Search Results (8)

A variety of statistical techniques were assessed for their usefulness for analysing the pattern of geographical and temporal changes in groundwater levels in order to diagnose the water supply in Meoqui, Chihuahua, which is situated in dry North-Central Mexico. These included Facebook Prophet, Lasso, generalized linear regularized models (GLMNET), autoregressive-integrated moving average (ARIMA), and a hybrid approach that merged Prophet and XGBoost. This was conducted on the assumption that the levels varied during the year and that it was possible to perform statistical analyses that derived a model explaining the changes and allowing for spatiotemporal prediction. The data set encompassed the period between 2020 and 2025 and was obtained from the Junta Municipal de Aguas y Saneamiento (JMAS) in Meoqui. The data set consisted of eight wells from which water was extracted for human consumption. The ARIMA model was identified as the optimal method for generating predictions on a monthly and annual basis. Furthermore, an inverse distance weighted (IDW) interpolation approach was utilised to conduct a spatial analysis. This enabled the visualisation of the predicted spatiotemporal changes in groundwater levels. The mean overall level was determined to be 26 m ± 16, with a minimum of 3 m and a lower level of 64 m. Models were estimated, comprising a general model and models specific to each well type. The best model for general level was Facebook Prophet (MAE 6.31, MAPE 16.28, MASE 1.23, SMAPE 16.79, RMSE 7.25, R-sq 0.29). The Sen’s slope of the historic level was found to be 0.38 (p < 0.001), thus indicating a decline in the groundwater level. The spatiotemporal analysis indicated a monthly decline in water levels from February to August, followed by an improvement in levels until November, which were then maintained until January. The lowest levels were observed in the area associated with Well 5. The findings of this study offer valuable insights into the spatiotemporal patterns of groundwater in the region, which could inform the development of sustainable groundwater management policies. Full article

The reliance on imported seeds for grassland rehabilitation in Mexico has led to increased costs and other difficulties in implementing grassland rehabilitation programs. Varieties need to be generated from local ecotypes that are outstanding in forage production and their response to rehabilitation programs. However, the scarcity of occurrence records is often a deterrent to niche and distribution modeling, hence the need for an approach that overcomes such limitations. The objectives of this study were (1) to develop a geographic information system (GIS)-based approach to determining the population distribution of a promising ecotype of Bouteloua curtipendula (Michx.) Torr. for grassland rehabilitation in the Chihuahuan Desert, Mexico; (2) to identify the edaphoclimatic variables that define the ecotype’s distribution; and (3) to develop models to determine the potential area for the use of the ecotype in grassland rehabilitation. The challenge for the present study was that only one georeferenced collection site of the ecotype in Chihuahua was available for use in the construction and calibration of the models. GIS software 10.3 was used to develop two potential distribution models: Model A, with variables obtained directly from a vector climate dataset, and Model B, with derived variables. A field work methodology was developed for the validation process using a georeferenced digital mesh and the nested sampling method modified by Whittaker. The information was analyzed with 10 non-parametric statistical tests. The two models had an overall accuracy and sensitivity level greater than 70% and a positive predictive power greater than 80%. The predicted population distribution areas in Chihuahua (18,158 ha) in the form of discontinuous patches cohered with those in previous reports on the distribution form of B. curtipendula. The edaphoclimatic variables influencing ecotype distribution were soil type, average minimum and maximum temperature in January, average maximum temperature in June, average minimum temperature in July, and average precipitation in August. The sensitivity analysis showed soil type as an important variable in defining the ecotype’s distribution. Considering soil as the main predictor variable, the potential rehabilitation area where the ecotype may be used was estimated at 7,181,735 ha in the Chihuahuan Desert region. The study developed and validated an approach to modeling the ecological niche of an ecotype of commercial interest, despite severe limitations in the number of georeferenced sites available for modeling. Further study is needed to explore its applicability to grassland rehabilitation in the Chihuahuan Desert and the study of rare and understudied ecotypes or species in other settings. Full article

