Texas Blackland Research Articles

Efficacy of various insecticides on thrips infesting cotton in the Texas Blacklands, 2023

Efficacy of various insecticides on thrips infesting cotton in the Texas Blacklands, 2023

Assessing the watershed-scale effects of tillage management on surface runoff and sediment loss using a Curve Number-precipitation relationship based approach

Poor soil management limits the soil functions of water infiltration and storage and enhances water and soil losses. Adoption of improved soil management practices is thus vital to protecting agricultural soils amid recurring droughts and declining water availability. Although the benefits of adopting soil health promoting practices such as no-tillage (NT) have been extensively investigated at field scale, studies quantifying the watershed-scale impacts of such practices are lacking. This study aims to address this gap by quantifying soil and water conservation benefits of adopting NT over conventional tillage (CT) on all croplands in the Brushy Creek Watershed in the Texas Blackland Prairies using the Agricultural Policy/Environmental eXtender (APEX) model. Most hydrologic and water quality models often fall short in accurately simulating the effects of management practices since they are not capable of simulating changes in soil and hydrologic properties that result from changes in soil management. This study proposed a novel framework to translate field-scale rainfall and runoff relationships into a watershed-scale parameterization tool that can be used for any agricultural watershed where measured rainfall and runoff data are available. Curve Number–Precipitation (CN-P) relationships were first defined based on field observations of rainfall and runoff from paired CT and NT fields. The CT and NT APEX models were then trained to follow the defined CN-P relationships to reflect the associated changes in hydrologic properties. Changing management from CT to NT on all croplands in the study watershed (i.e., in 35% of the watershed area) resulted in a 25% (38 mm year−1) reduction in average annual runoff and a 57% (1.13 t ha -1year−1) reduction in average annual sediment loss at the outlet of the watershed. The reduction in sediment loss from individual subareas with NT management was found to be sensitive to subarea physical properties such as slope and channel depth to width ratio, but the reduction in runoff was not sensitive to those properties. Results from this study are useful to natural resource conservationists and watershed managers in effectively implementing improved soil management practices.

Within-field yield stability and gross margin variations across corn fields and implications for precision conservation

Soil spatial variability is a primary contributor to within-field yield variation across farms. Spatio-temporal yield stability and variability can be assessed through multi-year yield monitor data and geostatistical techniques. Our objective was to delineate yield stability zones using multi-year yield data coupled with gross margins to plan precision conservation prescriptions. This study employed corn yield measurements from 2018, 2019, 2020 and farm economics data to compile yield stability and gross margin maps for nine Texas Blackland Prairie corn fields, and identified nonprofitable areas in each field that may be unsuitable for crop production. Yield stability zones were delineated using mean and coefficient of variation of multi-year yield maps (Zone A: high yield, stable; Zone B: high yield, unstable; Zone C: low yield, unstable; and Zone D: low yield, stable). Approximately 57% of the area in the fields was classified as unstable and, nearly 29% of the area yielded consistently below the field mean (Zone D). Gross margin for stability zones ranged from − $693 to $775/ha. Stability zones A and B generally had positive gross margins, whereas zones C and D had negative margins. Based on yield and gross margin assessment, yield stability zone D could be removed from row crop production. As a part of the Long-Term Agroecosystem Research Network Common Cropland Experiment, Zone D was removed from production (fields Y-8 and Y-13) or received reduced inputs (field SW-16 and W-13). Further study is needed to verify the farm-level economic benefits to producers and to evaluate the environmental benefits of precision conservation.

Mapping Within-Field Soil Health Variations Using Apparent Electrical Conductivity, Topography, and Machine Learning

