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Resumen
With the aim of studying the primary productivity dynamics of subtropical forests with different degrees of intervention or change due to human intervention, we classify the ecosystems of an area in northeastern Argentina, corresponding to a humid subtropical region, according to their temporal variability. A 22-year time series, ranging from 2000 to 2022, of MODIS EVI was assembled into a spatiotemporal cube, and pixels were classified by an archetypal [ver mas...]
dc.contributor.authorDíaz Villa, M. Virginia E.
dc.contributor.authorCristiano, Piedad M.
dc.contributor.authorEasdale, Marcos Horacio
dc.contributor.authorBruzzone, Octavio Augusto
dc.coverage.spatialArgentina .......... (nation) (World, South America)es_AR
dc.coverage.spatial7006477es_AR
dc.date.accessioned2023-07-06T16:03:49Z
dc.date.available2023-07-06T16:03:49Z
dc.date.issued2023-04
dc.identifier.issn2352-9385
dc.identifier.otherhttps://doi.org/10.1016/j.rsase.2023.100966
dc.identifier.urihttp://hdl.handle.net/20.500.12123/14708
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S2352938523000484
dc.description.abstractWith the aim of studying the primary productivity dynamics of subtropical forests with different degrees of intervention or change due to human intervention, we classify the ecosystems of an area in northeastern Argentina, corresponding to a humid subtropical region, according to their temporal variability. A 22-year time series, ranging from 2000 to 2022, of MODIS EVI was assembled into a spatiotemporal cube, and pixels were classified by an archetypal analysis applied to the frequency components of a Fourier power spectrum. Then the most representative pixels of this classification (archetypoids) were selected. A wavelet decomposition was performed on these archetypoids to identify temporal changes in the frequency composition of the time series, and an ARIMA model to identify changes in the noise pattern of the series. Finally, a distributed-lag model with meteorological variables, was applied to these time series to relate the dynamics of the archetypes to the local climate. A stepwise procedure using Gaussian processes for error and autocorrelation and multiple regressions to determine any univariate relationship between meteorological variables and EVI. The meteorological variables considered were temperature, rainfall, and potential evapotranspiration (PET). The procedure started with a null model with white noise, then Gaussian processes were gradually added to model the errors, and then the explanatory variables, which were filtered moving average time series of the meteorological variables. The interaction between the explanatory variables was assumed to be the minimum EVI of the predicted values of each variable according to Lieibig's law of minimum. The procedure was applied as the BIC decreased to find the optimal model. In this study area, three different archetypes were sufficient to describe most of the variability in the time series matrix. Archetype 1 was characterized by woody plantations of exotic species such as pines, yerba mate and tea, archetype 2 by native forests, and archetype 3 represented a mosaic of forests and agriculture/pasture. The analysis of climate and archetypes indicated that archetype 2 had the highest mean EVI values (i.e., primary productivity), followed by archetype 1 and lastly archetype 3. Also, it showed that all three archetypes responded to the same combination of climate variables (temperature and PET), with varying degrees of sensitivity to each variable. Archetype 2 was the least sensitive to changes in these variables, archetype 1 was more sensitive to PET, and archetype 3 was more sensitive to temperature, while also exhibiting the least response time.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherElsevieres_AR
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/es_AR
dc.sourceRemote Sensing Applications: Society and Environment 30 : 100966. (April 2023)es_AR
dc.subjectVegetaciónes_AR
dc.subjectVegetationeng
dc.subjectClasificaciónes_AR
dc.subjectClassificationeng
dc.subjectEcosistemaes_AR
dc.subjectEcosystemseng
dc.subjectBosqueses_AR
dc.subjectForestseng
dc.subjectZona Subtropicales_AR
dc.subjectSubtropical Zoneseng
dc.subjectArgentinaes_AR
dc.titleArchetypal classification of vegetation dynamics of a humid subtropical forest region from North-East Argentinaes_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)es_AR
dc.description.origenEEA Barilochees_AR
dc.description.filFil: Díaz Villa, M. Virginia E. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ecología, Genética y Evolución; Argentinaes_AR
dc.description.filFil: Díaz Villa, M. Virginia E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Laboratorio de Ecología Funcional. Instituto de Ecología, Genética y Evolución; Argentinaes_AR
dc.description.filFil: Díaz Villa, M. Virginia E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ecología, Genética y Evolución; Argentinaes_AR
dc.description.filFil: Cristiano, Piedad M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ecología, Genética y Evolución; Argentinaes_AR
dc.description.filFil: Cristiano, Piedad M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Laboratorio de Ecología Funcional. Instituto de Ecología, Genética y Evolución; Argentinaes_AR
dc.description.filFil: Cristiano, Piedad M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ecología, Genética y Evolución; Argentinaes_AR
dc.description.filFil: Easdale, Marcos Horacio. Instituto Nacional de Tecnologia Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentinaes_AR
dc.description.filFil: Easdale, Marcos Horacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentinaes_AR
dc.description.filFil: Bruzzone Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentinaes_AR
dc.description.filFil: Bruzzone Octavio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentinaes_AR
dc.subtypecientifico


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