A previously unreported bacterial disease on chili pepper (Capsicum annuum L.) seedlings affecting as many as 4% of seedlings was observed in greenhouses in Chihuahua, Mexico (Delicias and Meoqui counties). Initial lesions appeared as irregular small spots on leaves and brown necrosis at margins tips were observed. Later, the spots became necrotic with a chlorotic halo. Advanced disease was associated with defoliation. A Gram negative, rod-shaped bacterium was isolated from diseased chili pepper seedlings. Three inoculation methods revealed that isolated strains produce foliage symptoms, similar to those observed in naturally infected seedlings. Pathogenic strains that caused symptoms in inoculated seedlings were re-isolated and identified to fulfill koch's postulate. Polyphasic approaches for identification including biochemical assays (API 20E and 50CH), carbon source utilization profiling (Biolog) and 16S rDNA, hsp60 and rpoB sequence analysis were done. Enterobacter cloacae was identified as the causal agent of this outbreak on chili pepper seedlings.
One of the fastest-growing renewable energy sources is solar energy. A strategic step for a well-performing solar project is site identification. The evaluation of site-suitability is a complex task, where multiple qualitative and quantitative criteria, inherent to the territory, are involved. In this study, a GIS-based multi-criteria decision-making (MCDM) methodology for site-suitability evaluation in the development of solar farms (DSF) is presented. Two scenarios, the ranking method (RM) and the Analytical Hierarchy Process (AHP), each representing a different weighting approach, were tested. A case study was performed for the Desert of Chihuahua, Mexico, a region with the potential to provide a significant portion of the country’s energy demand. The RM was more stringent and identified less area with high suitability (1237 km2) compared to the AHP (4983 km2). Given its flexibility in assigning weights, the AHP is considered to have greater potential in identifying site-suitability levels. The final suitability maps of the AHP showed the northern part of the study region to have high suitability for the DSF. Thus, sites in this area could be used for the construction of solar energy projects in the future. This methodology provides a useful tool for land-use planning based on its suitability level.
This study developed a GIS-based framework for the zoning of land suitability for grassland conservation (LSGC) in the Central Valleys of Chihuahua, México. For that, a Geographic Information Systems (GIS)-based multicriteria evaluation techniques with weighted overlay (MCE-WO), and a fragmentation analysis were performed. The framework for LSGC consisted in the development of four scenarios: Nonintensive Agriculture, Intensive Agriculture, Urban, and Rural. The LSGC classes defined with the MCE-WO technique were: Very high, High, Moderate, Low, and Very low land suitability. Results showed that the zone with a high suitability covered the largest area in the four scenarios with a surface of 44,264 km2. The zones with low and very low suitability were concentrated mainly in the central region of the study area. At the landscape level, fragmentation of LSGC showed the Nonintensive Agriculture and the Rural scenarios with the highest Number of patches (54,640 and 46,210, respectively). The fragmentation of LSGC, under the scenarios evaluated, was mainly due to land opening for agriculture and to the influence of rural communities. The integration of GIS with MCE-WO is useful and effective for the evaluation of LSGC. This tool can provide a solid source of information for decision-makers regarding planning of land use to mitigate grasslands degradation.
The temperate forests of northern Mexico possess a great diversity of unique and endemic species, with the greatest associations of pine-oak in the planet occurring within them. However, the ecosystems in this region had experienced an accelerated fragmentation process in the past decades. This study described and quantified the landscape fragmentation level of a degraded watershed located in this region. For that, data from the Landsat series from 1990, 2005 and 2017, classified with the Support Vector Machine method, were used. The landscape structure was analyzed based on six metrics applied at both, the landscape and class levels. Results show considerable gains in surface area for the land use land cover change (LULC) of secondary forest while the Primary Forest (PF) lost 18.1% of its area during 1990–2017. The PF increased its number of patches from 7075 to 12,318, increased its patch density (PD) from 53.51 to 58.46 # of patches/100 ha, and reduced its average patch size from 39.21 to 15.05 ha. This made the PF the most fragmented LULC from the 5 LULCs evaluated. In this study, strong fluctuations in edge density and PD were registered, which indicates the forests of northern Mexico have experienced a reduction in their productivity and have been subjected to a continuous degradation process due to disturbances such as fires, clandestine and non-properly controlled logging, among others.
In this study, the transitions of land use that occurred in the urban and peripheral areas of Chihuahua City, Mexico, were determined for the period 1989–2014. Landsat TM and OLI scenes, as well as the method of Markov Chains (MC) were used. Grasslands and Shrublands were the land uses that experienced the highest pressures for land use. Grasslands occupied 23.5% of the area in 1989, decreasing to 16.01% in 2014. Likewise, Shrublands were reduced from 54.53% to 48.06%. The areas occupied by Croplands, Oak forest, Water bodies and Riparian vegetation stayed in general constant. In contrast, the urban area increased from 13.6% to 28.6% of the total area studied. In addition, projections of land use for 2019 and 2024 were generated through the method of MC and Cellular Automata (CA). According to the projections, validated with an agreement of 0.90, the Human settlements would continue to expand, occupying 38.57% by 2019 and almost half of the studied territory (47.33%) by 2024. The ecosystems with the highest pressure for land use change will continue to be the Grasslands and Shrublands. By 2024, the former would lose 15.8% while the latter would lose 16.7% of the area. These methods are valuable for urban planning and the results could support growth plans for Chihuahua City, Mexico, with a sustainable approach.