Fire modifies vegetation dynamics in terrestrial ecosystems. Abundant literature has studied the post-fire effects with satellite sensors; however, relatively fewer studies have used unmanned aerial vehicles (UAVs) to assess the dynamics of greenness prior to and immediately following prescribed fires. Using multispectral sensors mounted on UAVs, we documented the results of the normalized difference vegetation index (NDVI) as a proxy for pre- and post-fire greenness in a natural forest stand in northern Mexico. Using spectral reflectance techniques and the statistical analyses of Kruskal–Wallis and pairwise Wilcoxon rank-sum tests, statistically significant differences were found in the NDVI values, measured before and after controlled burning (p < 0.05). The results showed an increase in post-fire “greenness” from 0.57 to 0.65. This was interpreted as an immediate change in vegetation activity in the canopy, which could be attributable as a stimulus to heat stress. Complementary spectral indices also reinforce our findings; we recognize that further research is required, for instance, to address the timing of image capture. Our findings demonstrate the potential and some of the challenges associated with the use of UAVs to monitor prescribed fires, while also suggesting the need for more detailed physiological and phenological studies. High spatial and spectral resolution maps of greenness represent a valuable starting point for subsequent temporal monitoring and contribute to the knowledge of fire effects at fine spatial resolutions.

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.

A pilot-scale aerated lagoon was used for the aerobic treatment of pulp and paper mill effluent from September 1 to December 1, 2014. The aerated lagoon was installed at the chemistry laboratory in the Chemical Engineering Department at the Durango Institute of Technology and was fed with real pulp and paper mill effluent. The experimental work was run under various operating conditions. The operating parameters (total and volatile suspended solids (VSS) and dissolved oxygen concentration (DO)) and environmental variables (temperature, pH, COD, and BOD5 of influent water) were monitored daily. In all the experiments conducted, the aerated lagoon generated an effluent of optimal quality complying with the requirements of SEMARNAT (2003) and CONAGUA (2003). A model that explains the behavior of the system under realistic operating conditions was obtained. The model indicated an optimal DO of approximately 4 mg/L for concentrations up to 1000 mg/L, showing variations in concentrations above this value. This data indicate that the flexibility of the bacterial formulation and its ability to adapt to environmental changes play an important role in the stability of an aerated lagoon.

This study estimated biometric attributes of individual trees from the automated measurement of tree height (THUV) by using images from unmanned aerial vehicles (UAVs). An experiment was carried out in a natural forest stand in the north of Mexico by using a DJI P4 multispectral equipment and regression analysis. The results show that total tree height (TH) is successfully estimated from UAV images, as the automated estimation of total height (THUV) reaches a R2 = 0,95 and a RMSE = 0,36 m. Consequently, THUV was statistically reliable to generate allometric equations (R2 > 0,57) regarding the canopy height model (CH), diameter at breast height (DBH), basal diameter (BD), above-ground biomass (AGB), volume (V), and carbon contents (C). It is concluded that the estimation of total height with UAVs is a viable option to improve efficiency in forest inventories. However, increased efforts towards the configuration of modern technologies and statistical algorithms are needed; future research challenges remain, particularly in the densest forests areas.

NDVI elucidates the ecophysiological mechanisms faced by vegetation. With the flexibility and versatility of unmanned aerial vehicles (UAVs), temporal, spatial and spectral resolutions have been useful in supporting decision-making. Here, we modeled diurnal change in the NDVI derived from UAV imagery for individual trees in a natural forest stand. Eight flights were conducted during daylight hours over one day to assess the dynamics of the NDVI of the genera Pinus, Juniperus, and Quercus. The results showed unstable NDVI values over time, with a parabolic quadratic trend in the model. The NDVI reached its maximum around 13:00 h and the values differed significantly according to genus: the highest value was found in Pinus with significant differences presented with Juniperus and Quercus, which showed similar values between them (p=0.533). As a validation strategy, we test the model generated using 124 trees independent of those that were sampled, which strengthened our results in terms of reliability. The similarities of statistical parameters confer a high variability of application of the results in models of simulation of similar forests ecosystems. We recommend to study more spectral indices of vegetation, including calibration of the sensor, particularly in longer-term seasonal studies. We conclude that the NDVI measured using UAV should consider image acquisition time to calibrate the records and thus improve the interpretation of results.