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Abstract Winter oilseed Brassica plants have several documented allelochemicals; however, most literature revolves around the application of seed meal to fields, or the use of aerial parts of the plant. It is not clear if these chemicals interact with the surrounding environment to the same extent if the winter oilseeds are harvested as a cash crop in the spring. To determine this, we conducted a preliminary study bioassay using water extractable compounds from canola (Brassica napus L.) and pennycress (Thlaspi arvense L.) roots diluted to 25 and 50% (v/v). These four extracts, as well as deionized water for control, were used to irrigate plates with the seeds of soybean (Glycine max L.), Palmer amaranth [Amaranthus palmeri (S.) Watson], and mare's tail (Erigeron canadensis). We measured germination percent per plate and seedling radicle and hypocotyl lengths after 8 days of treatment. Mare's tail germination was lowered by 40% on day 4 by 50% pennycress extracts, and root length was stunted by both canola and pennycress extracts by 3–5 mm. Palmer amaranth root length was stunted by 10–15 mm by both species’ extracts, as well as shoots lengthened by 5–10 mm. Extract treatments did not affect soybean germination or growth. These interactions indicate potential for allelopathic interactions in the field following harvest of dual cropped winter oilseed and herbicide‐resistant weeds and warrant further study into the topic.

Woody biomass feedstock processing, including sorting, drying, and size reduction of biomass to provide standardized reactor-ready biomass to the biorefinery, is crucial to biofuel conversion. This study compares two comminution technology systems applied to woody biomass processing at a depot before being utilized for biofuel production at a biorefinery. The conventional comminution technology, known as the hammermill system, is compared with a rotary shear system developed by Forest Concepts™. Potential economic savings of using the new technology are evaluated by applying a deterministic and a stochastic partial capital budgeting model based on results from an experiment that processed chipped hybrid poplar chips and forest residues with both systems. The stochastic partial capital model estimates that savings will vary between approximately USD 28 and USD 42 per ton of reactor-ready processed biomass, with mean and median values around USD 34 per ton. It is 90% likely that savings will be between USD 30 and USD 39 per ton of reactor-ready processed biomass. The estimated savings are mainly due to differences in input (feedstock) to output (reactor-ready biomass) yields between technologies, affecting feedstock and drying costs.

The international aviation industry has the goal to gradually reduce carbon emissions mainly by using sustainable aviation fuel (SAF). However, currently SAF cannot be produced at competitive prices relative to petroleum-based jet fuel. Pennycress is a crop whose oilseed could be used as a relatively low-cost feedstock to produce SAF, potentially benefiting farmers and the environment. This stochastic techno-economic analysis (TEA) studies an enterprise buying pennycress oilseed from farmers, extracting the bio-oil and selling it to a biorefinery that converts bio-oil into SAF. Maximum buying prices (MBP)—prices that yield a zero net present value—the crushing enterprise could pay farmers for pennycress oilseed are estimated. To conduct the analysis, discount rates are estimated based on financial data of biofuel firms, thus providing a realistic benchmark to evaluate profitability and feedstock buying prices. Estimated risk-adjusted discount rates vary between 12 and 17%, above rates typically used in similar valuations. Estimated stochastic MBP range between 10.18 and 11.73 ¢ pound−1, which is below the price at which farmers are willing to plant pennycress, according to recent research. By considering the crushing facility’s inherent cash flow structure and risk, the distributions of stochastic modified internal rate of return suggest the crushing enterprise could be economically attractive at a 14% discount rate, our most likely estimate. However, between 11 and 17% times the cash flow model is simulated, the firm falls under financial distress. Overall, the findings suggest potential barriers for deployment of a SAF supply chain without governmental incentives or related policies.

