Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks.

Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site-its constituency-as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites' environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions "centered" on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These "specialist" sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context.

Genome-wide association mapping of resistance to the sorghum aphid in Sorghum bicolor.

Since 2013, the sorghum aphid (SA), Melanaphis sorghi (Theobald), has been a serious pest that hampers all types of sorghum production in the U.S. Known sorghum aphid resistance in sorghum is limited to a few genetic regions on SBI-06. In this study, a subset of the Sorghum Association Panel (SAP) was used along with some additional lines to identify genomic regions that confer sorghum aphid resistance. SAP lines were grown in the field and visually evaluated for SA resistance during the growing seasons of 2019 and 2020 in Tifton, GA. In 2020, the SAP accessions were also evaluated for SA resistance in the field using drone-based high throughput phenotyping (HTP). Flowering time was recorded in the field to confirm that our methods were sufficient for identifying known quantitative trait loci (QTL). This study combined phenotypic data from field-based visual ratings and reflectance data to identify genome-wide associated (GWAS) marker-trait associations (MTA) using genotyping-by-sequencing (GBS) data. Several MTAs were identified for SA-related traits across the genome, with a few common markers that were consistently identified on SBI-08 and SBI-10 for aphid count and plant damage, as well as loci for reflectance-based traits on SBI-02, SBI-03, and SBI-05. Candidate genes encoding leucine-rich repeats (LRR), Avr proteins, lipoxygenases (LOXs), calmodulins (CAM) dependent protein kinase, WRKY transcription factors, flavonoid biosynthesis genes, and 12-oxo-phytodienoic acid reductase were identified near SNPs that had significant associations with different SA traits. In this study, flowering time-related genes were also identified as a positive control for the methods. The total phenotypic variation explained by significant SNPs across SA-scored traits, reflectance data, and flowering time ranged from 6 to 61%, while the heritability value ranged from 4 to 69%. This study identified three new sources of resistant lines to sorghum aphid. These results supported the existing literature, and also revealed several new loci. Markers identified in this study will support marker-assisted breeding for sorghum aphid resistance.

Responses to environmental variability by herbivorous insects and their natural enemies within a bioenergy crop, Miscanthus x giganteus.

Precision agriculture (PA) is the application of management decisions based on identifying, quantifying, and responding to space-time variability. However, knowledge of crop pest responses to within-field environmental variability, and the spatial distribution of their natural enemies, is limited. Quantitative methods providing insights on how pest-predator relationships vary within fields are potentially important tools. In this study, phloem feeders and their natural enemies, were observed over two years across 81 locations within a field of the perennial feedstock grass in Georgia, USA. Geographically weighted regression (GWR) was used to spatially correlate their abundance with environmental factors. Variables included distance to forest edge, Normalized Difference of Vegetation Index (NDVI), slope, aspect, elevation, soil particle size distribution, and weather values. GWR methods were compared with generalized linear regression methods that do not account for spatial information. Non-spatial models indicated positive relationships between phloem-feeder abundance and wind speed, but negative relationships between elevation, proportions of silt and sand, and NDVI. With data partitioned into three seasonal groups, terrain and soil variables remained significant, and natural enemies and spiders became relevant. Results from GWR indicated that magnitudes and directions of responses varied within the field, and that relationships differed among seasons. Strong negative relationships between response and explanatory factors occurred: with NDVI during mid-season; with percent silt, during mid-, and late seasons; and with spider abundance during early and late seasons. In GWR models, slope, elevation, and aspect were mostly positive indicating further that associations with elevation depended on whether models incorporated spatial information or not. By using spatially explicit models, the analysis provided a complex, nuanced understanding of within-field relationships between phloem feeders and environmental covariates. This approach provides an opportunity to learn about the variability within agricultural fields and, with further analysis, has potential to inform and improve PA and habitat management decisions.

Riparian land cover and hydrology influence stream dissolved organic matter composition in an agricultural watershed.

