Estudio bibliométrico del rendimiento forestal. Un análisis de la Web Of Science con Vosviewer
Resumen
Este estudio tiene como objetivo realizar un análisis bibliométrico entre 1971 y 2023 sobre la producción científica sobre el rendimiento forestal en artículos indexados en la Web of Science (WoS) para conocer el estado del arte del tema analizado e identificar las áreas temáticas específicas del sector forestal. Para ello, se ha usado el programa VOSviewer de visualización de redes bibliométricas complementado con la Ley de Lotka para obtener el subconjunto de autores con más producción científica, la Ley de Zipf para estimar el subconjunto de palabras clave de autor y de palabras clave plus que presentan una mayor frecuencia, y el índice h de Hirsch, para conocer cuáles son los artículos de investigación publicados en WoS más citados. Los resultados muestran un creciente interés en los últimos años en la subdisciplina de rendimiento forestal, lo que puede favorecer la competitividad y la productividad de la industria forestal.
Recibido: 29-01-2024 / Aceptado: 06-11-2024
Palabras clave
Texto completo:
PDFReferencias
Acevedo Duque, Á., Vega Muñoz, A., & Salazar Sepúlveda, G. (2020). Analysis of Hospitality, Leisure, and Tourism Studies. Sustainability, 12(7238), 1-20. DOI: https://doi.org/10.3390/su12187238
Araújo Ruiz, J. A., & Arencibia, J. R. (2002). Informetría, bibliometría y cienciometría: aspectos teórico-prácticos. ACIMED, 10(4).
https://scholar.google.hn/scholarhl=es&as_sdt=0%2C5&q=Informetr%C3%ADa%2C+bibliometr%C3%ADa+y+cienciometr%C3%ADa%3A+aspectos+te%C3%B3ricopr%C3%A1cticos.&btnG=
Astana, A., Riva, w. F., Hardiyanto, G., Kamarudin, H., & Sukanda, A. (2020). Towards improved forestry performance: evaluating the added value of the timber legality assurance system in Indonesia. International Forestry Review, 22(1), 1-15.https://www.researchgate.net/publication/339683679
Bahi, J., Elghazel, W., Guyeux, C., Hakem, M., Mediaher, K., & Zerhouni, N. (2019). Reliable diagnostics using wireless sensor networks. Computers in Industry, 104, 103-115. DOI:https://doi.org/10.1016/j.compind.2018.10.006
Baskent, E. Z. (1999). Controlling the spatial structure of forested landscapes: a case study towards landscape management. Landscape Ecology, 83-97. https://link.springer.com/article/10.1023/A:100807130784
Baskent, E. Z., & Jordan, G. A. (1996). Designing forest management to control spatial structure of landscapes. Landscape and Urban Planning, 34(1), 55-74. DOI: https://doi.org/10.1016/0169-2046(95)00200-6
Baskent, E. Z., & Jordan, G. A. (1991). Spatial wood supply simulation modelling. Forest Chron, 67(6). DOI: https://doi.org/10.5558/tfc67610-6
Bini, D., Alcantara dos Santos, C., Calcciolari Pinheiro da Silva, M., Bon Fim, J. A., & Nogueira
Cardoso, E. J. (2018). Intercropping Acacia mangium stimulates AMF colonization and soil phosphatase activity in Eucalyptus grandis. SCI AGR, 75(2), 1-9. DOI: https://doi.org/10.1590/1678-992X-2016-0337
Bronnum, P. (2005). Preplanting indicators of survival and growth of desiccated Abies procera bareroot planting stock. Scandinavian Journal of Forest Research, 20(1), 36-46. DOI: http://dx.doi.org/10.1080/02827580510008257
Buras, A., Rammig, A., & Zong, C. S. (2021). The European Forest Condition Monitor: Using Remotely Sensed Forest Greenness to Identify Hot Spots of Forest Decline. Front. Plant Sc, 12. DOI: https://doi.org/10.3389/fpls.2021.689220
Comisión Europea (2011). Estrategia de la UE sobre la biodiversidad hacia 2020: nuestro seguro de vida y capital natural, Comunicación de la Comisión Europea al Parlamento Europeo, al Consejo, al Comité Económico y Social Europeo y al Comité de las Regiones, COM(2011) 244 final. https://eur-lex.europa.eu/legal-content/ES/TXT/
PDF/?uri=CELEX:52011DC0244&from=ES
Dorman , M., Svaray, T., Perevolotsky, A., & Sarris, D. (2013). Homogenization in forest performance across an environmental gradient – The interplay between rainfall and topographic aspect. Forest Ecology and Management, 310, 256-266. DOI: http://dx.doi.