Pennycress can be used as a renewable biomass because its harvested seeds can be converted into biofuel, supplying, for example the aviation industry. Pennycress can be adopted as a winter cover crop to make extra profit in addition to summer cash crops. This study ascertains influences on row crop farmers’ interest in growing pennycress to supply a biofuels industry. The study uses data from a survey of row-crop farmers in seven US states. Effects of farm and farmer attributes on acceptance of a farmgate pennycress price are measured. Nearly 58% were interested in growing pennycress if profitable. Among those interested, 54.4% would accept the farmgate pennycress price offered. Positive influences on interest included farm size, education, and familiarity with pennycress, while concern about knowledge on growing pennycress, and use of no-till practices had negative influences. Farmers aged 40 to 65 were more likely to accept the price, while share of rented hectares and no debt had positive influences. More risk-averse farmers and those using no-till were less likely to accept. Results suggest that the majority of row crop farmers would be interested in growing pennycress if profitable, while the overall willingness to accept the farmgate price was when it was at $0.28/kg.

Farmers may be reluctant to adopt variable rate nitrogen (VRN) management because of uncertain profits. This study assessed field landscape, soil, and weather effects on optical sensing (OS)-based VRN on cotton (Gossypium hirsutum L.) N rates, yields, and net returns (NRs). Field data were collected from 21 locations in Louisiana, Mississippi, Missouri, and Tennessee, USA, between 2011 and 2014. Data included yields, N rates, and NRs for the farmer practice (FP), OS-based VRN, and OS-based VRN supplemented with other information. Production data were augmented with landscape, soils, and weather data, and ANOVA and logistic regressions were used to identify field conditions where VRN was profitable, provided risk management benefits, and improved N efficiency. Key findings indicate that NRs were improved with VRN by applying additional N on more erodible soils. Higher organic matter soils also benefited from VRN through enhanced yields and NRs. VRN may also have provided risk management benefits by providing a lower probability of NRs below NRs for the FP on soils associated with greater water-holding capacity, higher organic matter levels, or deeper profiles. Results from this study may help identify farm fields with similar characteristics for adoption of VRN management.

We determined the value of soil test information for potassium (K) in upland cotton production using the linear response plateau (LRP) and linear response stochastic plateau (LRSP) functions. A stochastic dynamic programming model was used to determine the net present value to K fertilizer when optimal K was applied with knowledge about K carryover. Using K carryover information for K application decisions increased net present value and helped maintain steady levels of soil K. The LRSP function fit the data better than the LRP, and the value of soil testing was $27 ha-1 lower over ten years using the LRSP.

The purpose of this study was to determine the effects of three particle sizes of feedstock and two types of novel bale wraps on the quality of switchgrass by monitoring the chemical changes in cellulose, hemicellulose, lignin, extractives, and ash over a 225-day period. Using NIR (Near-infrared) modeling to predict the chemical composition of the treated biomass, differences were found in cellulose, lignin, and ash content across switchgrass bales with different particle sizes. Enclosing bales in a net and film impacted the cellulose, lignin, and ash content. Cellulose, hemicellulose, lignin, extractives, and ash were different across the 225-day storage period. A quadratic response function made better prediction about cellulose, lignin, and ash response to storage, and a linear response function best described hemicellulose and extractives response to storage. This study yields valuable information regarding the quality of switchgrass at different intervals between the start and end date of storage, which is important to conversion facilities when determining optimal storage strategies to improve quality of the biomass feedstock, based on potential output yield of a bale over time.

Factors influencing adoption of variable-rate nutrient management (VRM) and georeferenced precision soil sampling (PSS) for fertilizer management among cotton producers and the factors affecting awareness of and participation in cost-share programs encouraging the adoption of nutrient-management practices were analyzed using multivariate probit regression with sample selection. Data were collected from a fourteen-state cotton producer survey. Factors including farm size, operator age, and farm location were correlated with the adoption of VRM and PSS, awareness of cost-sharing programs, and program participation. The results may help agencies target farms with the specific attributes most likely to participate in cost-share programs.