Dissolved organic matter (DOM) represents an essential component of the carbon cycle and controls biogeochemical and ecological processes in aquatic systems. The composition and reactivity of DOM are determined by the spatial distribution of its sources and its residence time in a watershed. While the effects of agricultural land cover on DOM quality have been reported across spatial and temporal scales, the influence of riparian land cover on stream DOM composition has received little attention. Furthermore, the combined effects of riparian land cover and streamflow rates on DOM composition require investigation. To this end, a multi-year (2016-2018) DOM characterization study was conducted using bi-weekly water samples collected from seven sub-watersheds nested within the Little River Experimental Watershed (LREW) near Tifton, Georgia, USA. DOM optical properties were determined to assess compositional variations using UV-Vis and excitation-emission matrix (EEM) fluorescence spectroscopy coupled with parallel factor (PARAFAC) analysis. PARAFAC analysis indicated that DOM in the LREW was dominated by three humic-like fluorescing components of terrestrial, microbial, and anthropogenic origin and a protein-like component. DOM composition was influenced by riparian land cover and hydrology, and shifted towards recently produced, low molecular weight DOM with low aromaticity as the percentage of agricultural land within riparian wetlands increased. During periods of high discharge and high baseflow, the DOM pool was dominated by recalcitrant and terrestrial-derived material but shifted towards protein-like and microbial-derived with increasing cropland in the riparian area. The results of this two-year study indicate that the replacement of forested riparian buffers with agricultural land can result in altered DOM composition which may affect carbon cycling and downstream water quality in agricultural watersheds.

Evaluation of miscanthus productivity and water use efficiency in southeastern United States.

Second generation biofuels, such as perennial grasses, have potential to provide biofuel feedstock while growing on degraded land with minimal inputs. Perennial grasses have been reported to sequester large amounts of soil organic carbon (SOC) in the Midwestern United States (USA). However, there has been little work on biofuel and carbon sequestration potential of perennial grasses in the Southeastern US. Biofuel productivity for dryland Miscanthus × gigantus and irrigated maize in Georgia, USA were quantified using eddy covariance observations of evapotranspiration (ET) and net ecosystem exchange (NEE) of carbon. Miscanthus biomass yield was 15.54 Mg ha-1 in 2015 and 11.80 Mg ha-1 in 2016, while maize produced 30.20 Mg ha-1 of biomass in 2016. Carbon budgets indicated that both miscanthus and maize fields lost carbon over the experiment. The miscanthus field lost 5 Mg C ha-1 in both 2015 and 2016 while the maize field lost 1.37 Mg C ha-1 for the single year of study. Eddy covariance measurement indicated that for 2016 the miscanthus crop evapotranspired 598 mm and harvest water use efficiencies ranged from 6.95 to 13.84 kg C ha-1 mm-1. Maize evapotranspired 659 mm with a harvest water use efficiency of 19.12 kg C ha-1 mm-1. While biomass yields and gross primary production were relatively high, high ecosystem respiration rates resulted in a loss of ecosystem carbon. Relatively low biomass production, low water use efficiency and high respiration for Miscanthus × gigantus in this experiment suggest that this strain of miscanthus may not be well-suited for dryland production under the environmental conditions found in South Georgia USA.

Landscape Effects on Solenopsis invicta (Hymenoptera: Formicidae) and Geocoris spp. (Hemiptera: Geocoridae), Two Important Omnivorous Arthropod Taxa in Field Crops.

The economically important brown stink bug, Euschistus servus (Say) (Hemiptera: Pentatomidae), is a native pest of many crops in southeastern United States and insecticide applications are the prevailing method of population suppression. To elucidate biological control of E. servus populations, we investigated two egg predators' (red imported fire ants, Solenopsis invicta Buren (Hymenoptera: Formicidae), and Geocoris spp. (Hemiptera: Geocoridae)) responses to both local and landscape factors that may have influenced their combined ability to cause mortality in immature E. servus. We estimated the density of fire ants and Geocoris spp. on four major crop hosts-maize, peanut, cotton, and soybean-in 16 landscapes over 3 yr in the coastal plain of Georgia, USA. Both Geocoris spp. and fire ant populations were concentrated on specific crops in this study, maize and soybean for Geocoris spp. and peanut and cotton for fire ants, but the percentage area of specific crops and woodland and pasture in the landscape and year also influenced their density in focal fields. The crop specific density of both taxa, the influence of the percentage area of specific crops and woodland in the landscape, and the variability in density over years may have been related to variable alternative resources for these omnivores in the habitats. Despite the variability over years, differential habitat use of fire ants and Georcoris spp. may have contributed to their combined ability to cause E. servus immature mortality.

