*2.1.2 Identification, distribution and abundance of forest species*

To identify the tree and shrub diversity in the study area, we conducted 60 phytoecological inventories in 60 different sites distributed randomly using the sampling scheme already described (**Table 1**).

The field samplings were performed in rectangular plots of 600 m<sup>2</sup> , with a central line 100 m in length and two lateral lines with three m of separation. In each inventory, the frequency of the tree and shrub species present were determined, as well as the site environmental variables. Individuals with DBH ≥ 5 cm and height ≥ 1.50 m were considered as trees. Individuals below these categories were


*The intersections between lines and columns whose value is zero, indicate areas with little representativeness in the landscape and consequently an absence of samplings.*

#### **Table 1.**

*Number of samplings performed at different altitudinal levels, topographic positions and solar exposures, derived from the sampling system.*

#### *Ecology of Plant Communities in Central Mexico DOI: http://dx.doi.org/10.5772/intechopen.95629*

considered as juveniles and shrubs. The variables recorded in the site were: altitude, slope (in %), solar exposure (N, S, E, W), physiography (flat land, hillock, plateau, middle slope, high slope, ravine bottom, creek), coverage (c1 = ≤10%; c2 = 11–30%; c3 = 31–50%; c4 = 51–70% y c5 = ≥70%) and geoform. Management variables related to land use (no use, forest exploitation, wildlife management, grazing, agriculture and conservation) were considered as well as intensity of use (null, moderate, over-exploited and not determinable). Each one of the sampling points were geographically located by Transverse Mercator Units (UTM).

In order to identify the oak and conifer species in the field, keys generated by De la Cerda [17] and Siqueiros [18], respectively, were used. The unknown species were collected in botanical presses and identified at the Autonomous University of Aguascalientes herbarium (HUAA). To leave evidence of the new species records in the ANP SF, specimens were deposited in the HUAA.

#### *2.1.3 Distribution and abundance of species*

To estimate the distribution of tree and shrub forest species, the presence of each of the species found in each of the 60 sampling sites was quantified. In the case of species considered as restricted distribution (eg. *Quercus cocolobifolia, Pinus chihuahuana*, and *P. duranguensis* var*. quinquefoliata*), samples were taken at specific sites (n = 4), according to the information provided by De la Cerda [17] and Siquéiros [18]. Species with a wide distribution were those that occurred in the greatest number of sites.

The frequency of the species found was determined on 100 m transect at ground level, observing 100 separate points every meter. The species found at each point were recorded (when there was more than one vegetation layer), counting the number of times that each species appeared (absolute frequency) [16] over the whole transect. Relative frequency was calculated using the Equation [19]:

$$\text{Relative frequency} = \left(\frac{\text{Species frequency}}{\sum \text{Frequency values of all} \quad \text{species}}\right) \tag{1}$$

Where:

*2.1.2 Identification, distribution and abundance of forest species*

*Natural History and Ecology of Mexico and Central America*

**Altitude levels Topographic position**

**Total inventories 60**

*landscape and consequently an absence of samplings.*

*derived from the sampling system.*

**Table 1.**

**18**

sampling scheme already described (**Table 1**).

**Figure 2.**

To identify the tree and shrub diversity in the study area, we conducted 60 phytoecological inventories in 60 different sites distributed randomly using the

central line 100 m in length and two lateral lines with three m of separation. In each inventory, the frequency of the tree and shrub species present were determined, as

**N SEWN SEW** 2000–2200 0 0 0 0 1 1 0 0 1 3 2200–2400 0 1 0 0 3 2 0 0 0 6 2400–2600 8 4 1 1 8 3 0 0 3 28 2600–2800 2 0 0 1 4 3 0 0 11 21 > 2800 2 0 0 0 0 0 0 0 0 2 **Total 12 5 1 2 16 9 0 0 15 60**

*The intersections between lines and columns whose value is zero, indicate areas with little representativeness in the*

*Number of samplings performed at different altitudinal levels, topographic positions and solar exposures,*

**Concave Convexe Flat Total**

, with a

The field samplings were performed in rectangular plots of 600 m<sup>2</sup>

*Location of the protected natural area sierra Fria, the study area of the Temperate Mountain Forest.*

well as the site environmental variables. Individuals with DBH ≥ 5 cm and height ≥ 1.50 m were considered as trees. Individuals below these categories were

> Frequency of the species x = absolute frequency obtained from each site sampling.

Subsequently, an abundance index was calculated using the equation:

$$\text{Spp.ai} = \frac{\sum\_{\text{relative frequencies}}}{\text{Number of sampled sites}} \tag{2}$$

Where:

Spp.ai = Identified Species abundance index.

With this data, distribution and abundance graphs of the main arboreal-shrub forest species were created. The phytoecological analysis was used to calculate the species richness and the Shannon index diversity (*H´*) and the beta Whittaker's (ßw) index respectively, the first were calculated as a function of the altitudinal level, the second also incorporating the geoform using the Species Diversity and Richness® (Pisces Conservation LTD) software. Pear calculate the indexes we used the equation:

$$H' = -\sum\_{i=1}^{S} p\_i \log\_2 p\_i \tag{3}$$

#### Where

S = species richness; Pi = proportion of the individuals of species i with respect to the total number of individuals; ni = number of individuals of species i

$$\mathcal{R}\_{\mathbf{w}} = \frac{\mathbf{S}}{\overline{\mathbf{S}}} \tag{4}$$

Solar exposure was defined using an exposure map made with a Geographic Information System from a 2008 Spot® satellite image and a digital elevation model (MDE). Only the main cardinal points (North, South, East and West) were considered. To locate the altitudinal strata, the contours of the zone defined from the MDE were used. Subsequently, a grid map was developed for the identification of the

