Spatial distribution of two oak species and ecological attributes of pine-oak woodlands from Ixtlán de Juárez, Oaxaca

 

Distribución espacial de dos especies de encinos y atributos ecológicos del bosque de pino-encino en Ixtlán de Juárez, Oaxaca

 

Faustino Ruiz-Aquino*^1,2; Juan I. Valdez-Hernández²; Angélica Romero-Manzanares²; Filemón Manzano-Méndez¹; Martha E. Fuentes-López³

  

¹ Universidad de la Sierra Juárez, Instituto de Estudios Ambientales. Av. Universidad s/n. C. P. 68725. Ixtlán de Juárez, Oaxaca, MÉXICO. Correo-e: ruiz.faustino@colpos.mx, tel.: +52 (01) 9515536362 (*Autor para correspondencia).

² Colegio de Postgraduados. km 36.5 Carretera México-Texcoco. C. P. 56239. Montecillo, Texcoco, Estado de México.

³ Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias (INIFAP), Campo Experimental San Martinito. km. 56.6 Carretera Federal México-Puebla, col. San Martinito Tlahuapan. C. P. 74100. Puebla, Puebla, MÉXICO.

 

Received: May 29, 2014.
Accepted: February 10, 2015.

 

ABSTRACT

The structure and diversity of pine-oak woodlands in Ixtlán de Juárez, Oaxaca, was analyzed using three sampling units (SU) of 50 x 50 m. The spatial distribution of trees with normal diameter ≥ 2.5 cm was determined. Dasometric variables were recorded; two indices of structural importance (the Relative Importance Value Index [RIVI] and the forest value index [FVI], and three diversity indices (Shannon-Wiener Entropy Index, effective number of diversity, and Sorensen index) were calculated. A total of 799 trees were recorded, belonging to 11 families and 19 species; the most abundant family was Fagaceae (628 individuals, four species). In SU1, the most important species was Quercus crassifolia (RIVI = 53; FVI = 57). The highest values of RIVI and FVI in SU2 were for Q. laurina (RIVI = 48, FVI = 63). In SU3, the most important species was Q. crassifolia (RIVI = 49, FVI = 62). The analysis of both species revealed random distribution in practically all distances. The aggregate pattern of tree species was attributed to regeneration strategies and silvicultural practices. Both species can coexist modifying the structural importance and horizontal distribution pattern.ment of arsenic-contaminated water and soils in the region using native bacterial strains.

Keywords: Quercus laurina, Quercus crassifolia, species diversity, relative importance value index.

 

RESUMEN

La estructura y diversidad de un bosque de pino-encino se analizaron en tres unidades de muestreo (UM) de 50 x 50 m, en Ixtlán de Juárez, Oaxaca. Se determinó la distribución espacial de los individuos con diámetro normal ≥ 2.5 cm. Las variables dasométricas se registraron; se calcularon dos índices de importancia estructural (índice de valor de importancia relativa [IVIR] y de valor forestal [IVF]) y tres índices de diversidad (índice de entropía de Shannon-Weiner, número efectivo de diversidad e índice de Sorensen). Se registraron 799 individuos de 11 familias y 19 especies; la familia más abundante fue Fagaceae (628 individuos, cuatro especies). La especie más importante en la UM1 fue Quercus crassifolia (IVIR = 53, IVF = 57). Los valores más altos del IVIR e IVF en la UM2 correspondieron a Q. laurina (IVIR = 48, IVF = 63). En la UM3, la especie más importante fue Q. crassifolia (IVIR = 49, IVF = 62). El análisis de las dos especies en conjunto reveló distribución aleatoria en prácticamente todas las distancias. El patrón agregado de las especies individuales se atribuyó a estrategias de regeneración y prácticas silvícolas. Ambas especies pueden coexistir modificando la importancia estructural y el patrón de distribución horizontal.

Palabras clave: Quercus laurina, Quercus crassifolia, diversidad de especies, índice de valor de importancia relativa.