High-resolution maps of soil health measurements could help farmers finetune input resources and management practices for profit maximization. Within-field soil heath variations can be mapped using local topography and apparent electrical conductivity (ECa) as predictors. To address these issues, a study was conducted in Texas Blackland Prairie soils with the following objectives: (i) to assess and map within-field soil health variations using machine learning; (ii) to evaluate the usefulness of topography and ECa as soil health predictors; and (iii) to quantify the relationship between ECa and soil health index and use ECa to estimate soil health spatial distribution. We collected 218 topsoil (0–15 cm) samples following a 35 m × 35 m grid design and analyzed for one-day CO2, organic C, organic N, and soil health index (SHI) based on the Haney Soil Health Tool. A random forest model was applied to predict and map those properties on a 5 m × 5 m grid where ECa, and terrain attributes were used as predictors. Furthermore, the empirical relationship between SHI and ECa was established and mapped across the field. Results showed that the study area was variable in terms of one-day CO2, organic C, organic N, SHI, and ECa distribution. The ECa, wetness index, multiresolution valley bottom flatness, and topographic position index were among the top predictors of soil health measurements. The model was sufficiently robust to predict one day CO2, organic C, organic N (R2 between 0.24–0.90), and SHI (R2 between 0.47–0.90). Overall, we observed a moderate to strong spatial dependency of soil health measurements which could impact within-field yield variability. The study confirmed the applicability of easy to obtain ECa as a good predictor of SHI, and the predicted maps at high resolution which could be useful in site-specific management decisions within these types of soils.

Dual‐isotope approach for assessing agricultural management effects on nutrient dynamics: Proof of concept

AbstractQuantifying the impact of long‐term agricultural management on nutrient fate and transport is critical for developing sustainable management solutions. In this study, the utility of a dual‐isotope approach, combining soil δ15N with analysis of δ18O of phosphate (δ18Op), was assessed at the Riesel Watershed in the Texas Blackland Prairies. The objective was to examine changes in soil nutrient concentration and isotopic signal from fields with contrasting nutrient source (inorganic fertilizer vs. poultry litter) and land use (remnant prairie vs. row crops) over a long‐term study (2002–2017). Results showed that soil δ15N varied between land use at the study onset likely because of greater N loss and cycling in row crops, with differences between row‐cropped fields becoming apparent following application of litter to one field. In contrast, soil δ18Op in row‐cropped fields only differed from the prairie following the long‐term nutrient trial; however, signatures were similar irrespective of P source. Results from this proof‐of‐concept study highlight the potential of a dual‐isotope approach for quantifying nutrient dynamics within soil systems when coupled with knowledge of long‐term management practices. Findings and study limitations also emphasize the need for future research and application of a dual‐isotope framework in agricultural landscapes for identifying and tracing nutrient fate and transport.

Species identification and morphological trait diversity assessment in ryegrass (Lolium spp.) populations from the Texas Blackland Prairies

AbstractRyegrass (Lolium spp.) is a troublesome weed in major wheat (Triticum aestivum L.) production regions in the United States. High diversity and adaptive potential are known to contribute to its success as a weed species and also create difficulties in correct species identification in fields. The objective of this research was to characterize diversity for 16 different morphological traits among 56 Lolium populations collected from wheat production fields across the Texas Blackland Prairies region and identify Lolium species based on taxonomic characteristics. Populations were highly diverse (both at inter- and intrapopulation levels) for the traits studied, and a taxonomic comparison with USDA-GRIN reference samples revealed that all the populations were variants of Italian ryegrass [Lolium perenne L. ssp. multiflorum (Lam.) Husnot] with a few offtypes of perennial ryegrass (Lolium perenne L.) or probable hybrids between the two species. Hierarchical clustering grouped the populations into six clusters based on their similarities for the morphological traits investigated. Principal component analysis showed that the variability for yield traits greatly contributed to the total diversity. Pre-flowering plant height (stage 10 on Feekes scale) was positively correlated with tiller count, shoot biomass, and spike count, but not with total seed count per plant, whereas plant height at maturity (stage 11.3 to 11.4 on Feekes scale) was highly correlated with total seeds per plant. Further, basal node color was positively correlated with plant growth habit, regrowth rate, and leaf color. Leaf blade width was positively correlated with survival to pinoxaden and multiple herbicides, whereas, spike count was negatively correlated with survival to mesosulfuron. The high levels of intra- as well as interpopulation variability documented in this study indicate the potential of this species to rapidly adapt to herbicides and emphasize the need for implementing diverse management tactics, including the integration of harvest weed seed control.

Seed traits correlate with herbicide resistance in Italian ryegrass (Lolium perenne ssp. multiflorum).