org/10.1016/j.foreco.2013.08.026
Dorman, M., Svaray, T., Perevolotsky, A., & Sarris, D. (2013). Forest performance during two consecutive drought periods: Diverging long-term trends and short-term responses along a climatic gradient. Forest Ecology and Management, 310, 1-9. DOI: https://doi. org/10.1016/j.foreco.2013.08.009
Duguma, L. A., Minang, P. A., Foundjem-Tita, D., Makui, P., & Mandiefe Piabuo, S. (2018). Prioritizing enablers for effective community forestry in Cameroon. Ecology & Society, 23(3), 1-16. DOI: https://doi.org/10.5751/ES-10242-230301FAO (s.f.). Evaluación de los recursos forestales mundiales 2020. Principales resultados.
DOI: https://doi.org/10.4060/ca8753es
Figueiredo, S. M., Martins Venticinque, E., & Orfanó Figueiredo, E. (2016). Spatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon. Rev.Árvore, 40(4), 1-9. DOI: https://doi.org/10.1590/0100-67622016000400005
Gea Izquierdo, G., Guibal, F., Joffre, R., Ourcival, J. M., Simioni, G., & Guiot, J. (2015). Modelling the climatic drivers determining photosynthesis and carbon allocation in evergreen Mediterranean forests using multiproxy long time series. Biogeosciences, 12,
-3712. DOI: https://doi.org/10.5194/bg-12-3695-2015
Gea Izquierdo, G., Nicault, A., Doreado Liñan, I., Gutiérrez, E., Ribas, M., & Giot, J. (2017). Risky future for Mediterranean forests unless they undergo extreme carbon fertilisation. Glob. Change Biol., 2915-2927. DOI: http://dx.doi.org/10.1111/gcb.13597
Genere, B., & Garriou, D. (1999). Stock quality and field performance of Douglas fir seedlings under varying degrees of water stress. Ann For Sci, 56, 501-510. DOI:http://dx.doi.org/10.1051/forest:19990607
Genere, B., Garriou, D., Omarzad, O., Grivet, J. P., & Hagege, D. (2004). Effect of a strong cold storage induced desiccation on metabolic solutes, stock quality and regrowth, in seedlings of two oak species. Trees, 18, 559-565. DOI: https://doi.org/10.1007/s00468
-0348-5
Grupo Scimago (2006). El índice h de Hirsch: Aportaciones a un debate. El Profesional de la información, 15(4), 304-306. https://scholar.google.hn/scholar?hl=es&as_ sdt=0%2C5&q=El+%C3%ADndice+h+de+Hirsch%3A+Aportaciones+a+un+debate&btnG=
Holzfeind, T., Visser, R., Chung, W., Holzleitner, F., & Erber, G. (2020). Development and Benefits of Winch-Assist Harvesting. Current Forestry Reports, 6, 201-209. DOI: https://doi.org/10.1007/s40725-020-00121-8
Ismail, H., Abd Wahab, A. K., & Alias, N. E. (2012). Determination of mangrove forest performance in reducing tsunami run-up using physical models. Natural Hazards, 63, 939-963. https://link.springer.com/article/10.1007/s11069-012-0200-y
Jetten, V. G. (1996). Interception of tropical rain forest: performance of a canopy water balance model. hydrological processes, 10, 671-685. https://scholar.google.hn/scholar?hl=es&as_
FOREST%3A+PERFORMANCE++OF+A+CANOPY+WATER+BALANCE+MODEL&btnG=
Jim, C. Y., & Chen, S. S. (2013). Assessing Natural and Cultural Determinants of Urban Forest Quality in Nanjing (China). Physical Geography, 455-473. DOI: https://doi. org/10.2747/0272-3646.29.5.455
Lago Barcia, D., Bernardino DaSilva, M., Americo Conti, L., & Carbayo, F. (2020). Areas of endemism of land planarians (Platyhelminthes: Tricladida) in the Southern Atlantic Forest. Plos One, 1-24. DOI: https://doi.org/10.1371/journal.pone.0235949
León González, J. L., Socorro Castro, A. R., Cáceres Mesa, M. L., & Pérez Maya, C. J. (2020). Producción científica en América Latina y el Caribe en el período 1996-2019. Revista Cubana de Medicina Militar, 49(3), 1-10. https://scholar.google.hn/scholar?hl=es&as_sdt
=0%2C5&q=Producci%C3%B3n+cient%C3%ADfica+en+Am%C3%A9rica+Latina+y+el+ Caribe+en+el+per%C3%ADodo+1996-2019&btnG=
