Water Movement in an Experimental Plot in the Ouachita Mountains of Arkansas: the Effect of Soil Macropores

An experimental forested plot was hydrologically isolated in the ouachita Mountains of Central Arkansas to study the movement of water under simulated rainfall conditions. It was instrumented with (a) four subsurface flow collectors, (b) three sets of tensiometers, (c) six neutron access tubes, (d) six sentry 200 probes, and (e) a rainfall simulator. Lateral subsurface flow rates, soiil water pressure potentials, and soil moisture contents were obtained during seventeen simulated storms for time intervals of 1 to 2 minutes. Due to calibration procedures of the sentry 200 probes and neutron probe, soil moisture contents were not included in this proje~t. The data collected during the course of the study was analyzed to provide evidence of macropore flow based on deviations from potential flow theory. Data analysis, in agreement with field observations, suggested that macropores were actively contributing to subsurface water movement. Lateral macropore space was measured during the installation of the experimental equipment, and estimated from potential flow theory. Macropore and matrix flow were separated with statistical analysis. These findings suggested that modeling water movement should be based on both approaches: potential flow and kinematic wave theory.Environmental Scienc

Diversity-Productivity Relationship in the Northeastern Tamaulipan Thornscrub Forest of Mexico

This research examines the diversity-productivity relationship in a semiarid scrubland, initially under late successional conditions and subsequently under early successional conditions created by experimental clearing, to explore the roles that productivity and stochastic mortality play in species exclusion in this environment. A total of fifteen plots were studied by measuring environmental conditions and biomass components of shrubs and seedlings. These stands were distributed along a productivity gradient across five different landforms. A hypothesis about the stochastic self-thinning mortality model along the gradient was evaluated with the diversity-productivity-environment data. The diversity-productivity relationship was linear and reversed between the early and late succession stages. The hypothesis of stochastic mortality of species exclusion was rejected in the early stages of succession and partially accepted in the mature stage of succession. Species exclusion was negatively related to productivity gradients, suggesting that strong interspecific competition occurs in high productivity plots and that a larger number of species can survive in higher abiotic stress landscapes. Further research is needed to understand the temporal and spatial variations of the ecological interactions that shape this plant community

Biomass estimation equations for mesquite trees in the Americas

Mesquite trees are the preferred dendroenergy sources in arid and semi-arid forests. In spite of their relative importance, regional aboveground biomass (AGB) equations for mesquite trees are scarce in the scientific literature. For that reason, the aims of this study were to: (a) harvest trees and develop regional biomass equations; (b) contrast measured data with equations developed previously; and (c) test the applicability of the fitted equation for mesquite trees in the arid and semi-arid forests of the Americas. We harvested 206 new mesquite trees from arid and semi-arid forests in northern Mexico (Coahuila, Nuevo Leon, and Tamaulipas) in addition to using two other previously compiled data sets from Mexico (N = 304) to develop a regional equation. To test the validity of this equation, for biomass equations reported for the rest of the country, as well as for North and South American mesquite trees, we contrasted AGB measurements with predictions of fitted equations. Statistical analysis revealed the need for a single, regional, semi-empirical equation as together the three data sets represented the variability of the aboveground biomass of mesquite trees across northern Mexico, as well as mesquite trees in America’s arid and semiarid regions. Due to the large quantity of mesquite trees harvested for sampling and their variability, the regional biomass equation developed encompasses all other North and South American equations, and is representative of mesquite trees throughout the arid and semi-arid forests of the Americas

Hydro-Climatic Variability and Perturbations in Mexico\u27s North-Western Temperate Forests

Climate variability and/or climate change control/s the local hydrological cycle and consequently forest perturbations such as wildfires, bark beetle outbreaks and eventually tree and forest die-off. This case study addressed the following concerns: a) the long-term trends in precipitation, P, potential and actual evapotranspiration, E and Et, runoff, Q, soil moisture content, θ, the number of wildfires, No, the burned area, A, and bark beetle outbreaks, BBO and b) the manner in which the fire occurrence, fire size and beetle outbreaks are related to these hydrological variables and multi-decadal climate indices in Mexico\u27s north-western temperate forests.Using daily measurements of P and E as well as the modeled interception loss, I, and Et, runoff, Q, and soil moisture content, θ, were computed using a mass balance budget model. Mann-Kendall, linear regression, and auto-regressive integrated moving averaging, ARIMA, techniques were used to evaluated the statistical significance of monotonic trends on the first momentum for the monthly and annual time series of hydro-climate (1945-2007), forest wildfire (1970-2012), and bark beetle infestation (1999-2012) data. The statistical analysis showed time series to be stationary in the first momentum. Recent wildfires and bark beetle population eruptions are associated with low modeled dry season θ over several years. Drought spells, frosts, and pulses of high area burned,and high number of wildfires preceded acute discrete bark beetle population eruptions and tree die-off