 

INTRODUCTION

The pine-oak woodlands from Ixtlán de Juárez, Oaxaca, have been harvested for wood during the past six decades (Castellanos-Bolaños et al., 2008). The forest has been managed in order to promote harvesting of Pinus as main genus, and Quercus as a secondary genus (Álvarez & Rubio, 2013). At beginning of harvesting techniques, in the 1940s, selective cutting were applied, and from 1993, the method of parent trees for forest management was introduced (Técnica Informática Aplicada, S. A. [TIASA], 1993). The latter harvesting system has caused changes in the structure and composition of forest species, in favor of growing populations of Quercus spp. (Servicios Técnicos Forestales [STF], 2008).

The structure of a forest is defined as the spatial pattern of distribution of plants resulting from the action of biotic and abiotic forces (Hutchings, 1997). Forest characterization is ordered vertical and horizontally (Cortés, 2003). The vertical order is characterized by differentiation of height categories, while the horizontal structure is explained by the analysis of spatial distribution indices (Zarco-Espinosa, Valdez-Hernández, Ángeles-Pérez, & Castillo-Acosta, 2010). In both cases, analyzes are useful to know about the factors to which trees of a community have been exposed, whether chemical, physical (climate, soil, topography, geology) or biotic factors (dispersers, predators, competitors).

The present study was carried out in a pine-oak woodland from Ixtlán de Juárez, Oaxaca, with the aims of describing the vertical and horizontal structure of tree vegetation, as well as calculate the richness and diversity of species. Due to the economic importance of Quercus wood for firewood and charcoal production, and as part of a broader study for technological characterization, the spatial distribution patterns of Q. laurina Humb. Bonpl. and Q. crassifolia Humb. & Bonpl were analyzed.

 

MATERIALS AND METHODS

Study area

Ixtlán de Juárez, Oaxaca, is located at 17° 18' 16" - 17 34' 00" N and 96° 31' 38" - 96° 20' 00" W (Castellanos-Bolaños et al., 2008). The municipality has a mean annual temperature of 20 °C and annual rainfall of 800 to 1,200 mm (Aquino-Vásquez, Ruiz-Aquino, & Fuente-Carrasco, 2012). The area of forest harvesting is at an altitude of 2,156 to 2,458 m. The climate is C(m)(w'')b(i')g, temperate humid with summer rains (García, 1987). The pine-oak forest develops on humic acrisol (Ah) of silty medium texture with a rich layer of organic matter on the surface (Rainforest Alliance, 2006). Pinus patula Schltdl. & Cham., P. oaxacana Mirov., P. pseudostrobus Lindl., Q. crassifolia, Q. rugosa Masam., Anus acuminata Kunth and Arbutus xalapensis Kunth highlights among the dominant species (Ruiz-Aquino et al., 2014).

Sampling and measurement of variables

Three sampling units (SU) of 50 x 50 m (2,500 m²) were established considering the slope of the land to balance the horizontal distance due to the slope. Each SU was divided into 25 frames of 10 x 10 m as proposed by Zarco et al. (2010). Each tree with a diameter at breast height (DBH) ≥ 2.5 cm was identified taxonomically ; the normal diameter (ND, cm) was recorded, which was measured with a diameter tape, total height (TH, m) registered with Haga altimeter (W-Germany) and crown diameter (m) using measuring tape in the directions N-S and E-W. The location of Q. crassifolia and Q. laurina trees was recorded by their coordinates (x, y) on a Cartesian plane, taking the bottom left of the plane with respect to the slope of each SU, as the origin (0, 0). Stratification of height of the tree component was determined with TH data, and the diameter distribution with ND.

Indexes of structural importance

Species dominance in the horizontal plane was determined by the Relative Importance Value Index (RIVI), which is calculated based on the sum of the relative density according to the number of trees per unit area, the relative dominance through the basal area and the relative frequency by the presence of the species in the SU (Curtis & McIntosh, 1951). The bidimensional structure of vegetation was assessed by the forest value index (FVI) which in its calculation considers the sum of the relative diameter, relative height and relative cover (Corella-Justavino et al., 2001).