Italian ryegrass (Lolium perenne ssp. multiflorum) is one of the major winter annual weeds worldwide. In this research, diversity for seed morpho-physiological traits such as seed weight, seed size, awnedness, dormancy, speed of germination, and seed vigor among Italian ryegrass populations collected from the Texas Blacklands region were assessed, and potential association with herbicide resistance was investigated. A high degree of diversity was observed among the populations for 100-seed weight (125-256 mg), seed length (4.8-6.6 mm), awn length (0-6 mm), and total seedling length (9-14 cm at 21 days after seed germination). Inter-population range for seed dormancy was higher in the freshly harvested seed (31-85%), which reduced to 18 to 62% at 9months after harvest. Populations with high initial seed dormancy (> 70% dormancy) released dormancy at a faster rate than the low dormancy group (< 40%). Percent survival status to multiple postemergence herbicides was positively correlated with 100-seed weight and fresh or initial seed dormancy. Early emerging cohorts are easily controlled by pre-plant tillage and preemergence herbicides, whereas late emerging cohorts (facilitated by seed dormancy) are exposed to postemergence herbicides wherein greater opportunities exist for resistance evolution, likely explaining the occurrence of high seed dormancy in Italian ryegrass populations resistant to postemergence herbicides. High seed weights can further allow seedling emergence from greater burial depth, thereby exposing more seedlings to postemergence herbicides and increasing the likelihood of resistance evolution. Results provide unique insights into the association between seed traits and herbicide resistance in this species. © 2021 Society of Chemical Industry.

Corn response to selected soil health indicators in a Texas drought

The phrase “soil health” describes the condition of a soil in terms of its physical, chemical, and biological properties. The relationship between soil health and crop yield is rather complex, and quantifying their spatial characteristics at field scale is often limited in the literature. To explore the significance and spatial characteristics of soil health and its indicators in crop production, field-based research was conducted in 2018 at the Blackland Research Center, Texas with the following objectives: (i) to quantify soil health indicators of the Haney Soil Health Tool across a corn field; (ii) to relate soil health status to drought-year corn yield using geospatial techniques; and (iii) to evaluate the relationship among soil health, corn yield, and soils types. We collected 218 samples from 0 to 10 cm soil depth in a 27-ha field following a 35 m × 35 m grid sampling scheme. Samples were analyzed for water extractable organic carbon (WEOC), total nitrogen, nitrate-nitrogen, ammoniacal-nitrogen, and 24-hr CO2 evolution (1-day CO2). Analyses results were used to calculate a soil health value based on Haney Soil Health Tool. The field had an average soil health value of 8.5 (±2.2), and corn yield of 2.9 t ha−1 (±1.3); however, corn yield was more variable (CV > 43%) than soil health (CV = 26.7%). Overall, soil samples with lower values of 1-day CO2, WEOC, and organic nitrogen indicated a lower soil health value, which generally corresponding to lower corn yield. Corn yield may be weakly predicted by soil health (Corn yield = −0.29 + 0.39 × Soil health value, R2 = 0.28). Soil type and rainfall exhibited measurable effects upon the calculated soil health value; corn yields were greater for Houston Black clay than Austin silt clay under drought-year conditions. The variation in drought-year corn yield can be explained by the soil health and its indicators in Texas Blackland soils. Further research is necessary to verify the relationship in differing soil types, management scenarios, and annual rainfall totals.

Efficacy of Below Ground Bt Corn Technologies Toward Mexican and Southern Corn Rootworms in the Texas Blacklands, 2020

Efficacy of Below Ground Bt Corn Technologies Toward Mexican and Southern Corn Rootworms in the Texas Blacklands, 2020

Effects of planned grazing and burning to restore tallgrass species in old-field sites under drought conditions in Texas Blackland Prairie

