils under small-farmer land-use systems in the Eastern Amazon region, Brazil. Plant Soil 219:231–241
Townsend A, Vitousek P, Desmarais D, Tharpe A (1997) Soil carbon pool structure and temperature sensitivity inferred using CO2 and 13CO2 incubation fluxes from five Hawaiian soils. Biogeochemistry 38:1–17
van Groenigen J (2000) The influence of variogram parameters on optimal sampling schemes for mapping by kriging. Geoderma 97:223–236
Vanegas J, Landazabal G, Melgarejo LM, Beltran M, Uribe-Vélez D (2013) Structural and functional characterization of the microbial communities associated with the upland and irrigated rice rhizospheres in a neotropical Colombian savannah. Eur J Soil Biol 55:1–8
Acknowledgments
We thank the Faculty of Agronomy of the National University of Colombia, the Agustin Codazzi Geographic Institute, the Core Spatial Data Research Group (Faculty of Engineering, Francisco José de Caldas District University), and CORPOICA’s La Libertad Research Center for the economic, technical and scientific support given to this study.
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Santacruz, A., Rubiano, Y., Melo, C. (2014). Evolutionary Optimization of Spatial Sampling Networks Designed for the Monitoring of Soil Organic Carbon. In: Hartemink, A., McSweeney, K. (eds) Soil Carbon. Progress in Soil Science. Springer, Cham. https://doi.org/10.1007/978-3-319-04084-4_8
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DOI: https://doi.org/10.1007/978-3-319-04084-4_8
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