Landscape Effects on Reproduction of Euschistus servus (Hemiptera: Pentatomidae), a Mobile, Polyphagous, Multivoltine Arthropod Herbivore.

Landscape factors can significantly influence arthropod populations. The economically important brown stink bug, Euschistus servus (Say) (Hemiptera: Pentatomidae), is a native mobile, polyphagous and multivoltine pest of many crops in southeastern United States and understanding the relative influence of local and landscape factors on their reproduction may facilitate population management. Finite rate of population increase (λ) was estimated in four major crop hosts-maize, peanut, cotton, and soybean-over 3 yr in 16 landscapes of southern Georgia. A geographic information system (GIS) was used to characterize the surrounding landscape structure. LASSO regression was used to identify the subset of local and landscape characteristics and predator densities that account for variation in λ. The percentage area of maize, peanut and woodland and pasture in the landscape and the connectivity of cropland had no influence on E. servus λ. The best model for explaining variation in λ included only four predictor variables: whether or not the sampled field was a soybean field, mean natural enemy density in the field, percentage area of cotton in the landscape and the percentage area of soybean in the landscape. Soybean was the single most important variable for determining E. servus λ, with much greater reproduction in soybean fields than in other crop species. Penalized regression and post-selection inference provide conservative estimates of the landscape-scale determinants of E. servus reproduction and indicate that a relatively simple set of in-field and landscape variables influences reproduction in this species.

Perennial Grass and Native Wildflowers: A Synergistic Approach to Habitat Management.

Marginal agricultural land provides opportunities to diversify landscapes by producing biomass for biofuel, and through floral provisioning that enhances arthropod-mediated ecosystem service delivery. We examined the effects of local spatial context (adjacent to woodland or agriculture) and irrigation (irrigation or no irrigation) on wildflower bloom and visitation by arthropods in a biofeedstocks-wildflower habitat buffer design. Twenty habitat buffer plots were established containing a subplot of Napier grass (Pennisetum perpureum Schumach) for biofeedstock, three commercial wildflower mix subplots, and a control subplot containing spontaneous weeds. Arthropods and flowers were visually observed in quadrats throughout the season. At the end of the season we measured soil nutrients and harvested Napier biomass. We found irrespective of buffer location or irrigation, pollinators were observed more frequently early in the season and on experimental plots with wildflowers than on weeds in the control plots. Natural enemies showed a tendency for being more common on plots adjacent to a wooded border, and were also more commonly observed early in the season. Herbivore visits were infrequent and not significantly influenced by experimental treatments. Napier grass yields were high and typical of first-year yields reported regionally, and were not affected by location context or irrigation. Our results suggest habitat management designs integrating bioenergy crop and floral resources provide marketable biomass and habitat for beneficial arthropods.

Assessing pesticide wet deposition risk within a small agricultural watershed in the Southeastern Coastal Plain (USA).

Pesticide volatilization and deposition with precipitation is widely documented and has been connected to adverse ecological impact. Here we describe a 3-yr study of current use and legacy pesticides in event-based rain samples within a 123-ha agricultural watershed. Crops in farm fields were documented quarterly with data used to estimate target compound use. The median number of pesticide detections in samples was 6. The fungicide, chlorothalonil which was used most intensively was detected in nearly all samples. It had the highest mean and peak concentrations with total deposition ≈0.1% of the estimated amount applied. The insecticide endosulfan also had relatively high use with behavior mirroring chlorothalonil. There was strong seasonal variation in concentration and depositional dynamics with the highest values measured during growing seasons. Similar behavior was observed with other compounds detected in rain samples with a general decrease in deposition and mean concentrations as use decreased. Comparison of measured concentrations to values associated with toxic impact on aquatic organisms indicated that chlorothalonil, endosulfan, chlorpyrifos, malathion and atrazine may contribute to adverse impact. The number of samples exceeding risk endpoints ranged from 1 to 77%. The highest value was for endosulfan; however its on-going phase-out is expected to reduce risks. Another finding was that the wet deposition of the herbicide, metolachlor exceeded measured runoff rates in the watershed by 5-fold. The study has demonstrated that localized pesticide wet deposition may present ecological risks and that volatilization and wet deposition is an important pesticide transport pathway at the local scale. Findings point to the need to include wet deposition in assessments of pesticide ecological risk and environmental fate.