We examined if reintroduction of grazing with or without burning would enhance succession towards native prairie vegetation on previously over-seeded old-field tallgrass prairie subjected to mowing or burning. We hypothesized that returning grazing and fire to these seeded and old-field sites would change establishment and competitive relationships among plant species to benefit fire-tolerant prairie species. Grazing and burning had neutral effects on native prairie species on the previously seeded and unseeded sites over a study period that experienced 70 % of normal precipitation. Herbaceous group categories included old-field grasses, seeded tallgrasses, other grasses (< 2%), seeded perennial forbs, other perennial forbs, and annual forbs. Seeded species comprised about 70 % of the community on seeded plots and 10 % on unseeded plots for the eight years of this study. Seeded-ungrazed tallgrass biomass increased 19 % and on seeded-unburned sites biomass increased 11 %. Tallgrass biomass of unseeded-grazed burned treatment remained at about 4% throughout the study, but with no grazing or no burning biomass, doubled. Changes in biomass associated with treatments led to changes in soil temperatures near the soil surface in summer months. Community dissimilarity was most affected by seeding followed by year, grazing, and burning (P’s = 0.001). Collectively, seeded or unseeded, grazed, or ungrazed site soil temperatures averaged 4.8 °C higher than tree-shaded sites in afternoons of hotter months. Soil temperature differences were inversely proportional to successful site restoration. During afternoons of hotter months, soil temperatures of seeded sites were 1.1 °C lower than unseeded sites, while grazed sites were 2.0 °C greater than ungrazed sites, and burned sites were 1.6 °C higher the year of the burn than unburned sites (P’s < 0.05). While grazing and burning had neutral effects on previously seeded and unseeded prairie sites, seeding accounted for about 70 % of the community on seeded plots and 10 % on unseeded plots.

Texas Blackland Prairie restoration on old-field vegetation using seeding, mowing, and burning

This study compares degraded old-field grass-dominated pasture response to over-seeding with native tallgrass prairie species with the management practices of burning, mowing and a no-treatment control. Treatments were randomly allocated in a 2 × 3 factorial design with at least six replicate 40 m × 40 m plots. In the third year after treatment species richness increased for seeded vs. unseeded plots (18.9 vs. 14.4 species per plot; p < 0.01) and for mowed or control vs. burned plots (17.4 vs. 15.2 species per plot; p < 0.05). Also, tiller densities of planted tallgrasses increased somewhat to 12% of old-field grass tiller densities (p = 0.001). Multivariate analysis (ANOSIM) the third season following planting indicated some dissimilarity between seeded and unseeded plots (R = 0.32; p = 0.002). After 9 years dissimilarity between seeded and unseeded communities had increased (R = 0.83; p = 0.001) but species richness was similar (p > 0.27). Seeded tallgrasses comprised 44% biomass in seeded vs. 3% in unseeded plots, while seeded forbs comprised 16% biomass in seeded vs. 4% in unseeded plots (p < 0.01). Multivariate analysis of seeded-burned and seeded-mowed sites indicated some dissimilarity (R = 0.25; p = 0.002) with tallgrass biomass being 55% greater (p = 0.001) on mowed sites than controls and 117% greater than burned sites. Tallgrass prairie species planting success may be enhanced with well-timed mowing but harmed by burning when plants are young.

Multiple herbicide–resistant Lolium spp. is prevalent in wheat production in Texas Blacklands

AbstractField surveys were conducted across the Blacklands region of Texas during 2016 and 2017 to document the distribution of herbicide-resistant Lolium spp. infesting winter wheat production fields in the region. A total of 68 populations (64 Italian ryegrass, four perennial ryegrass) were evaluated in a greenhouse for sensitivity to herbicides of three different modes of action: an acetolactate synthase (ALS) inhibitor (mesosulfuron-methyl), two acetyl-coenzyme-A carboxylase (ACCase) inhibitors (diclofop-methyl and pinoxaden), and a 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) inhibitor (glyphosate). Herbicides were applied at twice the label-recommended rates for mesosulfuron-methyl (29 g ai ha−1), diclofop-methyl (750 g ai ha−1), and pinoxaden (118 g ai ha−1); and at the recommended rate for glyphosate (868 g ae ha−1). The herbicide screenings were followed by dose-response assays of the most-resistant ryegrass population for each herbicide at eight rates (0.5, 1, 2, 4, 8, 16, 32, and 64×), compared with a susceptible population at six rates (0.0625, 0.125, 0.25, 0.5, 1, and 2×). The initial screening and dose-response experiments were conducted in a completely randomized design with three replications and two experimental runs. Survivors (&lt;80% injury) were characterized as highly resistant (0% to 20% injury) or moderately resistant (21% to 79%). Results showed that 97%, 92%, 39%, and 3% of the Italian ryegrass populations had survivors to diclofop-methyl, mesosulfuron-methyl, pinoxaden, and glyphosate treatments, respectively. Of the four perennial ryegrass populations, three were resistant to diclofop-methyl and mesosulfuron-methyl, and one was resistant to pinoxaden as well. Perennial ryegrass populations did not exhibit any resistance to glyphosate. Dose-response assays revealed 37-, 196-, and 23-fold resistance in Italian ryegrass to mesosulfuron-methyl, diclofop-methyl, and pinoxaden, respectively, compared with a susceptible standard. One Italian ryegrass population exhibited three-way multiple resistance to ACCase-, ALS-, and EPSPS-inhibitors. The proliferation of multiple herbicide–resistant ryegrass is a challenge to sustainable wheat production in Texas Blacklands and warrants diversified management strategies.

