MATERIALS AND METHODS

5.2.1 STUDY AREA

The study was carried out in Nuevo Leon State, at the Northeast Mexico, located within the coordinates 23° 10’27” and 27° 46’06”of North latitude,

98° 26’24” and 101° 13’55” West longitude, with a territorial extension of 65,103 km2. The Tropic of Cancer line is located in the parallel 23° 27’ N crossing the State in the south. It is politically divided in 52 municipalities and has a population of 3,834,141 inhabitants. The analysis was made within the Rio Grande river hydrological basin (39,661.014 km2), San Femando- Soto La Marina area (11,521.683 km2), and El SaJado area (12,373.772 km2).

Based on thematic maps of land use and vegetation, scale 1:50,000 and digital ortophotos published by the INEGI (2002), stands with vegetation including mesquite were delimited, numbered in progressive fonn, and selected at random in order to determine the minimum size of the parcel using the method of the species/area curve (Franco et al., 2001). The study area was visited for the correct localization of the selected sites and the recognition of the communities with mesquite using a Global Positioning System (GPS) receiver to register the geographical coordinates of latitude, longitude, and elevation above sea level of each one of the study sites selected (Table 5.1 and Fig. 5.2).

5.2.2 CLIMATE AND SOILS

The climate of northeast Mexico (Nuevo Leon State) is in extreme contrast. The hot and diy climate predominates and it is associated to “B” diy climate, “Bw” arid or veiy diy, and “Bs” semiarid or semidiy of the Kopen classification. Most of the year it is veiy hot, mainly in the plains, since at the mountain regions the altitude attenuates the warm temperatures. In these areas the months from November to January are cold.

Other types of climates are also present at a lesser extent, as the semi- calid (A)C and the temperate subhumid C(W). The high climatic contrast is also verified in the top of the mountain range with an alpine climate Project Management Organization Energy, Technology, Sustainability (ETN) is loacted at Forschungszentrum Julich.

The mean annual temperature is 22.3°C with a large difference between winter and summer (-2.3 to 41.1°C). Hail and frosts usually occur eveiy year even after the beginning of the growing season in March. The longterm mean annual precipitation values vary from 380 nun (arid zones) to 749 nun (semiarid zones) with two peaks in late May and July-September and drought periods in June and winter. The water budget is unbalanced. The ratio of precipitation to free evaporation is 0.48 and precipitation to potential evaporation is 0.62 (Navar et al., 2004).

Physiographic province

Site/municipality

UTM X

UTM Y

Altitude

Great Plain of North America

2: Ejido Colorados de Arriba, Vallecillo

400906

2927506

239

4: La Barretosa. Los Herreras

451990

2858539

166

5: Ejido Emiliano Zapata. Paras

431651

2937498

164

6: Puente del Rio Salado. Anahuac

413460

2982484

146

7: Loma Larga. General Trevino

448858

2904109

147

9: Ejido El Alamo, Vallecillo

421068

2929095

195

24: El Nogal. Anahuac

399125

3005741

177

25: Comun. Regantes 26. Anahuac

367140

3024331

228

26: Rancho La Ceja. Los Aldama

476956

2883426

112

Mountain ranges and plains of Coahuila

1: Plan del Oregano. Melchor Ocampo

457694

2883106

152

3: El Llano. Los Ramones

437024

2854589

193

13: Los Pajaritos, Doctor Gonzalez

408854

2863751

423

17: El Resumidero. Salinas Victoria

373712

2882558

451

18: El Puente. Salinas Victoria

372252

2872246

424

19: Rancho Gomas, Salinas Victoria

353164

2895485

568

23: Ejido Las Presas. Lampazos

348405

2982066

341

27: El cuchillo. China

474439

2845014

138

Coastal plain of the North Gulf

8: Los Ebanos, Los Ramones

453517

2824931

196

10: Dulces Nombres. Pesqueria

394236

2844953

351

11: Hacienda San Pedro. Oral. Zuazua

384066

2867217

369

12: Higueras, Higueras

398119

2872672

503

14: Rancho El Recuerdo. Gral. Teran

427656

2806597

285

15: Loma La Parada. Marin

401847

2856144

323

16: El Bajio. Marin

402122

2858136

342

20: Kilornetro 80. Los Ramones

446057

2837409

191

21: Rancho La Bonanza. Grab Teran

467187

2787506

217

22: Rancho Nuevo, Grab Teran

452841

2790393

259

28: San Pedro de los Escobedo Linares

462356

2760631

261

29: San Ignacio de Texas. Galeana

379092

2690496

1684

30: Ejido Puentes. Arambarri

390606

2670446

1581

Distribution of mesquite scrub and woodland covered areas in northeast Mexico and sampling sites

FIGURE 5.2 Distribution of mesquite scrub and woodland covered areas in northeast Mexico and sampling sites.

