High Plains Research Articles

Influence of Climate Warming on the Ground Surface Stability over Permafrost along the Qinghai–Tibet Engineering Corridor

The warming climate has posed a serious threat on ground surface stability. In permafrost regions, ground surface instability may induce engineering and geological disasters, especially for the engineering corridor. It is difficult to evaluate ground surface stability over permafrost because the stability is influenced by various factors in permafrost regions. Many single index models cannot comprehensively evaluate the ground surface stability for permafrost. We, therefore, proposed an evaluation model considering different influential factors based on the trapezoidal fuzzy Analytical Hierarchy Process (AHP) method. And the ground surface stability was calculated and analyzed along the Qinghai–Tibet Engineering Corridor under three climate warming conditions (the slow climate warming, the medium climate warming and the rapid climate warming). The results show that the ground surface stability influential factors, including the mean annual ground temperature, the active layer thickness, and the volume ice content, will be greatly changed with the warming climate. By 2100, the percentage of high-temperature permafrost (−0.5 °C < T ≤ 0 °C) will increase about 29.45% with rapid climate warming. The active layer thickness will have an average thickening rate of about 0.030 m/year. Most of the high ice content permafrost will change to low ice content permafrost. The ground surface stability, therefore, will be greatly changed with the warming climate along the Qinghai–Tibet Engineering Corridor. Compared to the present, the stable area will decrease about 5.28% by 2050 under the slow climate warming. And that is approximately 7.91% and 21.78% under the medium and rapid climate warming, respectively. While in year 2100, the decrement is obviously increased. The stable area will decrease about 11.22% under the slow climate warming and about 17.3% under the medium climate warming. The proportion of stable area, however, has an increasing trend under the rapid climate warming. This phenomenon is mainly caused by the warming climate which can lead to the permafrost being degraded to melting soil. The unstable area is mainly distributed near the Chumaer River high plain, Tuotuohe–Yanshiping, Wudaoliang, Tangula Mountains, and other high-temperature permafrost areas. This paper provides a reference for geological hazard prevention and engineering construction along the Qinghai–Tibet Engineering Corridor.

Experimental study on creep behavior of high-strength concrete filled steel tubular (HSCFST) columns

The use of High Strength Concrete Filled Steel Tube (HSCFST) members has become widespread, but there is limited research on their creep behavior. This study examines the creep and shrinkage characteristics of HSCFST columns subjected to axial loading by testing fifteen specimens with various steel ratios over a period of 365 days. The experimental data is then compared to the predictions made by the creep prediction models MC 90, ACI 209, and AFREM. The results indicate that the creep coefficients of HSCFST specimens are significantly lower than those of plain concrete specimens. By the end of 365 days, the creep coefficient of plain concrete is more than twice that of concrete in HSCFST. The steel ratio has a slight effect on the creep of CFST specimens, with the creep coefficient decreasing as the steel ratio increases. The comparison of the results shows that the MC 90 and ACI 209 models overestimate the creep of concrete, while the AFREM model underestimates it. Furthermore, the ACI 209 model is modified based on the experimental results by applying a correction factor of concrete strength, which significantly improves its accuracy and makes it suitable for predicting the creep of high strength plain concrete and HSCFST.

USEPA CALPUFF validation and dispersion modeling of beef cattle feedlot PM10 and PM2.5 emissions factors