Long-term agro-economic and environmental assessment of adaptive nutrient management on cropland fields with established structural conservation practices

On-farm adoption of agricultural conservation practices or management alternatives depends on conservation ethic, social pressure, regulatory attention, and perceived impact on yield and economic return. Although agro-economic and environmental impacts are assumed to conflict, little research has been conducted to address potential tradeoffs and provide a scientific basis for decision-making. Thus, this 16-year evaluation of adaptive nutrient management was conducted in the Texas Blackland Prairies ecoregion on six fields with structural conservation practices already in place. Each field was randomly selected to receive either commercial fertilizer or poultry litter at rates of 4.5 to 13.4 Mg ha⁻¹. Two major nutrient management adaptations were made (i.e., soil test nitrogen [N] rate recommendations in 2009, and reduction of fallow period length and cover cropping during prolonged fallow periods in 2013). Important results included (1) soil test recommendations that consider historical crop yields reduced N application 25% to 38% for low rates of poultry litter, but did not reduce profits; (2) interannual variability of economic and weather conditions contributed to the lack of statistically significant differences in profit, although profit reduction for high nutrient rate treatments was clear; and (3) litter application, especially at rates in excess of crop phosphorus (P) needs, also increased runoff P losses by 1 to 1.4 kg ha⁻¹ indicating the need for careful management of organic nutrient sources. Results of this long-term study showed that maintaining or increasing economic return does not have to be sacrificed to improve environmental impacts, which is an important consideration as producers make on-farm management decisions.

The future of North American grassland birds: Incorporating persistent and emergent threats into full annual cycle conservation priorities

North American grasslands are one of the most threatened ecosystems in the world, and grassland bird populations have experienced drastic declines over the past half century. Land‐use change is widely accepted as the most persistent threat, and climate change is expected to further compromise grassland integrity. The limited consideration of projected future threats is a significant gap in existing conservation priorities for North America's central grasslands. We identified Grassland Climate Strongholds (predicted to have high climate suitability for grassland birds both today and under 21st century climate change scenarios) and Grassland Climate and Land‐use Strongholds (predicted to have high climate and land‐use suitability for grassland birds today and under 21st century climate change scenarios). Strongholds were mainly distributed across southern Canada, the Dakotas, Montana, Wyoming, Colorado, New Mexico, the Oklahoma Panhandle, Texas, and the Chihuahuan Desert. Strongholds vulnerable to land‐use conversion included the Prairie Pothole region and surrounding areas, much of the eastern‐central Plains, the Texas Blackland Prairie, the Western Gulf Coastal Plain, and areas west of the Chihuahuan Desert. A maximum of only 9% of strongholds were protected. Strongholds are critical for full annual cycle conservation of declining grassland birds in North America and complement existing grassland priorities.