López, N., & Muñoz, J. (2017). La producción forestal una actividad
con alto potencial en el Ecuador requiere un cambio. Bosques Latitud Cero, 7(1), 1-8. https://scholar.google.hn/scholar?hl=es&as_
restal+una+actividad+con+alto+potencial+en+el+Ecuador+requiere+un+cambio&btnG= Magalhaes, C. S., Pedreira, B. C., Tonini, H., &
Farias Neto, A. L. (2018). Crop, livestock and forestry performance assessment under different production systems in the north of Mato
Grosso, Brazil. Agroforest Syst. DOI:https://doi.org/10.1007/s10457-018-0311-x
Martinez Sancho, E., Gutierrez, E., Valeriano, C., Ribas, M., Popkova, M. I., Shishov, V. V., & Dorado Liñan, I. (2021). Intra- and Inter-Annual Growth Patterns of a Mixed PineOak Forest under Mediterranean Climate. Forest, 12(12). DOI: https://doi.org/10.3390/
f12121746
Maschmann, M. R. (2015). Integrated simulation of active carbon nanotube forest growth and mechanical compression. Carbon, 86, 26-37. DOI: http://dx.doi.org/10.1016/j.carbon.2015.01.013
McKay, H. M. (1996). A review of the effect of stresses between lifting and. New Forests, 363 393. DOI: https://doi.org/10.1023/A:1006563130976
McKay, H. M., & Morgan, J. L. (2001). The physiological basis for the establishment of bare-root larch seedlings. Forest Ecology and Management, 142, 1-18. DOI: https://doi. org/10.1016/S0378-1127(00)00336-4
McKay, H. M., & White, M. S. (1997). Fine root electrolyte leakage and moisture content: indices of Sitka spruce and Douglas-fir seedling performance after desiccation. New Forest, 139-162. DOI: http://dx.doi.org/10.1023/A:1006571805960
Mellor, A., Boukir, S., Haywood, A., & Jones, S. (2015). Exploring issues of training data imbalance and mislabelling on random forest performance for large area land cover classification using the ensemble margin. ISPRS Journal of Photogrammetry and Remote
Sensing, 105, 155-168. DOI:http://dx.doi.org/10.1016/j.isprsjprs.2015.03.014
Mena Petite, A., Ortega Lasuen, U., González Moro, M., Lacuesta, M., & Muñoz Rueda, A. (2001). Storage duration and temperature effect on the functional integrity of container and bare-root Pinus radiata D. Don stock-types. Trees, 289-296. DOI: http://dx.doi.org/10.1007/
s004680100104
O’Reilly, C., McCarthy, N., Keane, M., Harper, C. P., & Gardiner, J. J. (1999). The physiological status of Douglas fir seedlings and the field performance of freshly lifted and cold stored stock. Annals of Forest Science, 297-306. DOI: http://dx.doi.org/10.1051/forest:19990404
Ormeño Fuenzalida, J., Araya Castillo, L., Hernández Perlines, F., & Moraga Flores, H. (octubrediciembre de 2023). Bioética en la empresa: análisis cienciométrico. Revista Venezolana
de Gerencia, 28(104), 1825-1848. DOI: https://doi.org/10.52080/rvgluz.28.104.18
Peng, Y., & Wang, Y. (2022). Automatic wildfire monitoring system based on deep learning. European Journal Of Remote Sensing, 55(1), 554-567. DOI: https://doi.org/10.1080/2279
2022.2133745
Pérez, R., Santillán, A., Narváez, F.D., & Galeote, B. (2018). Riesgo del arbolado urbano: estudio de caso en el Instituto Tecnológico Superior de Venustiano Carranza, Puebla. Revista Mexicana de Ciencias Forestales, 9(45), 208-228. DOI: https://doi.org/10.29298/
rmcf.v9i45.143
Picos Martin, J. (2015). Industria Forestal y Mercado de la Madera:
Navegando en la Tormenta. Sociedad Española de la Ciencias Forestales, 39, 367-380. https://scholar.google.hn/scholar?hl=es&as_
dustria+Forestal+y+Mercado+de+la+Madera%3A+Navegando+en+la+Tormenta&btnG=
Quirós, R., Chinchilla, O., & Gómez, M. (2005). Rendimiento en Aserrío y procesamiento primario de madera provenientes de plantaciones forestales. Agronomía Costarricense, 29(2), 7-15. https://scholar.google.hn/scholar?hl=es&as_
