Herramientas tecnológicas complementarias para la fiscalización de tala ilegal y delitos forestales contra los bosques naturales
Barra lateral del artículo
Contenido principal del artículo
Resumen
El objetivo del presente artículo es mostrar algunas herramientas tecnológicas contemporáneas e innovadoras, que podrían contribuir complementariamente a la fiscalización de la tala ilegal y los delitos forestales; entre tales tecnologías se describen y comentan las potenciales aplicaciones de herramientas genéticas y de química instrumental, complementadas con tecnologías de información y comunicación (TIC)
Referencias
Athanasiadis, I., Anastasiadou, D., Koulinas, K., Kiourtsis, F. (2013). Identifying Smart Solutions for Fighting Illegal Logging and Timber Trade. In Environmental Software Systems. Fostering Information Sharing. Springer Berlin Heidelberg. Pp. 143-153. https://doi.org/10.1007/978-3-642-41151-9_14
Batista, J., Monteiro, T., Rauber, V., Alves, J., Da Silva A. (2011). The use of near infrared spectroscopy to identify solid wood specimens of Swietenia macrophylla (CITES Appendix II). Iawa Journal 32. Pp: 285–296. https://doi.org/10.1163/22941932-90000058
BIDEMA. (2015). Metodología de investigación criminalística de delitos relacionados con especies maderables. Segundo Taller Internacional “Trazabilidad y Control Transfronterizo de Productos de Especies Maderables incluidos en los Apéndices de CITES”. Arica 17 -19-de noviembre de 2015. Chile.
Byrne, S., Czaban, A., Studer, B., Panitz, F., Bendixen, C., Asp, T. (2013). Genome Wide Allele Frequency Fingerprints (GWAFFs) of Populations via Genotyping by Sequencing. PLoS ONE 8(3): e57438. https://doi.org/10.1371/journal.pone.0057438
CONAF. (2011). Denuncias interpuestas por terceros por presuntas infracciones a la legislación forestal vigente, para el periodo enero - diciembre de 2011. [En línea, Consultado 3 de Julio 2015] Disponible en: http://www.conaf.cl/wp-content/files_mf/1360872975denunciasplanes_manejofiscalizacion_mar2012.xls
Cooper, P., Jeremic, D., Radivojevic, S., Ung, Y., Leblon B. (2011). Potential of near-infrared spectroscopy to characterize wood products. Canadian Journal of Forest Research 41. Pp: 2150–2157. https://doi.org/10.1139/x11-088
Crowther, T., Glick, H., Covey, K., Bettigole, C., Maynard, D., Thomas, S., Smith, J., Hintler, G., Duguid, M., Amatulli, G., Tuanmu, N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S., Wiser, S., Huber, M., Hengeveld, G., Nabuurs, G., Tikhonova, E., Borchardt, P., Li, C., Powrie, L., Fisher, M., Hemp, A., Homeier, J., Cho, P., Vibrans, C., Umunay, P., Piao, S., Rowe, C., Ashton, M., Crane, P., Bradford, M. (2015). Mapping tree density at a global scale. Nature 525. Pp: 201-205. https://doi.org/10.1038/nature14967
Deguilloux, M., Pemonge, M., Bertel, L., Kremer, A., Petit, R. (2003). Checking the geographical origin of oak wood: molecular and statistical tools. Molecular Ecology 12. Pp: 1629-1636. https://doi.org/10.1046/j.1365-294X.2003.01836.x
Deguilloux, M., Pemonge, M., Petit, R. (2004). DNA-based control of oak wood geographic origin in the context of the cooperage industry. Annals of Forest Science 61. Pp: 97-104. https://doi.org/10.1051/forest:2003089
Elshire, R., Glaubitz, J., Sun, Q., Poland, J., Kawamoto, K., Buckler, E. and Mitchell, S. (2011). A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species. PLoS ONE 6. Pp: el19379. https://doi.org/10.1371/journal.pone.0019379
Espinoza, E., Lancaster, C., Kreitals, N., Hata, M., Cody, R., Blanchette, R. (2014). Distinguishing wild from cultivated agarwood (Aquilaria spp.) using direct analysis in real time and time of‐flight mass spectrometry. Rapid Communications in Mass Spectrometry, 28. Pp: 281-289. https://doi.org/10.1002/rcm.6779
Espinoza, E., Wiemann, M., Barajas-Morales, J., Chavarria, G., McClure, P. (2015). Forensic Analysis of Cites-Protected Dalbergia Timber from the Americas. IAWA Journal, 36. Pp: 311-325. https://doi.org/10.1163/22941932-20150102
FAO. (2014). Plan de acción mundial para la conservación, utilización sostenible y el desarrollo de los recursos genéticos forestales.
