Study area

The study was developed in the southern zone of the state of Oaxaca (Figure 1); whose original vegetation cover in the Costa region (CR) corresponds to forest and in the Sierra region (SR) to temperate forest. Both types of cover currently include small areas for agriculture, livestock, deforested areas and forest plantations established on abandoned or degraded agricultural lands.

Simbología = Symbology; Plantaciones forestales -= Forest plantlations; Regiones = Regions.

Figure 1 Location points of the plantations where the study was carried out. 

The climate of CR is warm sub-humid and semi-warm sub-humid, with a maximum temperature of 32 to 36 °C, an average of 24 to 28 °C; the average annual precipitation varies from 800 to 1 500 mm (^{Fernández et al., 2012}); and its soil units include regosoles, umbrisols, leptosols, luvisols and Phaeozem (^{Inegi, 2017}). In the SR, the climate is temperate subhumid and semi-cold sub-humid, with an average temperature of 12 to 18 ° C, and a precipitation of 1 000 to 1 500 mm (^{Fernández et al., 2012}); its main soil types are Cambisol, Leptosol, Luvisol and Umbrisol (^{Inegi, 2017}).

Methodology

In order to assess the commercial plantations, a selection was made among those established in 2000 to 2014 financed by Conafor. The vectorial data of its location and extension were provided by the management of Conafor in Oaxaca; farms with an area greater than or equal to 5 ha were considered, to facilitate the analysis using satellite images. In the RC the plantations correspond to broadleaved species: Cedrela odorata L., Swietenia humilis Zucc., Tabebuia rosea (Bertol.) Bertero ex A. DC. and Swietenia macrophylla King. In the RS, they are conifers: Pinus pseudostrobus Lindl., P. greggii Engelm., P. patula Schltdl. et Cham, P. ayacahuite Ehrenb. ex Schltdl., P. douglasiana Martínez, P. maximinoi H.E. Moore and P. leiophylla Schltdl. et Cham.

The plantations of the tropical region were developed under the following conditions: average evapotranspiration of 861 mm, average annual precipitation of 1 002 mm and at an altitude of 445 m above sea level; in the temperate region under the scenario described below: evapotranspiration of 636 mm, average precipitation of 1 340 mm and an altitude of 2 384 m.

Georeferenced environmental data were collected from the area of interest, corresponding to the average annual rainfall, average annual temperature, soil depth, soil pH, soil texture, altitude and slope of the land, on the websites of the Conabio, Inegi and of the Inventario Nacional Forestal y de Suelos (National Forestry and Soils Inventory) (^{Inegi, 2016}; ^{Inegi, 2017}; ^{Conabio, 2017}; ^{Conafor, 2017}). Their projection systems were homogenized to UTM, in order to perform the analysis of the environmental conditions of the area where the plantations are located.

Scenes of satellite images of the year 2014, 2015 and 2016 were acquired, all from the same period (November-December). Th0se of 2014 and 2015 were from Landsat 8 OLI (Operational Land Imager) and the 2016 from Sentinel-2. All the images were obtained for free in the following links: http://earthexplorer.usgs.gov/(Landsat 8) and https://scihub.copernicus.eu/dhus/#/home (Sentinel-2).

Two types of corrections were carried out: the geometric one to adjust the location of the scenes of images among themselves, and the atmospheric one to correct anomalies of the images; in addition to converting the digital numbers of each of them to radiance values and then to reflectance by using the QGIS software.

In the analysis of the vegetation biomass, with the indirect technique based on the NDVI, a total of 78 forest plantations were included, 28 in the tropical zone and 50 in the temperate zone. Coniferous and hardwoods were analyzed separately, because both groups of species have different spectral responses.

The NDVI was used to monitor the establishment of the plantations for 2014, 2015 and 2016. This index described the dynamics of soil-vegetation mix, as well as the quantity, quality, development and vigor of the plantations (^{Torres et al., 2014}; ^{Escribano et al., 2015}; ^{Muñoz et al., 2016}). The NDVI was calculated using the spectral values corresponding to the region of red visible light (R) (0.6-0.7 μm) and near infrared light (IRC) (0.7-1.3 μm):

Prior to the evaluation of the NDVI time series, the extraction of the area corresponding to the plantations was carried out, for which the limits of each area were used. The product was a portion per image, for which the statisticians were estimated considering the values of the pixels (mean, standard deviation, minimum and maximum value). After obtaining a significant deviation (p <0.05) of the data towards a non-normal distribution, a comparison of means with the Friedman test was applied to determine if there are significant changes in the three planting dates.

In the classification of the NDVI values, those between 0 and 0.4 were assigned for low or sparse vegetation; from 0.5, 0.6 to 0.8, for developing vegetation; and from 0.8 to 1, for healthy, vigorous and dense vegetation (^{Merg et al., 2011}; ^{Meneses, 2012}; ^{López et al., 2015}) (Table 1).

Finally, a multivariate analysis of canonical correspondence (CCA) was done with the R Studio program 1.1.4 version (^{RStudio Team, 2016}) to determine the environmental variables (annual average precipitation, annual average temperature, altitude, slope, pH and soil depth) that affect the dynamics of plantations. The CCA consisted of determining the degree of association of all environmental variables with respect to the NDVI of 2014, 2015 and 2016.

Plantations dynamics from NDVI

All the plantations of the tropical zone in their three assessments corresponded to a medium to high and vigorous vegetation, according to the classification of the NDVI by ^{Merg et al. (2011)}, ^{López et al. (2015)} and ^{Meneses (2012)}. The NDVI trend was similar in the three annual periods analyzed; however, their values were lower for 2016, due to a better resolution of the images used (Figure 2). The results of the Friedman test indicate that there are important differences in the three time series of NDVI for the tropical zone (ANOVA Chi square = 33.429 p <0.000), which show an increase with the passage of years.

Figure 2 NDVI values for the biomass of the plantations in the tropical zone 2014 - 2016. 

In the temperate zone it was determined that all areas correspond to tall and developing vegetation. The biomass figures represented by the NDVI showed an increasing trend between 2014 and 2015 (Figure 3); this is consistent with that described by ^{Vicente et al. (2004)} for forests and well-developed vegetation. The values recorded for the plantations established in recent years were the only ones low for the amount of biomass, which is probably due to the short time elapsed between establishment and evaluation (Figure 3). When using the Friedman test, it was found that there are significant differences between plantations (ANOVA Chi square = 50.520 p <0.000).

Figure 3 NDVI values for the biomass of the plantations in the temperate zone 2014 - 2016. 

Environmental factors associated with the NDVI

Based on the multivariate analysis of canonical correspondence (CCA), with time series of biomass and environmental variables, it was determined that for the tropical region, evapotranspiration, precipitation and altitude are factors that influence the biomass dynamics of the plantations (Figure 4). While, in the temperate region: altitude, pH, temperature, evapotranspiration and precipitation were the determining variables (Figure 5). Therefore, it is important to consider the environmental variables and the characteristics of the site (biotic and abiotic factors), to have a greater productivity of future plantings and fewer failures.

Figure 4 CCA: NDVI series of tropical species vs environmental variables. 

Figure 5 CCA: conifer NDVI series vs environmental variables. 

The interaction of climatic, soil and topographic variables determine the place where forest species can grow, how quickly, and how well they do it; however, internal factors such as the quality of the plants should be considered when they are established in the field (^{Schlatter and Gerding, 2014}). It is necessary to make a good selection of the sites before establishing the forest species, in order to obtain good timber productivity (^{Jofré et al., 2013}).