Ecological restoration is an essential strategy for mitigating the current biodiversity crisis, yet restoration actions are costly. We used systematic conservation planning principles to design an approach that prioritizes restoration sites for birds and tested it in a riparian forest restoration program in the Colorado River Delta. Restoration goals were to maximize the abundance and diversity of 15 priority birds with a variety of habitat preferences. We built abundance models for priority birds based on the current landscape, and predicted bird distributions and relative abundances under a scenario of complete riparian forest restoration throughout our study area. Then, we used Zonation conservation planning software to rank this restored landscape based on core areas for all priority birds. The locations with the highest ranks represented the highest priorities for restoration and were located throughout the river reach. We optimized how much of the available landscape to restore by simulating restoration of the top 10–90% of ranked sites in 10% intervals. We found that total diversity was maximized when 40% of the landscape was restored, and mean relative abundance was maximized when 80% of the landscape was restored. The results suggest that complete restoration is not optimal for this community of priority birds and restoration of approximately 60% of the landscape would provide a balance between maximum relative abundance and diversity. Subsequent planning efforts will combine our results with an assessment of restoration costs to provide further decision support for the restoration-siting process. Our approach can be applied to any landscape-scale restoration program to improve the return on investment of limited economic resources for restoration.

Groundwater is an important water source in Arizona, accounting for about 41% of water use in this mostly arid-to-semiarid state in the southwestern United States, and the availability of groundwater resources in the state is a concern. To provide accessible information from depth-to-groundwater data, a series of web-based interactive maps were developed, called the Arizona Groundwater Explorer (AGEx). Scripts were written to harmonize and synthesize groundwater datasets from the two largest publicly available sources, subset these data to address different groundwater availability questions, and display the results in online, interactive maps. The combined dataset contained 1,820,122 depth-to-groundwater measurements from 1891 through 2022 from 41,918 wells in Arizona. Data views are provided for 20 topics, including recent (2020 or later) depth to groundwater (4,569 wells), historical (pre-1950) depth to groundwater (4,287 wells), wells with long-term (≥50 years) records (1,183 wells), wells with recent groundwater level decline (277 wells), wells with recent groundwater level rise (120 wells), and linear trends in groundwater levels over ten 10-year periods (number of wells ranging from 341 in 1978–1987 to 1,208 in 2003–2012), among others. With ongoing drought in the region resulting in declining surface-water supplies in Arizona, groundwater may play an even larger role in satisfying water needs in the state. The AGEx series of maps provides a nonspecialist audience with an improved understanding of historical, current, and changes in groundwater levels in Arizona.

This study integrates results from previous studies with new reconnaissance-scale mapping of rock types, structures, and hydrothermal alteration at Goat Ridge and Tenabo to provide a district-scale cross section and palinspastic restoration of an area in Nevada with high potential for Carlin-type mineralization in the footwall of a dismembered thrust fault. Reinterpretation of legacy drill data in light of recent advances in the understanding of Cenozoic normal faulting in the area with the expected stratigraphy of the Roberts Mountains autochthon allows for deciphering whether previous drill holes piercements of faults are the Roberts Mountains thrust or are tilted normal faults that down-dropped the deep-water siliciclastic rocks of Roberts Mountains allochthon onto the coeval carbonate rocks of the Roberts Mountains autochthon. A cross-sectional reconstruction shows that ∼11.1 km (120 %) of extension was accomplished along one set of faults that initiated at 60-70°and tilted 40°E. Previously underappreciated Mesozoic folds are present, which likely formed with horizontal fold hinges. Because of Cenozoic normal faulting and associated tilting, the hinge lines currently plunge at moderate angles and are offset as they step across each crosscutting fault. The anticlinal fold hinges produced the modern exposures of lower plate rocks in the range. The Eocene paleogeologic map that results from a plan-view structural restoration shows that the hinge lines of the original folds trended northwest-southeast in the southern half of the range but turned northward toward the northern end of the range.Mineralization in the range includes silver-dominated polymetallic veins/lodes, weak porphyry-type, Carlin-type, and siliciclastic-hosted gold deposits of uncertain origin. Porphyry-style and silver-dominated polymetallic vein mineralization is associated with ∼39–40 Ma granodiorites, with the silver-dominated polymetallic veins interpreted as the distal veins around weakly mineralized and/or deeply buried porphyry system(s), probably of the quartz monzonitic-granitic porphyry Mo-Cu subclass of porphyry molybdenum deposits. Crosscutting relationships demonstrate that at least one of “upper plate” gold deposits is Eocene, but a Miocene age cannot be ruled out for the other gold deposits.