FAO. (2015). Evaluación de los recursos forestales mundiales, compendio de datos. http://www.fao.org/3/a-i4808s.pdf
Finkeldey, R., Leinemann, L., Gailing, O. (2010). Molecular genetic tools to infer the origin of forest plants and wood. Applied Microbiology and Biotechnology 85. Pp: 1251-1258. https://doi.org/10.1007/s00253-009-2328-6
Francisco-Fernández, M., Tarrío-Saavedra, J., Mallik, A., Naya, S. (2012). A comprehensive classification of wood from thermogravimetric curves. Chemometrics and Intelligent Laboratory Systems, 118. Pp: 159-172. https://doi.org/10.1016/j.chemolab.2012.07.003
Francisco-Fernández, M., Tarrío-Saavedra, J., Naya, S., López-Beceiro, J., Artiaga, R. (2015). Classification of wood using differential thermogravimetric analysis. Journal of Thermal Analysis and Calorimetry, 120. Pp: 541-551. https://doi.org/10.1007/s10973-014-4260-y
Gallardo, Enrique. (2013). Manual de Derecho Forestal, Corporación Nacional Forestal.
Glaubitz, J., Moran, G. (2000). Genetic tools: the use of biochemical and molecular markers. En: Young A, Boshier D, Boyle T (Eds.). Forest conservation genetics: principles and practice. CSIRO-CABI. Pp: 39-59. https://doi.org/10.1079/9780851995045.0039
Goncalves, M., Panjer, M., Greenberg, T., Magrath, W. (2012). Justice for forests. Improving criminal justice efforts to combat illegal logging. The World Bank, Washington, DC, 42 p. https://doi.org/10.1596/978-0-8213-8978-2
Hasbún, R., Gonzalez, J., Iturra, B., Fuentes, G., Alarcon, D., Ruiz, E. (2016). Using Genome-Wide SNP Discovery and Genotyping to Reveal the Main Source of Population Differentiation in Nothofagus dombeyi (Mirb.) Oerst. in Chile. International Journal of Genomics. Volume 2016 (2016), Article ID 3654093, 10 p. https://doi.org/10.1155/2016/3654093
Hermanson, J. and Wiedenhoeft, A. (2011). A brief review of machine vision in the context of automated wood identification systems. IAWA Journal, Vol. 32. Pp: 233-250. https://doi.org/10.1163/22941932-90000054
Kobayashi, K., Akada, M., Torigoe, T., Imazu, S., Sugiyama, J. (2015). Automated recognition of wood used in traditional Japanese sculptures by texture analysis of their low-resolution computed tomography data. Journal of Wood Science, 61. Pp: 630-640. https://doi.org/10.1007/s10086-015-1507-6
Khalid, M., Lee, E., Yusof, R., Nadaraj, M. (2008). Design of an intelligent wood species recognition system. International Journal of Simulation System, Science and Technology, 9. Pp: 9-19.
Lancaster, C. and Espinoza, E. (2012a). Analysis of select Dalbergia and trade timber using direct analysis in real time and time‐of‐flight mass spectrometry for CITES enforcement. Rapid Communications in Mass Spectrometry, 26. Pp: 1147-1156. https://doi.org/10.1002/rcm.6215
Lancaster, C. and Espinoza, E. (2012b). Evaluating agarwood products for 2‐(2‐phenylethyl) chromones using direct analysis in real time time‐of‐flight mass spectrometry. Rapid Communications in Mass Spectrometry, 26. Pp: 2649-2656. https://doi.org/10.1002/rcm.6388
Leathwick, L. and Austin, M. (2001). Competitive interactions between tree species in New Zealand old-growth indigenous forests. Ecology 82. Pp: 2560–2573. https://doi.org/10.1890/0012-9658(2001)082[2560:CIBTSI]2.0.CO;2
McClure, P., Chavarria, G., Espinoza, E. (2015). Metabolic chemotypes of CITES protected Dalbergia timbers from Africa, Madagascar, and Asia. Rapid Communications in Mass Spectrometry. Pp: 29783-788. https://doi.org/10.1002/rcm.7163
Martín, M., Mattioni, C., Lusini, I., Molina, J., Cherubini, M., Drake, F., Herrera, M., Villani, F., Martín L. (2013). New insights into the genetic structure of Araucaria araucana forests based on molecular and historic evidences. Tree Genetics & Genomes 10. Pp: 839-851. https://doi.org/10.1007/s11295-014-0725-1
Musah, R., Espinoza, E., Cody, R., Lesiak, A. (2015). A High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures, Scientific reports, 5. https://doi.org/10.1038/srep11520
Narum, S., Buerkle, C., Davey, J., Miller, M., Hohenlohe, P. (2013). Genotyping‐by‐sequencing in ecological and conservation genomics. Molecular Ecology, 22(11): 2841-2847. https://doi.org/10.1111/mec.12350
Nellemann, C. (2012). INTERPOL Environmental Crime Programme. In: Carbon, G. (ed.) Black Trade: Illegal Logging, Tax Fraud and Laundering in the Worlds Tropical Forests. A Rapid Response Assessment. United Nations Environment Programme, GRID-Arendal (2012), www.grida.no
Noss, R. (1990). Indicators for monitoring biodiversity: a hierarchical approach. Conservation Biology 4. Pp: 355-364. https://doi.org/10.1111/j.1523-1739.1990.tb00309.x
Nowakowska, J. (2011). Application of DNA markers against illegal logging as a new tool for the Forest Guard Service. Folia Forestalia Polonica, series A, 2011, Vol. 53 (2): 142–149.