Rarámuri Criollo (RC) cattle have been raised by the isolated Tarahumara communities of Chihuahua, Mexico, for nearly 500 years, mostly under natural selection and minimal management. RC cattle were introduced to the United States Department of Agriculture-Agricultural Research Service Jornada Experimental Range (RCJER) in 2005 to begin evaluations of beef production performance and their adaptation to the harsh ecological and climatic conditions of the Northern Chihuahuan Desert. While this research unveiled crucial information on their phenotypic plasticity and adaptation, the genetic diversity and structure of the RCJER population remains poorly understood. This study analyzed the genetic diversity, population structure, ancestral composition, and selection signatures of the RCJER herd using a ~64 K SNP array. The RCJER herd exhibits moderate genetic diversity and low population stratification with no evident clustering, suggesting a shared genetic background among different subfamilies. Admixture analysis revealed the RCJER herd represents a distinctive genetic pool within the Criollo cattle breeds, with significant Iberian ancestry. Selection signatures identified candidate genes and quantitative trait loci (QTL) for traits associated with milk composition, growth, meat and carcass, reproduction, metabolic homeostasis, health, and coat color. The RCJER population represents a distinctive genetic resource adapted to harsh environmental conditions while maintaining productive and reproductive attributes. These findings are crucial to ensuring the long-term genetic conservation of the RCJER and their strategic expansion into locally adapted beef production systems in the USA. Full article

The Chihuahuan Desert biogeographic province in Mexico is the largest of the fourteen biogeographic provinces of the country. This biogeographic province hosts a diverse array of amphibian and reptile species, with 262 native species, including 53 amphibians and 209 reptiles, accounting for a significant portion of Mexico’s total amphibian (~12%) and reptile diversity (~21%). The Zacatecana subprovince exhibits the highest concentration of species for both groups (89% and 50% of Chihuahuan Desert amphibians and reptiles, respectively), indicating its importance for biodiversity within the Chihuahuan Desert. Comparative analyses with neighboring biogeographic provinces reveal substantial species overlap (48–55%), particularly with the Sierra Madre Oriental, the Transvolcanic Belt, and the Sierra Madre Occidental. These findings suggest strong ecological connections and corridors facilitating species exchange among these regions. Conservation assessments highlight the vulnerability of many species in the Chihuahuan Desert, with a notable percentage listed in the International Union for Conservation of Nature’s (IUCN) Red List (~12%) and higher percentages categorized by the Mexican government as at risk according to their conservation status and the Environmental Vulnerability Score (~40%). Threats primarily stem from habitat loss, pollution, and other anthropogenic factors. In conclusion, the Chihuahua Desert emerges as a biogeographic province of significant biological richness and valuable evolutionary history for amphibians and reptiles. Its conservation is imperative for safeguarding the distinctive species and ecosystems that characterize this desert biome. Full article

This study highlights the importance of quantifying groundwater resources for the Monahans and Kermit dune fields in the northern Chihuahua Desert, West Texas, USA, as potential contributors to the regional Pecos Valley Aquifer (PVA). Dunal aquifers in arid environments are often unquantified, may augment regional groundwater resources, and can be compromised by anthropogenic activity. Sedimentary architecture models of these dune fields show perched aquifers with water tables 1–10 m below the surface and southwestern groundwater flow sub-parallel to a Pleistocene/Pliocene aquitard. The deuterium and oxygen isotopic ratios for groundwater from the Kermit and Monahans dune fields show pronounced evaporative isotopic depletion and less isotopic variability than corresponding rainfall, particularly for deuterium values. The radiocarbon and δ¹³C analyses of dissolved inorganic carbon (DIC) indicate that recharge occurs through enhanced capture of recent precipitation on mostly bare active dunes where infiltration rates are >250 mm/h. In contrast, more evolved ¹⁴C values at the western margin (FM = 0.84) and at 30 m below the surface (FM = 0.76) of the dunes, similar to proximal Fm values from the PVA (0.89–0.82), may indicate dissolution of older (>100 ka) DIC from buried playa-lake sediments and less direct atmospheric influence. Mixing models for DIC source partitioning highlighted possible groundwater contamination with hydrocarbon up to 24% in the PVA and in the dunal aquifers. The perched aquifers of the Monahans and Kermit dune fields each contain water volumes >0.1 km³ and may contribute up to 18% of the total annual recharge to the PVA. Full article