Diversity Indexes

The diversity in each SU was determined by the entropy index of Shannon-Wiener H' = Σpi · In(pi), where pi is the proportional abundance of the species i, which involves the proportion or relative abundance of each species in the population (Krebs, 1989; Moreno, 2001). To determine if there is significant difference in species diversity among SU, the method of Hutcheson was used (Hutcheson, 1970), which is based on the entropy index of Shannon-Weiner (Villavicencio-Enríquez & Valdez-Hernández, 2003). Additionally, the data was analyzed using true diversity measures, by converting the entropy index of Shannon H'= exp[Σpi · In(pi)] (Jost, 2006), also called effective number of diversity, which measures the diversity that an community consisting of commonly equal i species (Moreno, Barragán, Pineda, & Pavón, 2011). This analysis included all species weighing exactly proportional to their abundance in the community using logarithms base e. The similarity among SU was calculated with the Sorensen index (IS_S), using presence and absence data of the species (Badii, Landeros, & Cerna, 2008; Vázquez-Negrín, Castillo-Acosta, Valdez-Hernández, Zavala-Cruz, & Martínez-Sánchez, 2011):

Where:

C = Number of common species in both communities

A = Total number of species present in community A

B = Total number of species present in community B

Spatial distribution

The spatial distribution of Q. crassifolia and Q. laurina trees was analyzed with the coordinates (x, y) of the trees for each species, using the function K(t) of Ripley (Ripley, 1977), defined as:

Where:

n = Number of trees in sampling unit A (SU-A)

|A| = Area of SU-A (m²)

u_ij = Distance between the i-th and j-th tree in SU-A (m)

t = Distance between two trees (m)

I_t(u) = 1 if u ≤ t and 0 if u > t

W_ij = ratio of the circumference of a circle centered at UM-A (the sum is of all pairs of trees not greater than t).

The transformation of the square root of the function K(t) of Ripley was used to determine the statistical significance of the function L(t), with Monte Carlo simulations (Besag, 1977):

 

RESULTS AND DISCUSSION

Stratification of heights

The tree component of pine-oak forest in Ixtlán measured on average 13.8 m high, with few trees exceeding 28.0 m. Two vertical strata were identified: the bottom stratum (≤ 10 m) and the upper stratum (> 10 m). Figure 1 shows the vertical stratification of the tree component. The vertical stratification in SU1 and SU3 was similar: 24.8 and 26.0 % at the bottom stratum and 75.2 and 74.0 % at the upper stratum, respectively. In SU2, about half of all trees were concentrated on the bottom stratum. Castellanos-Bolaños et al. (2008) indicated that in the same mixed pine-oak forest in Ixtlán de Juárez, Oaxaca dominates an upper stratum of Pinus spp., but given that in this study the SU were established in stands of oak, the upper layer was physiognomically determined by Q. laurina and Q. crassifolia. Sánchez-Rodríguez, López-Mata, García-Moya, and Cuevas-Guzmán (2003) reported that the stratification of the forest is a function of the most important species in each locality (dominance of oaks in this case), and that the greatest number of trees is concentrated on the first two height classes, as was presented in the Figure 1. The size of the trees have phenotypic explanation, since according to the description of oak taxa (Oaks of the world: http://oaks.of.the.world.free.fr/index.htm), allometry registered for oaks in Ixtlán corresponds to the sizes of oaks for the sympatry area (Sierra Madre del Sur in Mexico and Guatemala), in the two species of interest; on average, Q. laurina has a height of 19.3 m and a diameter of 14.4 cm, whereas Q. crassifolia has a height of 15.3 m and a diameter of 22.9 cm.

Diameter distribution

Figure 2 shows the diameter distribution of the tree component of the sampling units analyzed. In the three SU, 63 % of the trees sampled were included in the first four diameter categories (DC) (ND ≤ 22.5 cm). In SU1 and SU2, the distribution is skewed (Figure 2) and according to the expected for a natural forest, as the diameter of the stem increases, the number of trees decreases, which means that there is seed supply, establishment of seedlings, and natural incorporation to the woodland (Bongers, Pompa, Del Castillo, & Carabias, 1988). SU3 has 32 % of the trees in the DC 25 and 30; however, the number of trees remains higher in lower DC.