Modeling annual discharge of six Mexico’s northern rivers

The overall goal of this report was to understand river discharge variability to improve conventional water management practices of Mexico’s northern subtropical rivers. This report addresses whether: a) river discharge tendencies, patterns and cycles can be detected with proxy and instrumental records; and b) annual discharge can be forecasted by stochastic models. Eleven gauging stations of six major rivers; three lowland rivers discharging into the Pacific Ocean (Rios Santa Cruz, Acaponeta, and San Pedro); five upland rivers draining into the Pacific Ocean (Rio San Pedro: Peña del Aguila, Refugio Salcido, San Felipe, Vicente Guerrero and Saltito), one river flowing across the interior Basin (Rio Nazas: Salomé Acosta) and two more rivers discharging into the Northern Gulf of Mexico (Rio San Juan: El Cuchillo and Rio Ramos: Pablillos) were statistically analyzed. Instrumental recorded daily discharge data (1940-1999) and reconstructed time series data (1860-1940) using dendrochronological analysis delivered annual discharge data to be modeled using autoregressive integrated moving average, ARIMA models. Spectral density analysis, autocorrelation functions and the standardized annual discharge data evaluated annual discharge frequency cycles. Results showed ARIMA models with two autoregressive and one moving average coefficient adequately project river discharge for all gauging stations with four of them showing significant declining patterns since 1860. ARIMA models in combination with autocorrelation and spectral density techniques as well as standardized departures, in agreement with present (2002-2010) observations, forecast a wet episode that may last between 9 and 12 years thereafter entering again into a dry episode. Three dry-wet spell cycles with different time scales (1-2 years; 4-7 years; 9-12 years) could be discerned from these analyses that are consistent for all three northern Mexico’s river clusters that emerged from a multivariate analysis test

ALLOMETRIC EQUATIONS AND EXPANSION FACTORS FOR TROPICAL DRY TREES OF EASTERN SINALOA, MEXICO

This research report aimed at estimating: (i) bole volume equations, (ii) aboveground biomass component equations, and (iii) biomass expansion factors, BEF, for aboveground biomass components for tropical dry trees of eastern Sinaloa, Mexico. Field work included measuring dasometric features, dissecting and fresh-weighting trees into biomass components, and collecting samples for ovendry weight measurements. Bole volume and biomass component equations fitted an inventory data set to estimate biomass expansion factors at the plot scale. Results show bole volume and biomass component equations. Mean biomass expansion factors (± standard deviation) reported are 0.7854 (0.111), 0.873 (0.055) and 1.460 (0.022) for branches, bole and total aboveground biomass, respectively. Biomass expansion factors are dependent on mean stand dbh and they do not distribute normally. Therefore the Weibull distribution was fitted to biomass expansion figures

THE SPATIAL DISTRIBUTION OF ABOVEGROUND BIOMASS IN TROPICAL FORESTS OF MEXICO

Biomass stocks and their spatial distribution remain poorly understood in tropical forests and reliable estimations are critical in the calculations of carbon stocks and fluxes. This report aims to estimate and contrast aboveground biomass stocks, AGB, in tropical forests of Mexico by employing three different evaluation techniques. Mexican tropical forests were classified as dry, moist and rainy. The first method uses a simple mean biomass density value per each forest class times the area of each forest. The second approach improves the spatial resolution by classifiying forests per each region and a mean biomass density is multiplied by the area of each forest class. The third methodology calculates biomass stocks by developing an empirical model using mean annual precipitation as the independent variable and then the equation is applied to the mean annual rainfall of each tropical forest times the area of the forest. Results showed that all three methods of aboveground biomass stock estimations are quite consistent since they have mean (confidence interval) values of 2.65 (0.74), 2.67 (0.68), and 2.08 (0.85) Pg estimated by approaches 1, 2, and 3, respectively. Deviations between evaluation methodologies did not surpass 0.33 Pg or 14% of the mean aboveground biomass stock. Using all three statistics, mean (confidence interval) aboveground biomass stocks for Mexican tropical forests is 2.46 (0.76) Pg. This statistic deviates by more than one order of magnitude when contrasting it with other six independent AGB estimates. However, the mean figure reported in this study or a mean AGB calculated across all estimation methods provides a dataset that is important for conducting carbon stocks and fluxes for Mexican tropical forests

ROOT ALLOMETRY OF TWO SUBTROPICAL PLANT COMMUNITIES OF NORTHEASTERN MEXICO

This research work aimed at the study of the root allometry in subtropical Tamaulipan thornscrub and pine forest communities of Nuevo Leon, Mexico. By excavating each individual root of each of 20 trees per plant community, we developed root allometric equations for biomass, volume, total length and diameter. Covariance analysis, ancova, was employed to determine the statistical difference of these parameters between plant communities. Results indicate that pine plant trees have larger root volumes, longer root systems and higher root basic densities than trees of Tamaulipan thornscrub forests. This piece of information is key to estimate root biomass, volume, total length and diameter of roots of trees of these plant communities at the stand scale; important environmental information.Key words: Power equations, ancova, root biomass, volume, length and diameter

FITTING AND TESTING ALLOMETRIC EQUATIONS FOR MEXICO’S SINALOAN TROPICAL DRY TREES AND FOREST INVENTORY PLOTS

Aboveground tree biomass (bole, branches and foliage), M, plays a key role in the conventional and sustainable management of forest communities. The standard approach to assess tree or plot M is harvesting trees, developing and fitting allometric equations to trees or forest inventory plot data. In the absence of local tree allometry, it is usually recommended to fit off site allometric equations to evaluate tree or plot M. This research aims: (a) to develop an updated on site allometric equation (b) to fit available off site allometric equations to destructively harvested trees and (c) to fit available allometric equations to plot M of Mexico’s Sinaloan tropical dry forests to understand sources of inherent tree and plot M variability. Results showed that: (a) the improved on site allometric equation increases precision in contrast to the conventional biomass equation previously reported as well as to off site tree M equations, (b) off site allometry projects tree and plot M deviates by close to one order of magnitude. Two tested and recommended approaches to increase tree and plot M precision when fitting off site equations are: (i) to use all available tree allometric functions to come up with a mean equation or (ii) to calibrate off site equations by fitting new, local parameters that can be calculated using statistical programs.These options would eventually increase tree and plot M precision in regional evaluations