*2.2.3 Selection and characterization of sites to quantify of the composition and abundance*

We established 26 sites to quantify phytoecological inventories, distributed in the landscape according to the above mentioned sampling system. At each point, the projected coordinates of the site were taken with GPS Garmin 48 XL line in UTM format, zone 13 North and with reference Datum WGS84 and with accuracies of 5 to 12 m with differential kinematic adjustment (WAAS). Subsequently, the points were placed on a SPOT 2010 satellite image (**Figure 5**). Site variables considered were the slope (%), solar exposure, physiography of the terrain, intensity

Slope at each sampling site was obtained by direct field measurement with a Bruntton clinometer with a precision of +/ 2° of variation for each 100 meters of length. This data in turn was contrasted with the data obtained from the digital elevation model with precision of 1 to 2 meters in the Z value. Five classes were used to define the slope: i) <10%, ii) 11–30, iii) 31–50, iv) 51–70 and v) > 70. Exposure to solar radiation was estimated considering the cardinal points North (N), South (S),

The altitude of each site was obtained directly in the field with the support of a GPS with barometric adjustment to reduce the effect of mathematical variation of the Geoid model and with precision of 1 to 3 meters. This was compared with the data obtained from the prospecting of points against elevation level curves obtained

*Geographic representation of dry tropical Forest and the sampling points in Terrero de la labor Ejido, in the*

sampling areas (See **Figure 4**).

*Ecology of Plant Communities in Central Mexico DOI: http://dx.doi.org/10.5772/intechopen.95629*

and type of use and canopy coverage.

East (E) and West (O), as well as their combinations.

*of woody species*

**Figure 4.**

**21**

*municipality of Calvillo, Aguascalientes.*

Where:

S = Species richness and S = mean richness of the site.

#### **2.2 Dry Tropical Forest (DTF)**

#### *2.2.1 Study area*

Although there are some studies that suggest the existence of relics of Dry Tropical Forest (DTF) vegetation in some municipalities of the Aguascalientes State [15, 20], this ecosystem has a greater representation both in surface area and in its conservation status in Calvillo municipality. The study was conducted in 26 sites with DTF vegetation cover in Terrero de la Labor ejido, located within the Sierra Fria Protected Natural Area, in the Municipality of Calvillo, State of Aguascalientes, in Central Mexico. The ejido polygon comprises an area of 5,861 ha. [21], of which, the DTF occupies 45% of its total area (**Figure 3**). It is located within the extreme coordinates: 102°43<sup>0</sup> 58.88" West Longitude and 22°6'4.78" North Latitude and at the Southeast end 102°41<sup>0</sup> 24.95" West Longitude and 21°44'27.61" North Latitude.

#### *2.2.2 Selection of the study sites and sampling design*

We used a stratified sampling design system [16]. Sampling strata were delimited based on geoforms, slope, exposure and altitude. To characterize geoforms, three criteria were used: concave, convex and flat terrain. A concave geoform was defined when the slope ranged between 10 and 25%, which usually corresponded to ravines and small depressions. When the sites had a slope between 25 and 60% they were characterized as convex sites. Flat terrains had slopes <10%.

#### **Figure 3.**

*Location of the study area. (A) Mexico, (B) state of Aguascalientes, (C) municipality of Calvillo and (D) Terrero de la labor Ejido.*

*Ecology of Plant Communities in Central Mexico DOI: http://dx.doi.org/10.5772/intechopen.95629*

Where

Where:

*2.2.1 Study area*

coordinates: 102°43<sup>0</sup>

**Figure 3.**

**20**

*Terrero de la labor Ejido.*

the Southeast end 102°41<sup>0</sup>

*2.2.2 Selection of the study sites and sampling design*

**2.2 Dry Tropical Forest (DTF)**

S = species richness; Pi = proportion of the individuals of species i with respect to

ßw <sup>¼</sup> <sup>S</sup>

Although there are some studies that suggest the existence of relics of Dry Tropical Forest (DTF) vegetation in some municipalities of the Aguascalientes State [15, 20], this ecosystem has a greater representation both in surface area and in its conservation status in Calvillo municipality. The study was conducted in 26 sites with DTF vegetation cover in Terrero de la Labor ejido, located within the Sierra Fria Protected Natural Area, in the Municipality of Calvillo, State of Aguascalientes, in Central Mexico. The ejido polygon comprises an area of 5,861 ha. [21], of which, the DTF occupies 45% of its total area (**Figure 3**). It is located within the extreme

We used a stratified sampling design system [16]. Sampling strata were delimited based on geoforms, slope, exposure and altitude. To characterize geoforms, three criteria were used: concave, convex and flat terrain. A concave geoform was defined when the slope ranged between 10 and 25%, which usually corresponded to ravines and small depressions. When the sites had a slope between 25 and 60% they were characterized as convex sites. Flat terrains had slopes <10%.

*Location of the study area. (A) Mexico, (B) state of Aguascalientes, (C) municipality of Calvillo and (D)*

58.88" West Longitude and 22°6'4.78" North Latitude and at

24.95" West Longitude and 21°44'27.61" North Latitude.

<sup>S</sup> (4)

the total number of individuals; ni = number of individuals of species i

S = Species richness and S = mean richness of the site.

*Natural History and Ecology of Mexico and Central America*

Solar exposure was defined using an exposure map made with a Geographic Information System from a 2008 Spot® satellite image and a digital elevation model (MDE). Only the main cardinal points (North, South, East and West) were considered. To locate the altitudinal strata, the contours of the zone defined from the MDE were used. Subsequently, a grid map was developed for the identification of the sampling areas (See **Figure 4**).