Structural indexes

A total of 799 trees belonging to 19 species and 11 families were measured in the three SU; Fagaceae was the most abundant family (628 trees, and four species). The individuals measured were extrapolated to obtain the total density per hectare. In SU1, the density was 1,096 trees·ha^-1; Q. crassifolia represented 60.9 % (668 trees·ha^-1), followed by Q. laurina with 30.3 % (332 trees·ha^-1). The total basal area was 42.3 m²·ha^-1, where the relative dominance of Q. crassifolia and Q. laurina was 58.4 and 25.8 %, respectively. In SU2, the extrapolated density was 1,208 trees·ha^-1, where Q. laurina represented 57.0 % (688 trees·ha^-1) and Q. crassifolia 9.9 % (120 trees·ha^-1). In SU2 the total basal area was 39.7 m²·ha^-1; the relative dominance of Q. laurina and Q. crassifolia was 61.9 and 7.1 %, respectively. In SU3, the extrapolated density was 892 trees·ha^-1, of which Q. crassifolia had 52.5 % (468 trees·ha^-1), followed by Q. laurina with 25.6 % (228 trees·ha^-1). The total basal area was 49.4 m²·ha^-1 and the relative dominance of Q. crassifolia and Q. laurina was 67.3 and 23.8 %, respectively.

Table 1 shows the RIVI of the three SU and the IVF per species. In SU1 and SU3, Q. crassifolia stand out as the most important species both in RIVI and IVF, followed by Q. laurina which is the most important species in SU2, which means that Quercus dominates structurally in both SU. In the three sampling units, the genus Quercus has between 57.9 and 82.9 % of structural importance, measured by RIVI, while the remaining species, although they are many, represent only 17.1 and 42.1 %, indicating lower amount and smaller sizes of the trees. In SU2, A. acuminata ranked second in the RIVI, while P. pseudostrobus ranked second in the IVF. This was expected, given that P. pseudostrobus reaches greater heights compared to A. acuminata and considering that the IVF includes the variables in both (horizontal and vertical) dimensions.

In the Sierra of Coahuila, Encina-Domínguez, Zárate-Lupercio, Estrada-Castillón, Valdés-Reyna, and Villarreal-Quintanilla (2009) found that higher RIVI correspond to Q. greggii Trel. (41.3) and Q. mexicana Humb. & Bonpl. (18.7). The density was 1,480 trees·ha^-1 with basal area of 9 m²·ha^-1 for Q. greggii, and 284 trees·ha¹ and 5.68 m²·ha^-1 for Q. mexicana. In this study, the densities of Q. laurina (416 trees·ha^-1) and Q. crassifolia (419 trees·ha¹) were lower than recorded for Q. greggii. However, the average of basal area of the three SU was higher; 15.7 m²·ha^-1 and 20.2 m²·ha^-1 for Q. laurina and Q. crassifolia, respectively. This result is an indicator of favorable environmental conditions for the growth of oaks in Ixtlán de Juárez, with annual rainfall between 800 m and 1,200 mm compared to 498 mm of rain in the Sierra of Coahuila; 2,700 m of elevation in Ixtlán against 1,590 m to 2,200 m in the Sierra of Coahuila; humid temperate climate in the south against prevailing dry climate to the north; and soil type humic acrisol l in Oaxaca, compared to lithosols and rendzinas (stony and shallow soils) in Coahuila. The most suitable physical conditions in Ixtlán, Oaxaca, compared to those of the Sierra of Coahuila, would explain the presence of larger diameters in Q. laurina and Q. crassifolia. In addition, these diameters are the result of poor use of oak species, because without use these species reach older ages and, consequently, larger diameters. Environmental conditions similar to this study are those mentioned by Zacarías-Eslava, Cornejo-Tenorio, Cortés-Flores, González-Castañeda, and Ibarra-Manríquez (2011) in the oak-pine forest of the Cerro El Águila, Michoacán, Mexico, where the species with higher RIVI was Q. laurina (21.8); however, the density (141 trees·ha^-1) and basal area (17.31 m²) were lower than those reported in the present study for Q. crassifolia. Similarly, Rubio-Licona, Romero-Rangel, and Rojas-Zenteno (2011) reported that in the oak-pine forest in Villa del Carbón, Estado de México, the RIVI of Q. crassifolia was 62.4 %, which suggests that this forest is little disturbed, with even distribution of species and good incorporation of young trees to the community.