The aim of this study was to determine the impact of incorporating switchgrass samples that have been in long term storage on the development of near-infrared (NIR) multivariate calibration models and their predictive capabilities. Stored material contains more variation in their respective spectral signatures due to chemical changes in the bales with storage time. Partial least squares (PLS) regression models constructed using NIR spectra of stored switchgrass possessed an instability that interfered with the correlation between the spectral data and measured chemical composition. The models were improved using calibration sample sets of equal parts stored and fresh switchgrass to more accurately predict the chemical composition of stored switchgrass. Acceptable correlation values (rcalibration) were obtained using a calibration sample set composed of 25 stored samples and 25 samples of fresh switchgrass for cellulose (0.91), hemicellulose (0.74), total carbohydrates (0.76), lignin (0.98), extractives (0.92), and ash (0.87). Increasing the calibration sample set to 100 samples of equal parts stored to senesced material resulted in statistically increased (p = 0.05) correlations for total carbohydrates (0.89) and ash (0.96). When these models were applied to a separate validation set (equal to 10% of the calibration sample set), high correlation coefficients (r) for predicted versus measured constituent content were observed for cellulose (0.94), total carbohydrates (0.98), lignin (0.91), extractives (0.97), and ash (0.90). For optimization of processing economics, the impact of feedstock storage must be investigated for implementation in conversion processes. While NIR is a well-known high-throughput technique for characterization of senesced switchgrass, the selection of appropriate calibration samples and consequent multivariate models must be taken into careful consideration for NIR application in a biomass storage facility for rapid chemical compositional determination.

This research analyzes the adoption patterns among cotton farmers for remote sensing, yield monitors, soil testing, soil electrical conductivity, and other precision agriculture technologies using a Multiple Indicator Multiple Causation regression model. Adoption patterns are analyzed using principle component analysis to determine natural technology groupings. Identified bundles are regressed on farm structure and operator characteristics. The propensity to adopt technology bundles was greater for producers managing relatively larger operations who used a variety of information sources to learn about precision farming, irrigated cotton, practiced crop rotation, and participated in working land conservation programs.

A 2009 survey of cotton farmers in twelve states collected information about the use of georeferenced precision soil testing (PST). Adoption of PST technology and the interval until retesting were examined with a Poisson hurdle regression. Survey data were calibrated using a post-stratification weighting protocol. Farming experience, farm size, land ownership, variable rate fertilizer management plans, and the use of soil electrical conductivity devices were correlated the with period until PST adopters retested soil. Understanding how producers perceive the useful life of soil-test information may be important for monitoring the effectiveness of best nutrient management practice adoption.

This study evaluates biorefinery bio-oil feedstock costs at the plant gate for a prospective field pennycress (Thlaspi arvense L.) to sustainable aviation fuel (SAF) supply chain. The biorefinery would supply SAF to the Nashville, Tennessee international airport. Supply chain activities include pennycress production, transporting oilseed to a crushing facility, processing of oilseed into bio-oil, and transporting bio-oil to the biorefinery. The analysis shows profit potential for economic agents in the prospective supply chain. Estimated breakeven cost (profit = 0) of growing, harvesting, and transporting oilseed to a crushing facility is 17.7 ¢ kg−1. A crushing facility can pay up to 23.8 ¢ kg−1 for pennycress oilseed during the first year of production and provide investors 12.5% annual rate of return. Therefore, a profit margin of up to 6.1 ¢ kg−1 is available for the crushing facility to induce prospective pennycress producers to supply oilseed for SAF production. However, the estimated profit margin was sensitive mainly to uncertain oilseed yields, changes in field production costs, and pennycress meal and bio-oil prices. A spatial biorefineries sitting model, the Biofuels Facility Location Analysis Modeling Endeavor, estimated that the least-cost supply chain configuration is to establish three crushing facilities located in Union City, Huntington, and Clarksville, TN, to supply bio-oil to the biorefinery, with the biorefinery sited in an industrial park about 24.14 km from the Nashville international airport aviation fuel storage. Estimated total costs of bio-oil at the biorefinery plant gate are between 83 and 109 ¢ kg−1 if crushing facility oilseed procurement costs are between 17.7 and 23.8 ¢ kg−1 for oilseed.