Beef cattle feedlots are major sources of criteria air pollutants in the United States. To aid stakeholders in air quality modeling, emissions factors for animal waste-producing facilities are under development by the U.S. Environmental Protection Agency (USEPA). However, beef cattle feeding operations (feedlots) are not among facilities surveyed under the associated USEPA National Air Emissions Monitoring Study (NAEMS). Authors aim to supplement NAEMS through development and validation of particulate matter (PM10 and PM2.5) emission factors from a previous sampling campaign of five large feedlots in the Southern High Plains of North America via USEPA's CALPUFF dispersion model. PM concentrations were higher overall during the warm season (March–August; PM10 = 692 ± 507, PM2.5 = 114 ± 110 μg/m3) relative to cool season (November–January; PM10 = 102 ± 105, PM2.5 = 12.2 ± 8.6 μg/m3), and overall median PM10 and PM2.5 emission factors were 48.2 (day = 33.8, night = 72.4) and 5.22 (day = 8.4, night = 3.1) mg/m2/hr, respectively. Validated emissions factors were then used to model diurnal peaks and long-range transport (100 km maximum extent). Peak concentrations were most frequently observed between 2000 and 0600 h (93.9%; mean 1-hr peak ± SD = 1119 ± 1240 μg/m3) for PM10 and 1600-0600 h (80.0%; mean 1-hr peak ± SD; 178 ± 174 μg/m3) for PM2.5. Four of five feedlots exceeded ≥1 primary PM National Ambient Air Quality Standard (NAAQS) at receptors (2-m height) over a 5-km spatial extent during the modeling period (November 2010–August 2011). Moreover, present estimates of feedlot-derived inhalable PM represent human and environmental exposure pathways currently exempt from Clean Air Act monitoring and reporting standards, and spatial interpolation of federal air quality monitors cannot adequately characterize inhalable PM concentrations in non-metropolitan municipalities and unincorporated rural communities.

Semi-arid soil bacterial communities are refined by altered plant selection pressure under conservation management practices

Plants' ability to select for, and refine, their microbiome over time is well known. In soil, the strength of plant selection pressure on microbial composition can result in distinct rhizosphere, and root-zone communities, but may be masked in soils with lower native diversity such as semi-arid soils. Semi-arid soils are also known for their high potential for wind erosion, which may be mitigated by the implementation of cover crops. These cover crops may also alter the microbial composition of the semi-arid soils, but the strength of this effect, and the resulting changes in the composition of the microbiome, are less well known. This study aimed to address whether the implementation of a single-species wheat cover crop in semi-arid agricultural soils would impact the bacterial composition of the cash crop. We investigated three tillage regimes—no-tillage with a winter wheat cover crop, no-tillage winter fallow, and conventional tillage winter fallow—to determine the effects of tillage removal, and cover crop implementation on the soil bacterial community present in the root zone of the cash crop. It was determined that the composition of the bacterial microbiome was similar between cover cropped and non-cover cropped treatments. The similarity of bacterial composition was likely due to the strong effect of environmental selection reducing overall biodiversity in these soils. However, the variability of bacterial community composition was strongly reduced for the cover cropped treatment compared to the two non-cover cropped treatments. The similarity of bacterial communities with cover cropping, without significant soil physicochemical changes, suggests that plant-selection pressure, rather than management-induced changes in soil physicochemical properties, drove the refinement (decreased dissimilarity compared to non-cover cropped treatments) of the bacterial community. The composition of this refined community under cover cropping was determined to contain an enrichment of several genera of interest including N cycling and potential plant-growth promoting bacteria. In summary, the introduction of cover cropping in the nutrient and microbial-poor soil of the semi-arid Southern High Plains strongly refined the bacterial community and selected for organisms with the potential to improve soil functions associated with greater agronomic sustainability.

Comparative analysis of rhizobial and bacterial communities in experimental cotton fields: Impacts of conventional and conservation soil management in the Texas High Plains

Conservative agricultural management strategies pursue long-term ecological benefits through practices such as no-tillage, cover crop, and inherent soil properties management. Farmers, however, are often hesitant to adopt such practices due to lack of experience, initial expense, and concern for low crop productivity. Overcoming this barrier requires novel approaches, such as effectively managing the soil microbiome to attain high productivity at a low cost, especially in a semi-arid region. To study the potential of conservation agriculture, we investigated components of soil bacterial community and rhizobial diversity in long-term experimental cotton fields divided into conventional tillage monoculture systems with winter fallow (CT) and no-tillage with mixed cover crop (M-NT) system on the Texas High Plain (THP). We conducted next-generation amplicon sequencing targeting rpoB gene with collected soil samples from different soil managements and seasons. Our research revealed that although CT had significantly greater bacterial diversity and species richness than the M-NT management, rhizobial diversity and species richness were higher in M-NT than in CT management. Both bacterial and rhizobial diversity and richness were greater in summer than in fall. The abundance of the order Rhizobiales was consistently high in M-NT than in CT fields in both seasons. Soil management altered the dominant rhizobial genus associated with cotton production systems; Rhizobium and Pararhizobium dominated M-NT management, while Bradyrhizobium and Sinorhizobium were dominant under CT management. These outcomes suggest that incorporating legumes into a cover crop in this semi-arid cotton-growing region can initiate beneficial changes to the dynamics of the indigenous rhizobial assemblage. The high prediction accuracy of our machine learning model using bacterial community data classifying the managements as CT or M-NT validates the possibilities of a strong underlying relationship between soil management and the bacterial diversity in the soil.