Species diversity

Table 2 presents the values of richness and diversity of species in the sampled units. This table shows that the diversity measured with the index of entropy of Shannon (H') was significantly different (P ≤ 0.05) between SU1 (H' = 1.02) and SU2 (H' = 1.51), and between SU1 (H' = 1.02) and SU3 (H' = 1.43), while there were no such differences between SU2 and SU3 (P > 0.05). The indices to estimate the diversity agree that SU1 has the lowest values of the three SU, indicating lower species diversity. According to Tárrega, Calvo, Marcos, and Taboada (2006), differences between sampling sites are due to the composition of the understory or to the species ability to survive and recuperate to a disturbance. The equity evaluated based on Shannon index was higher in SU2, indicating proportional abundance among species, and lower in SU1, reflecting the dominance of few species. Based on the conversion of the Shannon index (effective number of species), it was determined that diversity in SU1 is equal to the diversity that a theoretical community would have with 2.77 species with the same abundance. Moreover, with this efective number we can differentiate visibly that diversity in SU1 is 39 % lower than in SU2, and 34 % lower than in SU3 (Table 2). The low diversity in SU1 reflects the high structural importance (83 %) of Q. laurina and Q. crassifolia. Moreover, Table 3 shows that according to the Sorensen Index greater similarity was found between SU1 and SU2, that between SU1 and SU3. In the latter, the lower values of similarity express greater spatial replacement in species composition (Zacarías-Eslava et al., 2011), possibly due to the slow colonization and germination capacity of seeds of different species, after the disturbances caused by forest harvesting.

Spatial distribution

In the three SU analyzed, Q. crassifolia and Q. laurina alternate their distribution patterns between random and clumped. In SU1, Q. laurina trees showed a clumped distribution pattern, except between 4 and 8 m where result important the random pattern. In contrast, Q. crassifolia showed a random pattern ofspatial distribution in SU1, where most of the spaces are occupied by Q crassifolia trees except for distances between 0-3 m where highlight clumped distribution. In SU2, Q. laurina presented a random pattern and had the lowest number of Q. crassifolia trees (30 trees) with clumped distribution at distances less than 12 m; random distribution between 11.5 and 14 m at greater distances of 19 m; and an even distribution among distances of 14 and 19 m. In SU3, the two oaks showed almost similar patterns as SU1; Q. laurina had clumped pattern and Q. crassifolia showed greater tendency to a random distribution. Where Q crassifolia had the highest RIVI (SU1 and SU3), the species showed a pattern of random distribution. Something similar happened in SU2, where Q. laurina had the largest RIVI and their distribution pattern was also random. By contrast, in the SU1 and SU3, Q. laurina which was the second importance value had clumped patterns, indicating that they are associated with a lower tree density and probably with the position of hierarchically subordinate species to the dominant species, occupying the spaces left free. The clumped pattern is due to specific topographic conditions or to a heterogeneous field (Condés, & Martínez, 1998; Linzaga-Román, Ángeles-Pérez, Catalán-Heverástico, & Hernández de la Rosa, 2011), leading to high variation in the distribution of light and soil nutrients. However, Figure 3 shows patterns of random distribution when analyzing the spatial distribution of Q. laurina and Q. crassifolia in each SU, indicating that the spatial distribution of each species is due to the relations of association between trees; to the different regeneration strategies, v. g. the asynchrony in producing acorns as a mechanism to reduce competition between sympatric species (Crawley & Long, 1995);vvvv to the dispersion of the species, v. g. acorns dispersed to reduce mortality result of predation (Pérez, Barrera, García, Cuevas-Reyes, & González-Rodríguez, 2013); and to silvicultural practices in the field, v. g. selective cutting of species of the genus Pinus (STF, 2008) rather than to topographic conditions or soil characteristics (Martínez-Ramos, 1994; Montes, Del Río, & Cañellas, 2003). Additionally, it is also possible that suitable conditions for the dominance of some species are generated when a breeding cycle coincides with the release of space to any disturbance (Márquez-Linares, González-Elizondo, & Álvarez-Zagoya, 1999).

 

CONCLUSIONS

Based on the Relative Importance Value Index (RIVI) and forest value (FVI), greater dominance of species of the genus Quercus (Q. crassifolia and Q. laurina) was found in the three sampling units (SU). The tree density was higher in SU2, where the greatest diversity of species was recorded; however, the highest basal area was measured in SU3. In the diversity of species, differences between SU1 and SU2 were found, and also in SU1 and SU3. According to the effective number of diversity, SU1 has lower diversity compared to SU2 and SU3, this aspect is attributed to the high dominance of Quercus species. The spatial distribution patterns were randomized in species with greater IVI in each SU. The analysis of the spatial distribution of both Q. crassifolia and Q. laurina, revealed a random distribution in practically all distances tested. The clumped pattern of tree species was attributed to regeneration strategies and silvicultural practices in the area. It is possible that both species can coexist in one place.