Sotol (Dasylirion leiophyllum) grows in the Chihuahan Desert in the north of Mexico and south of the United States. The stem of this species is used to produce a liquor widely known as sotol. A field sampling and a laboratory analysis were carried out to determine the influence of the rainy season, altitude, topography, and aspect over the soluble solid content (°Brix) and bromatological variables of mature plants of sotol in Chihuahua, Mexico. Analyses of variance and Tukey tests were performed. The rainy season and altitude showed significant statistical influence (p ≤ 0.05) on the total soluble solids content; meanwhile, only altitude showed a significant effect on the bromatological variables (p ≤ 0.05). According to the results of the Tukey tests (p < 0.05), sotol plants have the highest concentrations of soluble solid contents before the rainy season (25 °Brix) and at sites with altitudes lower than 1300 m (25.95 °Brix). In addition, the means of raw protein and carbohydrates content were the highest in plants living at altitudes lower than 1500 m, at 1.93% and 31.74%, respectively. Meanwhile, topography, aspect, and the interactions of the evaluated factors did not show significant influence (p ≤ 0.05) over the total soluble solid content, nor over the bromatological variables studied. Full article

Rangelands provide significant socioeconomic and environmental benefits to humans. However, climate variability and anthropogenic drivers can negatively impact rangeland productivity. The main goal of this study was to investigate structural and productivity changes in rangeland ecosystems in New Mexico (NM), in the southwestern United States of America during the 1984–2015 period. This goal was achieved by applying the time series segmented residual trend analysis (TSS-RESTREND) method, using datasets of the normalized difference vegetation index (NDVI) from the Global Inventory Modeling and Mapping Studies and precipitation from Parameter elevation Regressions on Independent Slopes Model (PRISM), and developing an assessment framework. The results indicated that about 17.6% and 12.8% of NM experienced a decrease and an increase in productivity, respectively. More than half of the state (55.6%) had insignificant change productivity, 10.8% was classified as indeterminant, and 3.2% was considered as agriculture. A decrease in productivity was observed in 2.2%, 4.5%, and 1.7% of NM’s grassland, shrubland, and ever green forest land cover classes, respectively. Significant decrease in productivity was observed in the northeastern and southeastern quadrants of NM while significant increase was observed in northwestern, southwestern, and a small portion of the southeastern quadrants. The timing of detected breakpoints coincided with some of NM’s drought events as indicated by the self-calibrated Palmar Drought Severity Index as their number increased since 2000s following a similar increase in drought severity. Some breakpoints were concurrent with some fire events. The combination of these two types of disturbances can partly explain the emergence of breakpoints with degradation in productivity. Using the breakpoint assessment framework developed in this study, the observed degradation based on the TSS-RESTREND showed only 55% agreement with the Rangeland Productivity Monitoring Service (RPMS) data. There was an agreement between the TSS-RESTREND and RPMS on the occurrence of significant degradation in productivity over the grasslands and shrublands within the Arizona/NM Tablelands and in the Chihuahua Desert ecoregions, respectively. This assessment of NM’s vegetation productivity is critical to support the decision-making process for rangeland management; address challenges related to the sustainability of forage supply and livestock production; conserve the biodiversity of rangelands ecosystems; and increase their resilience. Future analysis should consider the effects of rising temperatures and drought on rangeland degradation and productivity. Full article

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. Full article