Machine learning algorithms improve MODIS GPP estimates in United States croplands

Introduction: Machine learning methods combined with satellite imagery have the potential to improve estimates of carbon uptake of terrestrial ecosystems, including croplands. Studying carbon uptake patterns across the U.S. using research networks, like the Long-Term Agroecosystem Research (LTAR) network, can allow for the study of broader trends in crop productivity and sustainability.Methods: In this study, gross primary productivity (GPP) estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) for three LTAR cropland sites were integrated for use in a machine learning modeling effort. They are Kellogg Biological Station (KBS, 2 towers and 20 site-years), Upper Mississippi River Basin (UMRB - Rosemount, 1 tower and 12 site-years), and Platte River High Plains Aquifer (PRHPA, 3 towers and 52 site-years). All sites were planted to maize (Zea mays L.) and soybean (Glycine max L.). The MODIS GPP product was initially compared to in-situ measurements from Eddy Covariance (EC) instruments at each site and then to all sites combined. Next, machine learning algorithms were used to create refined GPP estimates using air temperature, precipitation, crop type (maize or soybean), agroecosystem, and the MODIS GPP product as inputs. The AutoML program in the h2o package tested a variety of individual and combined algorithms, including Gradient Boosting Machines (GBM), eXtreme Gradient Boosting Models (XGBoost), and Stacked Ensemble.Results and discussion: The coefficient of determination (r2) of the raw comparison (MODIS GPP to EC GPP) was 0.38, prior to machine learning model incorporation. The optimal model for simulating GPP across all sites was a Stacked Ensemble type with a validated r2 value of 0.87, RMSE of 2.62 units, and MAE of 1.59. The machine learning methodology was able to successfully simulate GPP across three agroecosystems and two crops.

Distributed Auto-Clustering for Residential Load Profiling Using AMI Data From the U.S. High Plains

Managing demand and building customized services are essential for power retailers, distribution network operators (DNOs), and load-serving entities (LSEs) in a competitive retail environment. Therefore, understanding residential customer power demand behaviors is essential for accurate load profiling. However, the large volume of fine-grained smart meter data and the wide variety of residential behavior make load profile extraction extremely challenging, even further exacerbated by deterministic clustering’s inherent limitations. This paper develops a distributed auto-clustering approach (DAA) for load profiling using real smart meter data based on a divide-and-conquer scheme to tackle current load profiling challenges. To improve the load profiling accuracy, temperature-based categories (TBCs) are proposed to distinguish days with similar temperatures. A Heterogeneous Distributed Local Sites (HDLS) scheme is developed based on the raster map concept to distribute smart meter data among local sites while considering their size and density. Local sites send the load representatives to a central site for global clustering to significantly reduce clustering complexity and computational burden. To verify the proposed DAA, approximately 11,000 residential 15-minute smart meter data provided by a utility company from the U.S. high plains were utilized in this paper.

New observational data on orchid species in the Tiaret region (West Algeria)

Algeria, due to its geographical position, presents a great diversity of biotopes occupied by significant floristic wealth. Located in the west of the country, the Tiaret region appears as a contact zone between the Oran Tell and the Algerian -Constantin Tell, on the one hand, and between the Mediterranean Tell and the high steppe plains, on the other hand. This region is home to a very remarkable floristic diversity in general and orchids in particular which unfortunately remains very little studied and poorly known. This contribution concerns a new observation of Ophrys scolopax var. picta (Link) Rchb. f. (Orchidaceae) in the wilaya of Tiaret not previously reported. The species was discovered in a place called Chehama (Commune of Sebt) in the far north of the wilaya in the borders with the wilaya of Tissemsilt. This discovery will enrich the orchidoflora of Algeria in general and that of Tiaret in particular.