 

ACKNOWLEDGEMENTS

The first author is grateful to the Teacher's Improvement Program (PROMEP) of the Universidad de la Sierra Juárez for having granted the scholarship for postgraduate studies (folio number UNSIJ/001). The first author thanks Dr. Marcos M. González Peña who edited a preliminary version of this document.

 

REFERENCES

Álvarez, S. & Rubio, A. (2013). Línea base de carbono en bosque mixto de pino-encino de la Sierra Juárez (Oaxaca, México). Aplicación del modelo CO2FIX V. 3.2. Revista Chapingo Serie Ciencias Forestales y del Ambiente, 19(1), 125-137. doi: 10.5154/r.rchscfa.2012.01.005.         [ Links ]

Aquino-Vásquez, C., Ruiz-Aquino, F., & Fuente-Carrasco, M. E. (2012). Caracterización del patrimonio natural de la comunidad de Ixtlán de Juárez: Una aproximación desde el espacio territorial. In M. E. Fuente-Carrasco, F. Ruiz-Aquino, & C. Aquino-Vásquez (Eds), Conocimiento indígena contemporáneo y patrimonio biocultural en la Sierra Juárez de Oaxaca: Aportaciones empíricas y analíticas hacia la sustentabilidad (pp. 35-59). México: Universidad de la Sierra Juárez.         [ Links ]

Badii, M. H., Landeros, J., & Cerna, E. (2008). Patrones de asociación de especies y sustentabilidad. Daena: International Journal of Good Conscience, 3(1), 632-660. Obtenido de http://www.spentamexico.org/v3-n1/3%281%29%20632-660.pdf.         [ Links ]

Besag, J. (1977). Contribution to the discussion on Dr. Ripley's paper. Journal of the Royal Statistical Society, 39, 193-195.         [ Links ]

Bongers, F., Pompa, J., Del Castillo, J. M., & Carabias, J. (1988). Structure and floristic composition of the lowland rain forest of Los Tuxtlas, Mexico. Vegetatio, 74(1), 55-80. doi: 10.1007/BF00045614.         [ Links ]

Castellanos-Bolaños, J. F., Treviño-Garza, E. J., Aguirre-Calderón, O. A. Jiménez-Pérez, J., Musalem-Santiago, M., & López-Aguillón, R. (2008). Estructura de bosques de pino pátula bajo manejo en Ixtlán de Juárez, Oaxaca, México. Madera y Bosques, 14(2), 51-63. Obtenido de http://www1.inecol.edu.mx/myb/resumeness/14.2/MB_2008_14-2_051-064.pdf.         [ Links ]

Condés, S. & Martínez, M. (1998). Comparación entre los índices de distribución espacial de árboles más usados en el ámbito forestal. Investigación Agraria. Sistemas y Recursos Forestales, 7(1/2), 173-187. Obtenido de http://www.inia.es/gcontrec/pub/12.S.CONDES_1047630757178.pdf.         [ Links ]

Corella-Justavino, F., Valdez-Hernández, J. I., Cetina-Alcalá, V. M., González-Cossio, F. V., Trinidad-Santos, A. & Aguirre-Rivera, J. R. (2001). Estructura forestal de un bosque de mangles en el noreste del estado de Tabasco, México. Ciencia Forestal en México, 26(90), 73-102. Obtenido de http://revistas.inifap.gob.mx/index.php/Forestales/article/view/38/29.         [ Links ]

Cortés, S. P. (2003). Estructura de la vegetación arbórea y arbustiva en el costado oriental de la serranía de Chía (Cundinamarca, Colombia). Caldasia, 25(1), 119-37. Obtenido de http://www.unal.edu.co/icn/publicaciones/caldasia/25(1)/ecologia3.pdf.         [ Links ]