The soils of the region are basically stony of Upper Cretaceous siltstone, with pH 7.5-8.5 and abundant limestone. In the FAO (2006) classification, these soils are classified as rendzine, vertisoils, feozem, and castanozem with low organic matter content and low levels of phosphorus and nitrogen. Underground water is hard but not saline.

The Nuevo Leon State presents five morphological zones well defined which correspond to the physiographical provinces. These morphological units are demonstrated in the Figure 5.3.

Once the sites were located in each geographic zone, the minimum area in each one of them was considered with the purpose to obtain a represented vegetal composition employing the technique of the nested sample according to Salvador and Alvarez (2004). The species occurring in each subsample were registered and the minimum area of sampling was determined as the surface where at least 95% of the species of the vegetal community were contained.

Permanent 10 x 10 m quadrant sampling along each study zones and site was made at random. The average distance among the plots varied according to the vegetative composition and the heterogeneity degree.

In each quadrate, all the arboreal and shrub species were identified. The following measurements were made.

5.2.3 ESTIMATION OF FOREST PRODUCTION OF THORN SCRUB

The forest potential was evaluated by determining the volume of each species per hectare, taking into account of total height, BD, and diameter at breast height (DBH) of all the individuals, also including shoots.

These variables were selected to determine the developmental behavior of individuals, since the proportions between height and diameter, between tree crown size and diameter, between biomass and diameter, usually respond to a general rule, which is the same for all trees that develop under the same environmental conditions, being considered from the smallest to the largest (Archibald and Bond, 2003; Bohlman and O’Brien, 2006; Dietze et al., 2008).

5.2.3.1 DIAMETER AND HEIGHT

The measurement of BD was undertaken at 0.1 m above the soil surface, adopting a standard measurement employee for trees and shrubs of the Tamaulipan thorn scrub, according to Gomez (2000), Alanis et al. (2008a), Jimenez et al. (2012a). This variable was measured, based on the premise that it supports the generation of relationships for the structuring of allometric

FIGURE 5.3 Physiographical provinces of the Nuevo Leon state, Mexico.

equations for the estimation of biomass (Mendez, 2001), calculating from this, the basal area. Both BD and DBH were measured by a calibrator.

The total height as a dendrometric variable (//) forms part of the main interactions for the construction of allometric equations for biomass estimation (Vanclay, 2009).

5.2.32 VOLUME OF WOOD AND CANOPY COVER

The wood volume of each tree was determined according to diameters and total height, applying the formula of Smalian (Moctezuma, 2007) with a morphic coefficient factor of 0.6 (eq. 5.1).

where К is the volume (nr'/lia), D1 and D2 are diameters (cm) of each section (height).

Once the volume was obtained per tree, the mathematical process was carried out to estimate the volume of wood corr esponding to each species.

The canopy coverage generally forms part of principal interactions during the construction of allometric equations for the estimation of biomass so that this variable was also considered for the present study. Canfield (1941) defined canopy cover as the vertical downward projection of foliage or the upper part of the plant over the soil or also the proportion of soil occupied by the aerial part of the plants.

According to this definition, this variable was determined by recording the perpendicular projections of the aerial part of each tree over the soil, according the north-south and east-west directions, with the use of metric tape.

From the classical method of calculating the area of a circle, a method adapted to the scrub was developed to calculate the area occupied by each individual (eq. 5.2). From this, the total area occupied by each species and the relative area (in percentage) in each plot and then per hectare was determined.

where C is the coverage (m2) of each tree, D1 and D2 are diameters (m) of the canopy projections in the north-south and east-west directions.

The floristic diversity of the woody plant was determined by the evaluation of the ecological attributes proposed by Mueller-Dombois and Ellenberg (1974), when applying the four equations of affinity of Sorensen (1948):

where FR is the relative frequency, Fi the frequency of a species, and F the frequency of all the species.

where DR is the relative density, Ni the number of individuals of a species, and N the number of individuals of all the species.

where CD is the relative coverage, Ci the coverage of a species, and C the coverage of all the species.

where VI is the importance value.

52.3.3 STATISTICAL ANALYSIS

The statistical package used for analysis of scrub productivity data was SPSS version 21, the statistics practiced included an analysis of variance to verify significant differences between growth variables and wood volume, with a 95% confidence interval. The Tukey test was used to determine groups of homogeneity between species and between sites for the aforementioned variables, according to Zar (2010). Since the data resulting from the immediate analysis are percentage values, they were transformed with the sum of square function of the p arcsine, where P = a proportion of the dependent variable (Schefler, 1981).

 
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