Registration of Golden Promise/Otis barley recombinant inbred line mapping population

AbstractA recombinant inbred line mapping population was developed from a cross between the heritage malting barley (Hordeum vulgare ssp. vulgare) cultivar ‘Golden Promise’ and ‘Otis’, a feed barley cultivar developed in the 1960s suitable for the high dry plains. The Golden Promise/Otis recombinant inbred line (RIL) population (MP‐3, NSL 545640 MAP) consists of 190 F5:7 individuals. The parental lines exhibited significant differences in several agronomic traits including height, heading date, yield/plant, and lodging. Transgressive segregation in the RILs was evidenced by the broad range of values observed for these agronomic traits. The RIL population was genotyped using the Illumina 50k iSelect single nucleotide polymorphism (SNP) arrays. Of the 10,810 polymorphic markers that were identified between the two parents, 4617 markers were used for generating a genetic map that spanned 4566 cM with an average distance of 1 cM between markers. The fact that Golden Promise is a malting cultivar developed in the United Kingdom, versus Otis, a feed barley bred in the United States for dryland cultivation, indicates that this population may be useful in identifying the genetic basis of many other traits.

Late Miocene paleoecology and paleoclimate in the central High Plains of North America reconstructed from paleopedological, ichnological, and stable isotope analyses of the Ogallala Formation in western Kansas, USA

The late Miocene was a critical time in the development of the North American Great Plains marked by paleoclimate-driven biotic change, including faunal turnovers and the spread of C4 dominated grasslands. The large volume of sediment shed from the Rocky Mountain region during this time preserves a record of these transitions, which can be informed by previously undescribed paleosol and trace fossil properties from the Ogallala Formation of the central High Plains. The purpose of this paper is to reconstruct paleoenvironments, paleoclimate, and paleoecology from outcrops of the Ogallala Formation in western Kansas by integrating paleopedology, ichnology, and stable isotope geochemistry. Eleven lithofacies are recognized in the study area, mostly massive to crudely stratified, fine-to coarse-grained sandstone and pebbly gravel with stratigraphically uncommon fine-grained lithofacies restricted to thinly bedded intervals or lens-shaped geometries within the sand-dominated strata. These host five pedotypes: 1) calcic Vertisols developed on overbank fines, 2) Entisols developed on braid bar gravels, 3) Entisols developed on volcaniclastic sediment lenses, 4) calcic Inceptisols developed on coarse sandy channel fills, and 5) calcareous Mollisols developed on fine sandy bedforms and channel fills. We recognize ten ichnogenera within paleosols, including burrows attributed to ants, bees, beetles or hemipterans, vinegarroon-like arthropods, fossorial reptiles, seed caching mammals, and large carnivorous mammals. Organic carbon stable isotopes indicate that the flora consisted entirely of C3 plants, and paleosols and trace-fossil evidence suggest a tree-limited savanna environment with patches of unvegetated soil. Paleoclimate proxies from paleosol and trace fossil properties indicate mean annual air temperatures between 8 °C and 20 °C with seasonal differences of up to 14 °C between mean monthly temperatures of the warmest and coolest months. Mean annual precipitation was likely between 250 mm and 460 mm with a seasonal difference of up to 250 mm between mean monthly precipitation of the driest and wettest months. While hymenopteran tracemakers were active, soil surface temperatures reached at least 30 °C and moisture content was between 10% and 20%. With timing of deposition constrained biostratigraphically to the Barstovian through Hemphillian, our paleoclimate interpretations are most consistent with the period of relative climate stability after Middle Miocene Climate Transition cooling and before Late Miocene Cooling (∼13.8 Ma–7 Ma). The trace-fossil assemblage reveals previously unknown biodiversity among soil arthropods, as well as important trophic connections between the belowground and aboveground components of the terrestrial food web.