Crawley, J. & Long, C. R. (1995). Alternated bearing, predation satiation and recruitment in Quercus robur L. Journal of Ecology, 83, 683-606. Obtenido de http://www.jstor.org/stable/2261636.         [ Links ]

Curtis, J. T. & McIntosh, R. P. (1951). An upland forest continuum in the pariré-forest border region of Wisconsin. Ecology, 32, 476-496. Obtenido de http://biosurvey.ou.edu/rice_and_penfound/1931725.pdf.         [ Links ]

Encina-Domínguez, J. A., Zárate-Lupercio, A., Estrada-Castillón, E., Valdés-Reyna, J., & Villarreal-Quintanilla, J. (2009). Composición y aspectos estructurales de los bosques de encino de la sierra de Zapalinamé, Coahuila, México. Acta Botánica Mexicana, 86, 71-108. Obtenido de http://www.scielo.org.mx/pdf/abm/n86/n86a4.pdf.         [ Links ]

García, E. (1987). Modificaciones al sistema de clasificación climática de Köppen (para adaptarlo a las condiciones de la República Mexicana). México: Instituto de Geografía, UNAM.         [ Links ]

Hutcheson, K. (1970). A test for comparing diversities based on Shannon formula. Journal of Theoretical Biology, 29, 151-154.         [ Links ]

Hutchings, M. J. (1997). The structure of plant populations. In M. J. Crawley (Ed.), Plant ecology (pp. 325-358). Oxford, UK: Blackwell Science.         [ Links ]

Jost, L. (2006). Entropy and diversity. Oikos, 113(2), 363-375. doi: 10.1111/j.2006.0030-1299.14714.x.         [ Links ]

Krebs, C. J. (1989). Species diversity measures. In C. J. Krebs (Ed), Ecological methodology (pp. 328-370). USA: Harper & Row.         [ Links ]

Linzaga-Román, B. E., Ángeles-Pérez, G., Catalán-Heverástico, C., & Hernández de la Rosa, P. (2011). Estructura espacial de Pachycereus weberi (Coult.) Backeb. en la Cañada del Zopilote, Guerrero. Revista Chapingo Serie Ciencias Forestales y del Ambiente, 17(2), 189-198. doi: 10.5154/r.rchscfa.2010.06.039.         [ Links ]

Márquez-Linares, M. A., González-Elizondo, S., & Álvarez-Zagoya, R. (1999). Componentes de la diversidad arbórea en bosques de pino encino de Durango, Méx. Madera y Bosques, 5(2), 67-77. Obtenido de http://www.redalyc.org/articulo.oa?id=61750206.         [ Links ]

Martínez-Ramos, M. (1994). Regeneración natural y diversidad de especies arbóreas en selvas húmedas. Boletín de la Sociedad Botánica de México, 54, 179-224. Obtenido de http://www.oikos.unam.mx/LECT/images/publicaciones-2000/mmr_regenaracion_1994.pdf.         [ Links ]

Montes, T. F., Del Río, M., & Cañellas, I. (2003). Índices de diversidad estructural en masas forestales. Investigación Agraria. Sistemas y Recursos Forestales, 12(1), 159-176. Obtenido de http://dialnet.unirioja.es/servlet/ejemplar?codigo=72072.         [ Links ]

Moreno, C. E. 2001. M & T. Manuales y Tesis SEA. Métodos para medir la biodiversidad. Zaragoza, España. Obtenido de http://entomologia.rediris.es/sea/manytes/metodos.pdf.         [ Links ]

Moreno, C. E., Barragán, F., Pineda, E., & Pavón, N. P. (2011). Reanálisis de la diversidad alfa: Alternativas para interpretar y comparar información sobre comunidades ecológicas. Revista mexicana de biodiversidad, 82(4), 1249-1261. Obtenido de http://www.scielo.org.mx/pdf/rmbiodiv/v82n4/v82n4a19.pdf.         [ Links ]

Oaks of the world. Consultado 23-04-2014 en http://oaks.of.the.world.free.fr/index.htm.         [ Links ]

Pérez, L. P., Barrera, F. L., García, O. F., Cuevas-Reyes, P., & González-Rodríguez, A. (2013). Procesos de regeneración natural en bosques de encinos: Factores limitadores y limitantes. Biológicas, 1, 18-24. Obtenido de http://www.biologicas.umich.mx/index.php/biologicas/article/viewFile/148/pdf.         [ Links ]