Adoption of precision agriculture technology has arrived considerable attention, but abandonment has received little. This paper identified factors motivating adoption and abandonment of precision soils sampling in cotton. Younger producers who farmed more cotton area, owned more of their cropland, planted more non-cotton area, or used a computer were more likely to adopt precision soil sampling. Those with more cotton area or who owned livestock were more likely to abandon, while those who used precision soil sampling longer, or used variable-rate fertilizer application were less likely to abandon precision soil sampling.

Farmers are concerned about the high cost of planting herbicide-resistant cotton with the high plant densities recommended for ultra-narrow-row cotton. This study evaluated the effects on net revenues of four herbicide-resistant technology fee policies used since 1996 by Monsanto, the technology license holder. Results indicate that changes in the technology fee policy by Monsanto have raised the cost of planting herbicide-resistant cotton. As a consequence, farmers may have an incentive to switch from ultra-narrow-row cotton to wide-row cotton and to use a lower plant density when the technology fee is tied to the seeding rate.

Research has evaluated the relative profitability of variable-rate (VRT) versus uniform-rate (URT) application of a single input in fields with multiple management zones. This study addresses map-based VRT decisions for multiple inputs in fields with multiple management zones. The decision-making framework is illustrated for nitrogen and water applied to irrigated cotton in fields with three management zones. Results suggest traditional methods of determining VRT application of a single input may by suboptimal if interactions exist among VRT inputs and URT inputs. Implications are that a systems approach to multiple-input VRT decisions can produce increased net returns to VRT.

By using a stochastic frontier framework, the mutual effect of input use on production risk and inefficiency is investigated. Disentangling this mutual effect proves important for empirical reasons, at least when applied to west Tennessee cotton systems grown after various cover crops. The most striking result is that the stochastic frontier model, when compared with a typical Just-Pope model, reorders the relative riskiness of cover-crop regimes associated with the cotton systems.

In recent years, bioenergy has become a promising renewable energy source that can potentially reduce the greenhouse emissions and generate economic growth in rural areas. Gaining understanding and controlling biomass chemical composition contributes to an efficient biofuel generation. This paper presents a principal component analysis (PCA) that shows the influence and relevance of selected controllable factors over the chemical composition of switchgrass and, therefore, in the generation of biofuels. The study introduces the following factors: (1) storage days; (2) particle size; (3) wrap type; and (4) weight of the bale. Results show that all the aforementioned factors have an influence in the chemical composition. The number of days that bales have been stored was the most significant factor regarding changes in chemical components due to its effect over principal components 1 and 2 (PC1 and PC2, approximately 80% of the total variance). The storage days are followed by the particle size, the weight of the bale and the type of wrap utilized to enclose the bale. An increment in the number of days (from 75–150 days to 225 days) in storage decreases the percentage of carbohydrates by −1.03% while content of ash increases by 6.56%.

Producers in southwest Oklahoma lack adequate information about optimal planting decisions for cotton. This study uses a cotton growth simulation model to evaluate alternative cultivar, planting date, irrigation, and harvest choices. Effects of using information about soil moisture at reproduction and revenue loss at harvest in making cultivar and planting data decisions are evaluated. Using soil temperature information to plant at an early date produced high net revenue some years, but reduced mean net revenue and increased risk. Producers maximizing expected net revenue should plant a short-season cultivar in late May and use soil moisture information to schedule irrigation at reproduction.