Energy consumption represents a significant operating expense in the mining and minerals industry. Grinding accounts for more than half of the mining sector’s total energy usage, where the semi-autogenous grinding (SAG) circuits are one of the main components. The implementation of control and automation strategies that can achieve production objectives along with energy efficiency is a common goal in concentrator plants. However, designing such controls requires a proper understanding of process dynamics, which are highly complex, coupled, and have non-deterministic components. This complex and non-deterministic nature makes it difficult maintain a set-point for control purposes, and hence operations focus on an optimal control region, which is defined in terms of desirable behavior. This paper investigates the feasibility of employing machine learning models to delineate distinct operational regions within in an SAG mill that can be used in advanced process control implementations to enhance productivity or energy efficiency. For this purpose, two approaches, namely k-means and self-organizing maps, were evaluated. Our results show that it is possible to identify operational regions delimited as clusters with consistent results.

We conducted a population genomic study of the crested caracara (Caracara plancus) using samples (n = 290) collected from individuals in Florida, Texas, and Arizona, United States. Crested caracaras are non-migratory raptors ranging from the southern tip of South America to the southern United States, including a federally protected relict population in Florida long thought to have been isolated since the last ice age. Our objectives were to evaluate genetic diversity and population structure of Florida's apparently isolated population and to evaluate taxonomic relationships of crested caracaras at the northern edge of their range. Using DNA purified from blood samples, we conducted double-digest restriction site associated DNA sequencing and sequenced the mitochondrial ND2 gene. Analyses of population structure using over 9,000 SNPs suggest that two major clusters are best supported, one cluster including only Florida individuals and the other cluster including Arizona and Texas individuals. Both SNPs and mitochondrial haplotypes reveal the Florida population to be highly differentiated genetically from Arizona and Texas populations, whereas, Arizona and Texas populations are moderately differentiated from each other. The Florida population's mitochondrial haplotypes form a separate monophyletic group, while Arizona and Texas populations share mitochondrial haplotypes. Results of this study provide substantial genetic evidence that Florida's crested caracaras have experienced long-term isolation from caracaras in Arizona and Texas and thus, represent a distinct evolutionary lineage possibly warranting distinction as an Evolutionarily Significant Unit (ESU) or subspecies. This study will inform conservation strategies focused on long-term survival of Florida's distinct, panmictic population.

ABSTRACT Numerous studies have evaluated the application of Remote Sensing (RS) techniques for mapping actual evapotranspiration (ETa) using Vegetation-Index-based (VI-based) and surface energy balance methods (SEB). SEB models computationally require a large effort for application. VI-based methods are fast and easy to apply and could therefore potentially be applied at high resolution; however, the accuracy of VI-based methods in comparison to SEB-based models remains unclear. We tested the ETa computed with the modified 2-band Enhanced Vegetation Index (METEVI2) implemented in the Google Earth Engine – for mapping croplands’ water use dynamics in the Lower Colorado River Basin. We compared METEVI2 with the well-established RS-based products of OpenET (Ensemble, eeMETRIC, SSEBop, SIMS, PT_JPL, DisALEXI and geeSEBAL). METEVI2 was then evaluated with measured ETa from four wheat fields (2017–2018). Results indicated that the monthly ETa variations for METEVI2 and OpenET models were comparable, though of varying magnitudes. On average, METEVI2 had the lowest difference rate from the average observed ETa with 17 mm underestimation, while SIMS had the highest difference rate (82 mm). Findings show that METEVI2 is a cost-effective ETa mapping tool in drylands to track crop water use. Future studies should test METEVI2’s applicability to croplands in more humid regions.