Rainforest Alliance. (2006). Resumen público de certificación de la comunidad de Ixtlán de Juárez, Oaxaca. New York, USA: Rainforest Alliance-Consejo de Manejo Forestal-SmartWood.         [ Links ]

Ripley, B. D. (1977). Modelling spatial patterns (with discussion). Journal of the Royal Statistical Society, 39, 172-212. Obtenido de http://www.stat.colostate.edu/~bradb/files/brad.pdf.         [ Links ]

Rubio-Licona, L. E., Romero-Rangel, S., & Rojas-Zenteno, E. C. (2011). Estructura y composición florística de dos comunidades con presencia de Quercus (Fagaceae) en el Estado de México. Revista Chapingo Serie Ciencias Forestales y del Ambiente, 17(1), 77-90. doi: 10.5154/r.rchscfa.2010.03.014.         [ Links ]

Ruiz-Aquino, F., Valdez-Hernández, J. I., Manzano-Méndez, F., Rodríguez-Ortiz, G., Romero-Manzanares, A., & Fuentes-López, M. E. (2014). Ecuaciones de biomasa aérea para Quercus laurina y Q. crassifolia en Oaxaca, México. Madera y Bosques, 20(2), 33-48. Obtenido de http://www1.inecol.edu.mx/myb/resumeness/20.2/myb2023348.pdf.         [ Links ]

Sánchez-Rodríguez, E. V., López-Mata, L., García-Moya, E., & Cuevas-Guzmán, R. (2003). Estructura, composición florística y diversidad de especies leñosas de un bosque mesófilo de montaña en la Sierra de Manantlán, Jalisco. Boletín de la Sociedad Botánica de México, 73, 17-34. Obtenido de http://www.redalyc.org/articulo.oa?id=57707302.         [ Links ]

Servicios Técnicos Forestales (STF). (2008). Estudio sobre el aprovechamiento del encino Ixtlán de Juárez, Oaxaca, México: Autor.         [ Links ]

Tárrega, R., Calvo, L., Marcos, E., & Taboada, A. (2006). Forest structure and understory diversity in Quercus pyrenaica communities with different human uses and disturbances. Forest Ecology and Management, 227(1), 50-58. doi:10.1016/j.foreco.2006.02.008.         [ Links ]

Técnica Informática Aplicada, S. A. (TIASA). (1993). Programa de manejo forestal de Ixtlán de Juárez, Oaxaca. México: Autor.         [ Links ]

Vázquez-Negrín, I., Castillo-Acosta, O., Valdez-Hernández, J. I., Zavala-Cruz, J., & Martínez-Sánchez, J. L. (2011). Estructura y composición florística de la selva alta perennifolia en el ejido Niños Héroes Tenosique, Tabasco, México. Polibotánica, 32, 41-61. Obtenido de http://www.herbario.encb.ipn.mx/pb/pdf/pb32/flor.pdf.         [ Links ]

Villavicencio-Enríquez, L. & Valdez-Hernández, J. I. (2003). Análisis de la estructura arbórea del sistema agroforestal rusticano de café en San Miguel, Veracruz, México. Agrociencia, 37(4), 413-423. Obtenido de http://www.redalyc.org/pdf/302/30237410.pdf.         [ Links ]

Zacarías-Eslava, L. E., Cornejo-Tenorio, G., Cortés-Flores, J., González-Castañeda, N., & Ibarra-Manríquez, G. (2011). Composición, estructura y diversidad del cerro El Águila, Michoacán, México. Revista Mexicana de Biodiversidad, 82(3), 854-869. Obtenido de http://www.scielo.org.mx/pdf/rmbiodiv/v82n3/v82n3a12.pdf.         [ Links ]

Zarco-Espinosa, V. M., Valdez-Hernández, J. I., Ángeles-Pérez, G., & Castillo-Acosta, O. (2010). Estructura y diversidad de la vegetación arbórea del parque estatal Agua Blanca, Macuspana, Tabasco. Universidad y Ciencia Trópico Húmedo, 26(1), 1-17. Obtenido de http://www.scielo.org.mx/pdf/uc/v26n1/v26n1a1.pdf.         [ Links ]