Ochieng, R., Visseren-Hamakers, I., Nketiah, K. (2013). Interaction between the FLEGT-VPA and REDD+ in Ghana: Recommendations for interaction management. Forest Policy and Economics, 32. Pp: 32-39. https://doi.org/10.1016/j.forpol.2012.07.003
ONU. (2015). Objetivos de Desarrollo del Milenio Informe 2015.
Piuri, V. and Scotti, F. (2010). Design of an Automatic Wood Types Classification System by Using Fluorescence Spectra. IEEE transactions on systems, man, and cybernetics–part c: applications and reviews 40. Pp: 358–366. https://doi.org/10.1109/TSMCC.2009.2039479
Prades, C., Gomez-Sanchez, I., Garcia-Olmo, J., Gonzalez, R. (2012). Discriminant analysis of geographical origin of cork planks and stoppers by near infrared spectroscopy. Journal of Wood Chemistry and Technology 32. Pp: 54–70. https://doi.org/10.1080/02773813.2011.599697
Richter, H., Grosser, D., Heinz, I., Gasson, P. (Eds.). (2004). IAWA list of microscopic features for softwood identification. IAWA Bulletin (N.S.) 1. Pp: 1–70. https://doi.org/10.1163/22941932-90000349
Riginos, C. and Grace, J. (2008). Savanna tree density, herbivores, and the herbaceous community: bottom-up vs. top-down effects. Ecology 89. Pp: 2228–2238. https://doi.org/10.1890/07-1250.1
Rojas, J., Alpuente, J., Postigo, D., Rojas, I., Vignote, S. (2011). Wood species identification using stress-wave analysis in the audible range. Applied Acoustics, 72. Pp: 934-942. https://doi.org/10.1016/j.apacoust.2011.05.016
Roberedo, F. (2013). Socio-economic, environmental, and governance impacts of ilegal logging. Environment Systems and Decisions, 33. Pp: 295-304. https://doi.org/10.1007/s10669-013-9444-7
Russ, A. and Fiserova, M. (2011). Estimation of hardwood species in mixture by near infrared spectroscopy. Wood Res 56. Pp: 93–103.
Sandak, A., Sandak, J., Negri, M. (2011). Relationship between near-infrared (NIR) spectra and the geographical provenance of timber. Wood Science and Technology 45. Pp: 35-48. https://doi.org/10.1007/s00226-010-0313-y
Tarrío-Saavedra, J., Naya, S., Francisco-Fernández, M., López-Beceiro, J., Artiaga, R. (2010). Functional nonparametric classification of wood species from thermal data. Journal of thermal analysis and calorimetry, 104. Pp: 87-100. https://doi.org/10.1007/s10973-010-1157-2
Tarrío‐Saavedra, J., Francisco‐Fernández, M., Naya, S., López‐Beceiro, J., Gracia‐Fernández, C., Artiaga, R. (2013). Wood identification using pressure DSC data. Journal of Chemometrics, 27. Pp: 475-487. https://doi.org/10.1002/cem.2561
Tsuchikawa, S. and Kobori, H. (2015). A review of recent application of near infrared spectroscopy to wood science and technology. Journal of Wood Science 61. Pp: 213-220. https://doi.org/10.1007/s10086-015-1467-x
Valbuena, P., Gomez, R., Herrero, J., Segur, M. (2013). Trazabilidad: reto y oportunidad para los territorios en el mercado de productos forestales. 6 Congreso Forestal Español 10-14 Junio 2013.
Yang, Z., Jiang, Z., Lu, B. (2012a). Investigation of near infrared spectroscopy of rosewood. Spectrosc Spectr Anal 32. Pp: 2405–2408.
Yang, Z., Lu, B., Huang, A., Liu, Y., Xie, X. (2012b). Rapid identification of softwood and hardwood by near infrared spectroscopy of cross-sectional surfaces. Spectrosc Spectr Anal 32. Pp: 1785–1789.
Wang H-j., Zhang G-q., Qi H-n. (2013). Wood Recognition Using Image Texture Features. PLoS ONE 8(10): e76101. https://doi.org/10.1371/journal.pone.0076101
Wheeler, E., Baas, P., Gasson, P. (1989). IAWA list of microscopic features for hardwood identification. IAWA Bull. New Ser. 10. Pp: 219–332. https://doi.org/10.1163/22941932-90000496
Descargas
Los trabajos publicados en Ciencia & Investigación Forestal se rigen por la licencia Creative Commons Atribución 4.0 Internacional (CC BY 4.0).
En lo esencial esta licencia involucra que los autores conservan sus derechos de autor, y que los lectores puedan de forma gratuita descargar, almacenar, copiar y distribuir la versión final aprobada y publicada del trabajo, siempre y cuando se realice sin fines comerciales y se cite la fuente y autoría de la obra.