Continent-Scale Landscape Conservation Design for Temperate Grasslands of the Great Plains and Chihuahuan Desert

In support of natural resource agencies in Canada, the United States, and Mexico, we report on a series of component analyses and an updated Landscape Conservation Design for temperate grassland conservation. We targeted 12 major grassland ecosystem types that occur across the Great Plains and Chihuahuan Desert regions. Component analyses included (1) documenting long-term trends in extent by grassland type, (2) identifying species of concern associated with the major grassland types, (3) documenting current protected areas including each grassland type, (4) assessing landscape intactness and connectivity among grassland areas, and (5) identifying Grassland Potential Conservation Areas (GPCAs) to advance grassland conservation. Most severe declines in grassland extent have occurred in tallgrass prairie types, followed by mixed-grass, shortgrass, and semi-desert grasslands. Similar trends by type were documented for landscape intactness and connectivity. Some 174 species of vertebrates, invertebrates, and plants considered by NatureServe as critically imperiled, imperiled, or vulnerable are strongly associated with these grassland types, and 103 are listed under protective legislation in one or more countries. Just 1.2% of historic extent for all types combined is currently found within designated protected areas. A total of 177 GPCAs were identified to represent grassland type diversity in areas least likely to conflict with other land uses. Within identified GPCAs, type-specific representation varied from a low of just 1% of historic extent for Texas Blackland Tallgrass Prairie to a high of 27% for Western Great Plains Sand Prairie. Combined across all 12 grassland types, 15% of historic extent is represented.

Corn (Zea mays L.) Response to Hybrid, Row Spacing, and Plant Populations in the Blacklands of Central Texas

Field studies were conducted during the 2013 and 2014 growing seasons in central Texas near Taylor (30.5326o N; 97.4548o W) to determine the effect of hybrid, row spacing, and plant populations on corn growth and yield. Two corn hybrids (BH 8844 and BH 8900) were compared at 53,000, 62,000, and 71,000 plants ha-1 planted one row on a single bed or twin rows (spaced approximately 20 cm apart) on a single bed. Plant counts were taken 4 to 6 wk after planting while ear height measurements were taken approximately four wk prior to corn harvest. Crop yield was determined by harvesting all eight rows of each plot with a combine. Weights were adjusted to 12% moisture. Experimental design was a factorial arrangement using a randomized complete block design with corn hybrid (2), row spacing (2), and seeding rates (3) as factors. Data were analyzed using PROC GLM with SAS (SAS Institute, Inc., Cary, NC) and treatment means separated by Fisher's protected least significant difference test at P = 0.05. Plant height was not affected by plant populations or row spacing as only hybrid response was significant with BH 8900 being taller in both years. Row spacing affected ear height in one of two years with the twin row spacing having a taller ear placement in the dryer year. No differences were seen with ear placement with respect to plant populations. In the dry year, yield of BH 8844 decreased as plant populations increased; however, no differences were noted with BH 8900. In the wet year, the inverse was seen with increased yield with higher populations with both hybrids. The twin row system increased BH 8900 yield in 2013. In 2014, with BH 8844, the single row system outyielded twin row and no differences noted with BH 8900. The results were quite variable and this was due in part to rainfall events in the two years. Plant and ear height was influenced by hybrid while yield response was somewhat affected by population and row spacing. A hybrid x row width response was noted indicating that certain hybrids will respond to row spacing more than others.

Selecting Cool‐Season Forage Grasses for Yield, Seasonal Yield Distribution, and Nutritive Value in the Blacklands and Rolling Plains Ecoregions of Texas

Core Ideas The study evaluated seven cool‐season crops for their forage yield and quality in the Blacklands and Rolling Plains of Texas. There was significant interaction of crop species and environment on forage yield and quality. Triticale has wide range of adaptability in both the Blacklands and Rolling Plains ecoregions. Site‐specific recommendation of best adapted forage crop species would help the producers achieve higher forage productivity and profitability. Selection of suitable cool‐season crop species for winter forage production is a critical management decision in many ecoregions of the United States, including Texas. A study was conducted during 2004 to 2007 in the Blacklands and Rolling Plains ecoregions of Texas using seven cool‐season crops to determine the site‐specific crop choice to maximize forage yield and nutritive value. The seven crop species tested in these two ecoregions included: barley (Hordeum vulgare L.), hard red wheat (Triticum aestivum L.), oat (Avena sativa L.), rye (Secale cereale L.), ryegrass (Lolium multiflorum Lam.), soft red wheat (Triticum aestivum L.), and triticale (×Triticosecale Wittmack). The results indicated that crop choice for maximizing the forage yield and nutritive value varied with environment. In the Blacklands, oat and triticale produced greater forage yields than other crop species (P &lt; 0.05). In the Rolling Plains, ryegrass yielded more forage during years of above‐average precipitation, whereas rye and triticale produced more forage during drier years. Seasonal forage yield distribution varied among different site‐years of the Blacklands and Rolling Plains ecoregions. Triticale was demonstrated to be the crop that performed most consistently at both ecoregions of Texas. Rye and barley had greater nutritive value and mineral composition in the Blacklands, whereas ryegrass had greater mineral composition in the Rolling Plains (P &lt; 0.05). Given this information, producers in the Blacklands and Rolling Plains ecoregions can make informed decisions on selection of suitable forage crops to be grown on their farms to achieve greater forage yield and nutritive value, and to match up their specific management and livestock requirements.