Telescopic Megafans on the High Plains, USA Were Signal Buffers in a Major Source-To-Sink System

Sediment routing systems transport sediment and environmental signals inefficiently. The storage and recycling of sediment buffers the responses of sedimentary systems to tectonic, climatic, and geomorphic changes. Long-term ( >106 a.) storage may occur in megafans—large, low-relief, hemiconical fluvial deposystems—but the behavior of these systems over such timescales is unclear. We examine late Neogene megafan deposits on the High Plains, USA that are stored in the catchment of the continental-scale Rocky Mountain-Gulf of Mexico source-to-sink system. Using high-resolution elevation data, we map numerous fluvial ridges (inverted channel relics) that can be differentiated into five, chronologically distinct groups. The oldest four groups comprise radial arrays with multiple channel divergences (avulsion nodes). The inferred fan apices and longitudinal intersection points are offset successively downgradient, indicating that fanhead entrenchment and fan-lobe deposition were approximately contemporaneous and strongly suggesting a telescopic morphology. The youngest group of channels, also the lowest in elevation, is confined to terraces along the modern valley of the South Platte River. We interpret this group as direct evidence for the abandonment of the megafan and the incision of the present valley. Uplift was the chief driving mechanism for early telescoping, but channel widening and uniform downcutting in the younger groups suggest that change in stream power was the primary driver of later telescoping and incision. The storage of sediment in the megafan effectively decoupled sources from downstream sinks. Some of this sediment was recycled during entrenchment, but much of it remains in storage as the Ogallala Group and Broadwater Formation. Emplacement of telescopic megafans should be considered as a long-term ( ≥106 years) buffer in other modern and ancient sediment routing systems.

Quantifying groundwater recharge in the Venetian high plain between the Brenta and Piave Rivers through integrated surface–subsurface hydrological modeling

Study regionVenetian high plain between the Brenta and Piave Rivers, Northeast Italy. Study focusGroundwater recharge is the process by which aquifers, i.e., the groundwater reservoirs, are replenished. In many regions, recharge fluxes are currently declining due to more frequent hydroclimatic extreme events and unsustainable land use management. In this study, CATHY (CATchment Hydrology), an integrated surface–subsurface hydrological model (ISSHM), is used to estimate current and future recharge fluxes in a study area that represents an important source of drinking water supply for the Treviso province (Veneto Region, Northeast Italy). In particular, we aim to evaluate the impacts on recharge of a scenario with changed irrigation management, planned in compliance with European directive indications, to decrease water withdrawals from the Piave River and preserve its ecological flow. The model was first calibrated through a combination of FePEST and the Shuffled Complex Evolution algorithm, whereby both the bottom of the unconfined aquifer and the hydraulic conductivity field were tuned. After a validation step, the resulting model was used to simulate a scenario in which the flood irrigation method, currently the most widespread in the study area, is fully replaced by sprinkler irrigation. New hydrological insights for the regionOur results show that, in response to a 50 % decrease in water withdrawn from the Piave River, the total recharge decreases by about 10 %, with a local reduction in groundwater head, mainly limited in wells located in the area directly affected by the conversion of the irrigation technique. The model suggests that most of the recharge fluxes occur in irrigated areas where the hydraulic conductivity is higher. Overall, this work resulted in the development of an ISSHM capable to reproduce groundwater dynamics and its drivers at high resolution and large scale. Although it can still be improved, the model represents a useful tool to investigate possible responses of the considered hydrosystem to future land use and climate change.

Spatiotemporal Economic Analysis of Corn and Wheat Production in the Texas High Plains

The aim of this study is to visualize the historical changes in wheat and corn cropping patterns in the Texas High Plains from the perspective of geographical concentration and spatial autocorrelation. Historical county-level agricultural census data were collected from the United States Department of Agriculture and the National Agricultural Statistics Service from 1978 to 2017. Exploratory data analysis techniques were employed to examine the geographical concentration and spatial dependence of crop production among nearby locations. The results of temporal changes indicate that the harvested acres of corn and wheat tended to decrease throughout the study period. Total and irrigated harvested corn and wheat acreages were concentrated in a smaller number of counties over time while wheat production was mainly concentrated in the northern part of the region. The Moran’s I test statistic for total and irrigated areas of cropland suggest that there was spatial dependence among the neighboring counties in crop production in this region. In summary, there was a spatiotemporal change in cropping patterns in the Texas High Plains over the study period. Based on the results of the spatiotemporal changes in cropping patterns in the Texas High Plains, policy makers should promote and support non-irrigated varieties of crops in order to decrease the dependence on irrigation water from the Ogallala Aquifer.