Rines, D., Kane, B., Kittredge, D. B., Dennis, H., Ryan, P., & Butler, B. (2011). Measuring urban forestry performance and demographic associations in Massachusetts, USA. Urban Forestry & Urban Greening, 10, 113-118. DOI: https://doi.org/10.1016/j.ufug.2010.12.005
Rodriguez de Prado, D., Riofrio, J., Aldea, J., McDermott, J., Bravo, F., & Herrera de Aza, C. (2022). Species Mixing Proportion and Aridity Influence in the Height–Diameter Relationship for Different Species Mixtures. Forest, 13(119), 1-9. DOI: https://doi.org/10.3390/f13010119
Sengupta, a., Hawley, R. J., & Stein, E. D. (2017). Predicting Hydromodification in Streams Using Nonlinear Memory-Based Algorithms in Southern California Streams. Journal of
Water Resources Planning and Management, 144(1). DOI: https://doi.org/10.1061/(ASCE) WR.1943-5452.0000853
Sharpe, A. L., & Mason, W. L. (1992). Some Methods of Cold Storage can Seriously Affect Root Growth Potential Root Moisture Content and Subsequent Forest Performance of Sitka Spruce and Douglas Fir Transplants. Forestry, 463-472. DOI: https://doi.org/10.1093/ forestry/65.4.463
Suominen, L., Ruokolainen, K., Tuomisto, H., Llerena, N., & Higgins, M. A. (2013). I am predicting soil properties from floristic composition in western Amazonian rain forests:
performance of k-nearest neighbour estimation and weighted averaging calibration. J. Appl. Ecol. DOI: http://dx.doi.org/10.1111/1365-2664.12131
Tabbush, P. M. (1987). Effect of Desiccation on Water Status and Forest Performance of Bare-rooted Sitka Spruce and Douglas Fir Transplants. Forestry, 60(1), 31-43. DOI: http://dx.doi.org/10.1093/forestry/60.1.31
Torres Cala, Y., Ramírez Cruz, Z. D., Muñoz González, R., & González Pérez, M. (2017). Introducción y generalización de resultados científicos en el Sector Forestal Cubano. Principales regularidades. Ciencias de la Información, 8(3), 48-54.
Wehner, K., Simons, N. K., Blüthgen, N., & Heethoff, M. (2021). Drought, windthrow and forest operations strongly affect oribatid mite communities in different microhabitats. Global Ecology and Conservation, 1-13. DOI: https://doi.org/10.1016/j.gecco.2021.e01757
Wylie, B. K., Zhang, L., Bliss, N., Ji, L., Tieszen, L. L., & Jolly, W. M. (2008). Integrating modelling and remote sensing to identify ecosystem performance anomalies in the boreal forest, Yukon River Basin, Alaska. International Journal of Digital Earth, 196-220. DOI:
https://doi.org/10.1080/17538940802038366
Wylie, B., Rigge, M., Brisco, B., Murnaghan, K., Rover, J., & Long, J. (2014). Effects of Disturbance and Climate Change on Ecosystem Performance in the Yukon River Basin Boreal Forest. Remote Sensing, 6(10), 9145-9169. DOI: https://doi.org/10.3390/rs6109145
Yin Ooi, S., Chiang Tan, S., & Ping Cheah, W. (2017). Temporal sampling forest (TS-F): An ensemble temporal learner. Soft Computing Article, 21, 7039-7052. DOI: http://dx.doi. org/10.1007/s00500-016-2242-7
Zhu, J., Dai, E., Zheng, D., & Wang, S. (2021). Using a Simple Model to Determine the Best Management Regimes for Plantations at the Stand Level: A Case Study of Moshao Forest Farm in the Red-Soil Hilly Region of Southern China. Forest, 12(1358), 1-21. DOI: https://
doi.org/10.3390/f1210135
Enlaces refback
- No hay ningún enlace refback.
E-ISSN: 2443-4418 P-ISSN: 2443-4256
Todos los documentos publicados en esta revista se distribuyen bajo una
Licencia Creative Commons Atribución -No Comercial- Compartir Igual 4.0 Internacional.
Por lo que el envío, procesamiento y publicación de artículos en la revista es totalmente gratuito.