An updated understanding of Texas bumble bee (Hymenoptera: Apidae) species presence and potential distributions in Texas, USA.

Texas is the second largest state in the United States of America, and the largest state in the contiguous USA at nearly 700,000 sq. km. Several Texas bumble bee species have shown evidence of declines in portions of their continental ranges, and conservation initiatives targeting these species will be most effective if species distributions are well established. To date, statewide bumble bee distributions for Texas have been inferred primarily from specimen records housed in natural history collections. To improve upon these maps, and help inform conservation decisions, this research aimed to (1) update existing Texas bumble bee presence databases to include recent (2007–2016) data from citizen science repositories and targeted field studies, (2) model statewide species distributions of the most common bumble bee species in Texas using MaxEnt, and (3) identify conservation target areas for the state that are most likely to contain habitat suitable for multiple declining species. The resulting Texas bumble bee database is comprised of 3,580 records, to include previously compiled museum records dating from 1897, recent field survey data, and vetted records from citizen science repositories. These data yielded an updated state species list that includes 11 species, as well as species distribution models (SDMs) for the most common Texas bumble bee species, including two that have shown evidence of range-wide declines: B. fraternus (Smith, 1854) and B. pensylvanicus (DeGeer, 1773). Based on analyses of these models, we have identified conservation priority areas within the Texas Cross Timbers, Texas Blackland Prairies, and East Central Texas Plains ecoregions where suitable habitat for both B. fraternus and B. pensylvanicus are highly likely to co-occur.

Identifying subsoil variation associated with gilgai using electromagnetic induction

Proximal sensing, such as electromagnetic induction, has been used to map the spatial distribution of soil properties; however, the response of these instruments to short-interval variability associated with Vertisols has not been studied. Meter-scale circular landscape features called gilgai, which are associated with surface and subsurface variability, make sampling these soils difficult, especially if the surface has been plowed. The EM38 is an electromagnetic induction tool with a relatively small spatial footprint (1m2), which may be fine enough to identify subsoil variability associated with gilgai. In 2011, an EM38 survey was conducted for a 40 by 50m field with intact circular gilgai in the Texas Blackland Prairies. Soil properties including gravimetric water content, bulk density, inorganic C content, and electrical conductivity of the soil solution were measured. In 2012, half of the field was plowed, and another EM38 survey was conducted. The EM38 was able to locate subsurface variability in soil properties between microhighs and microlows under both intact and plowed conditions. Semi-variance of soil properties increased with increasing distance and reached maximum variance at 3m, corresponding to the average diameter of gilgai features. The overall variability across the study site decreased after plowing. Water content and inorganic C content were the primary soil properties that forced the response of the EM38 in these landscapes, and the partial correlation coefficient suggests the effects of water content and inorganic C content on EM38 response are independent. In calcareous Vertisols, the EM38 can be used to identify subsurface variability and may be useful in developing sampling schemes for Vertisol classification, soil sampling, and fine-scale digital soil mapping.

MEAN-VARIANCE VERSUS MEAN–EXPECTED SHORTFALL MODELS: AN APPLICATION TO WHEAT VARIETY SELECTION

AbstractOne of the most popular risk management strategies for wheat producers is varietal diversification. Previous studies proposed a mean-variance model as a tool to optimally select wheat varieties. However, this study suggests that the mean–expected shortfall (ES) model (which is based on a downside risk measure) may be a better tool because variance is not a correct risk measure when the distribution of wheat variety yields is multivariate nonnormal. Results based on data from Texas Blacklands confirm our conjecture that the mean-ES framework performs better in term of selecting wheat varieties than the mean-variance method.