Dryland Winter Wheat Production and Its Relationship to Fine-Scale Soil Carbon Heterogeneity—A Case Study in the US Central High Plains

Soil carbon plays a key role in maintaining soil quality, but its direct impact on crop yields depends on the interplay of different factors. This study aims to study fine–spatial variation soil properties and their effect on grain productivity in fallow–wheat cropping systems in the US central High Plains. We evaluate wheat yields in relation to soil macro and micronutrients, total C (TC), and texture as well as subtle variations in field elevation. To document soil–yield relationships at a fine spatial scale, soil sampling (0–15 and 15–30 cm depths) was conducted using a regular 30 m grid spacing in eleven adjacent fields. Interpolated yield maps indicated that the availability of key nutrients and textures contributed to the spatial distribution of wheat productivity. Random forest (RF) showed that these soil attributes were able to explain slightly under 30% of the spatial variation in crop yields. Our findings demonstrate that TC can often serve as a reliable proxy for delineating yield-based management zones, even in inherently low C soils. In addition, Fe, Zn, SO4-S, sand, and subtle topographic changes were also critical factors affecting wheat yield. Our results highlight that developing management zones in these soils relying exclusively on soil information is not straightforward. However, the high level of within-field spatial variability observed needs to be addressed.

Artificial Skin with Patterned Stripes for Color Camouflage and Thermoregulation.

Chameleons are famous for their quick color changing abilities, and it is commonly assumed that they do this for camouflage. However, recent reports revealed that chameleons also change color for body temperature regulation. Inspired by the structure of the panther chameleon's skin, a stripe-patterned poly(N-isopropylacrylamide) (PNIPAM) and polyacrylamide (PAM) hydrogel film with a laminated structure is fabricated in this work; thus, both camouflage and thermoregulation can be achieved through controlling Vis and NIR light effectively. For the PNIPAM stripe, the upper layer is the native PNIPAM hydrogel and the lower layer is the carbon nanotube-composited PNIPAM hydrogel. Thus, the PNIPAM stripe is capable of reaching 28 °C at a low environmental temperature (12 °C) and a low radiation intensity (20 mW cm-2), while preventing the body temperature from rising by changing to white under a strong radiation intensity (100 mW cm-2). For the PAM stripe, the upper layer combines colloidal photonic crystals and displays a tunable structural color by stretching, and the lower layer is mixed with PNIPAM microgels for thermal regulation. Through the fabrication of multifunctional patterns, the film can achieve both dynamic structural color and thermoregulation by precisely controlling solar radiation absorption, scattering, and reflection. More importantly, in the stripe-patterned system, the shrinkage of the PNIPAM stripes can effectively trigger the elongation of the PAM stripe, which endows the structural color changing process to be self-powered completely. The performances show that the stripe-patterned film may have potential applications in intelligent coatings, especially in areas with large temperature differences during the day such as high plains.

Regional variability of terrain index and machine learning model applications for prediction of ephemeral gullies

Terrain, or topographic, index models aggregate morphometric features of a landscape and use them to predict trajectories and initiation points of classical or ephemeral gullies. As an alternative to the index-based models, statistical machine learning approaches have been recently gaining an increased attention for identification of areas of gully susceptibility. Application of index-based or statistical models is normally restricted to the area of study, and regional model transferability is not well understood. In this study, seven terrain index models and two machine learning algorithms were applied to eight watersheds in Kansas and two watersheds in Sicily. The predictive ability of the nine models was measured by using both cut-off independent (area under the receiver operating characteristic curve) and dependent (Cohen's kappa index, sensitivity, specificity) statistics. The performance statistics of both terrain index and statistical models were cross-examined by finding an optimal threshold in one watershed and applying it to other watersheds. In Kansas, the model based on stream order (GORD) was found to perform similar to machine learning approaches, whereas the modified stream power index (MSPI) model overperformed other terrain index models in Sicily. Different landform characteristics in cultivated areas of the High Plains region in Kansas and in the steep hillslopes of Central Sicily caused models to have variable success rate when the indexes from one region were transferred to another region. The results also showed that a well-calibrated terrain index model, especially based on stream grid order, can be viewed as a valid alternative to a data driven approach for ephemeral gully mapping, but transferability of the optimal thresholds can be applied with caution.

An early warning for better planning of agricultural expansion and biodiversity conservation in the Orinoco high plains of Colombia

The eastern high plains of the Orinoco region in Colombia are known as ‘Altillanura’. They are considered the future agricultural frontier of Colombia. Unfortunately, an agricultural expansion without taking in consideration areas of high biodiversity and conservation of fragile ecosystems that are ecologically irreplaceable will likely fail in providing a sustainable grow. An orderly management planning of the territory based on scientific evidence is currently lacking for this region. Specifically, studies that combine biodiversity data and agricultural information are a major research gap. This study analyses the spatial patterns of species richness and endemism of flora and fauna at the site and subregional levels. We compared the spatial changes of biodiversity patterns with aspects related to the expansion of the agricultural frontier and its possible impacts. We found a west-to-east pattern; sites closer to the Andes were more exposed to ecological degradation than those in the east. Santa Rosalía and Puerto Lopez are the municipalities with the most remarkable species diversity. Conversely, La Primavera municipality has the most significant number of endemic species. Our spatial changes results raise the alarm showing that hotspots of diversity closer to the municipalities of Puerto Lopez and Puerto Gaitan are under more pressure than underdeveloped municipalities (La Primavera and Puerto Carreño). Our results could serve as a baseline to identify spatial changes of agrobiodiversity and a guideline for land-use planning, regional policies and local decision-makers to improve regional development in Colombia’s eastern plains region.

Groundwater sustainability in the Friuli Plain

Groundwater resources in the Friuli Venezia Giulia (FVG) Region (northeast Italy) are an important natural wealth in terms of quantity, quality and ease of supply. This optimal condition, however, has long believed that it allowed an irrational and uncontrolled exploitation that inevitably produced tangible consequences on the water resources availability.The goal of the present research is the evaluation of the sustainable use of the groundwater in the Friuli Venezia Giulia Region aimed at providing guide-lines for its rational use. The study area belongs to the hydrogeological basin of the Friuli Plain and includes part of Veneto Region and Slovenia. The plain area is divided in two parts: the High Plain (HP) characterized by a phreatic aquifer and the Low Plain (LP) where eleven confined aquifer systems were identified. The two physiographic zones are separated by the spring belt. In order to evaluate the groundwater avaliability, a 3D model of the Low Friuli Plain aquifer systems was realized using Rockworks R14 software, starting from 603 lithostratigraphic wells data. Isobath and isopach maps were elaborated using kriging geostatistical method. Precipitation, evapotranspiration, runoff and infiltration were calculated to evaluate the inflow and outflow groundwater budget terms (109 rainfall and 46 thermometric stations, time series 1979-2008). To better define the river influences and the outflows at sea, a series of recent surveys on river discharges and surface withdrawals were considered. To obtain the water-budget in non-natural conditions, as the currents, were taken into account the groundwater withdrawals that were evaluated for each type of use and for each aquifer systems, starting from 2 geodatabases: one for the domestic uses (50101 estimated wells) and one for the industrial, agricultural, fish breeding, hygienic, geothermal and other minor uses (7594 wells). Well withdrawals amount were evaluated on annual base for recent periods and expressed as m3/s. The total current estimated groundwater withdrawals reach 62.4 m3/s, of which 41.1 m3/s from the confined aquifer systems in the LP area. More than 52% of the withdrawals are due to the domestic wells. For the water-budget, the studied territory was considered a “semi-closed box” in which groundwater sharings with the neighboring areas are not relevant and where the recharge is mainly due to the influent character of the river, infiltration, rainfall and irrigation practices. As result, the waterbudget for the confined LP is equal to +2.6 m3/s representing the accuracy, fairly acceptable for the scale of the research. Withdrawal entity, spring belt discharge, phreatic levels and confined aquifer’s pressure are closely interdependent and in dynamic equilibrium. The sustainability comes from the consistency and ratio between recharge and withdrawals. The confined aquifer withdrawals in the LP represent the 23.1% of the groundwater recharge coming from the HP and the 30.6% of the spring belt discharge. Seen that this last one can not further decrease, unless loss of important ecosystems, is likely to think that the present situation can be defined of limit equilibrium.

Prescribed Fire Case Studies From Wyoming, USA: Diverse Applications and Common Themes at the Great Plains-Rocky Mountains Interface

Prescribed fire is an important management tool for rangelands and forests in North America and globally. However, the application of prescribed fire is a complex endeavor that involves significant planning, partnerships, and risk. Recent evidence suggests that not enough prescribed fire is being applied to reduce wildfires, in part, because risk and bureaucracy continue to hinder application. While common in the eastern and central Great Plains, prescribed fire is less common in the western United States. Therefore, we summarized 11 prescribed fire projects in Wyoming, USA (or immediately adjacent to in one case) across five U.S. Environmental Protection Agency Ecoregions (High Plains, Northwestern Great Plains, Wyoming Basin, Southern Rockies, and Middle Rockies)—a state where the prairies converge with the western mountains. Fires were conducted from 2014 to 2022 and ranged in size from <1 acre to 3,000 acres (a total of 8,795 acres). Fires occurred on a variety of land ownerships including private ranch, university, state trust, Army, Bureau of Land Management, Forest Service, Bureau of Reclamation, and U.S. Department of Agriculture. Crew sizes ranged from 1 to 40 people. Approximately half of the burns were in the spring, a third were in the fall, and two were in the winter; no summer burns were reported. Duration of planning ranged from a few months to 5 years. Drip torches were the most common ignition device used; however, we noted the use of propane torches, terratorches, helitorches, and drones for lighting fires. Weather prescriptions varied across fires with some choosing low humidity to make up for low fuel loads and others choosing moderate humidity to minimize risk. A wide variety of plant communities, purposes, and applications were noted. Weather prescriptions particularly in the spring were consistently challenging and the importance of partnerships with neighbors and other agencies for planning and implementation was noted frequently. Across these unique prescribed fire case studies, we have noted commonalities that can communicate important practicalities of applying fire across complex land types and jurisdictions. Sharing such information is important in a state with the least population density in the country to enhance the professional application of prescribed fire across a diversity of situations.

Determination of the Most Efficient Forage Sorghum Irrigation Scheduling Strategies in the U.S. Central High Plains Using the AquaCrop Model and Field Experiments

The current status of water resources in the U.S. Central High Plains necessitates adopting water conservation practices to move toward a sustainable agricultural economy. Identifying proper irrigation scheduling techniques is a conservative practice to maintain the sustainability of the agricultural systems. However, conducting field experiments is time and money consuming. Thus, the utilization of crop models, such as AquaCrop, could be a convenient alternative to field experiments. The FAO AquaCrop model was calibrated and validated for simulating forage sorghum yield response to various deficit irrigation conditions in a semi-arid region. Afterwards, the model was used to investigate the efficiency of the pre-season and in-season irrigation scheduling scenarios. In this study, the soil water status at the planting time was considered as the indicator of the pre-season irrigation level. Therefore, the pre-season irrigation scenarios were arranged as the replenishment of soil water deficiency at the time of planting at up to 30, 50, and 100% of the soil’s total available water for the first 60 cm of soil depth and the same replenishment levels for the entire crop root zone (150 cm soil depth). Then, AquaCrop long-term (37 years) simulations of forage sorghum biomass and irrigation water use efficiency reactions to three levels of maximum allowable depletion (MAD) (40, 55, and 70%) were compared to three fixed irrigation interval (4, 6, and 10 days) scenarios by considering six pre-season irrigation conditions (36 scenarios). The scenarios analysis found the 10-day irrigation interval and the MAD levels of 55% and 70% to be the most efficient irrigation scheduling strategies if combined with pre-season irrigation that brought the crop root zone (0–150 cm soil depth) to field capacity. Moreover, the 40% MAD application was the least efficient strategy. This study’s outputs can be a baseline for establishing forage sorghum irrigation scheduling in the U.S. Central High Plains. However, exploring the interactions of irrigation scheduling strategies with other irrigation and agronomic practices, such as salinity management and fertilizer application, is highly recommended.