AbstractBackground:Phlegmonous gastritis is a rare and often fatal condition that can affect healthy individuals in 50% of cases. The condition has been described in accounts dating back to the pre-antibiotic era, during which time mortality was nearly 100%. Over the past century, case reports average about one per year. The etiology remains unclear, although Streptococcusspecies is isolated frequently. The optimum treatment has not been delineated clearly but likely involves a combination of antibiotics with or without surgical resection.Methods:A case report was presented and the pertinent literature was reviewed.Case Report:A 45-year-old man with a history of recent paranasal sinus surgery presented with acute abdominal pain and criteria consistent with toxic shock syndrome. Computed tomography scan showed diffuse thickening of the gastric wall and free intraperitoneal fluid. Exploratory laparotomy revealed a thickened stomach wall with outer fibrinous exudate and murky peritoneal fluid, which grew Streptococcuspyogenes. Intraoperative esophagogastroduodenoscopy revealed thickened gastric folds with a “cobblestone” appearance and no evidence of perforation. He was treated with antibiotics intravenously and sustained a difficult intensive care unit course complicated by ventilator-dependent respiratory failure, renal failure, and coagulopathy, but survived without major disability.Conclusions:This is an unusual case presentation of a rare but potentially lethal condition, whose optimal treatment is unclear. Phlegmonous gastritis should be considered when isolated gastric wall thickening is encountered in the clinical setting of toxic shock syndrome. [ABSTRACT FROM AUTHOR]

Abstract Watershed nutrient management often focuses on actions that reduce the movement of nitrogen (N) and phosphorus (P) from agricultural lands into streams. One area of management focus is the buffer of land adjacent to streams. Wetlands and forests in this buffer can intercept and retain N and P from the landscape. In addition to directly intercepting agricultural nutrients, natural habitats in the buffer can alter stream geomorphology and influence the in‐stream processing and transformation of N and P to less labile and mobile forms. Here, we assess the influence of buffer land cover on in‐stream processing of N and P. We measured nutrient dynamics in the water column and sediments of agricultural streams in the Fox River and Duck Creek watersheds (WI, USA) during the growing season. In these streams, water column processing was low, possibly due to a lack of primary producers in the water column. Water column P processing was weakly associated with wetland land cover in the buffer, but buffer land cover had no clear effect on inorganic N processing. On the other hand, sediments were almost always a source of inorganic P and a sink for inorganic N. Sediment P release was higher in streams with more agricultural land cover in the buffer. Sediments in streams with agricultural land cover in the buffer also removed more nitrate, even after accounting for the greater availability of nitrate in those streams. The buffer land cover conditions we quantified occupy a very small portion of the overall watershed (100 m wide, for 1 km upstream of the study site) but nevertheless appear to influence in‐stream cycling of N and P. For P management, reducing agricultural land cover in buffers is already a priority due to the ability of wetlands and forests to intercept nutrients, but this study suggests there may be some additional benefit due to changes in in‐stream P processing.

Chemical thinning, the most common and cost-effective thinning method, is conducted during early apple fruit development over a 3- to 4-week period using multiple applications of plant growth regulators. It is critical to provide apple growers with tools to assess the efficacy of chemical thinners quickly and accurately because visible responses are not apparent for up to 2 weeks after application. The objective of this study was to build a model to predict apple fruitlet abscission following a chemical thinner application with in situ reflectance data obtained with a portable visible and near infrared (Vis/NIR) spectrophotometer. Developed models were compared with the currently available fruitlet growth model (FGM). ‘Honeycrisp’ fruitlet diameter and reflectance were measured on dates around a chemical thinner application across a 2-year period. After June drop, measured fruitlets were determined to have either persisted or abscised. Random forest, partial least squares regression, and XGBoost classification models were used to predict fruitlet abscission from reflectance data. Each classification model was developed with 2021, 2022, and combined 2021 + 2022 data. For each dataset, 5-fold cross validation was used to assess three model performance metrics: 1) overall accuracy, 2) recall, and 3) specificity. Datasets tested were either unbalanced, majority class down-sampled, or minority class up-sampled with synthetic minority oversampling technique. In both years, the FGM reliably estimated chemical thinner efficacy 9 days after application. Before this time point, the FGM had low prediction accuracy of the minority class in both years—persisting fruitlets in 2021 and abscising fruitlets in 2022. For reflectance spectroscopy, the developed random forest models that were balanced with synthetic minority over-sampling technique were found to be the best combination in predicting chemical thinner efficacy. The combined 2021 + 2022 dataset overall model accuracy ranged from 84% the day before to 93% at 9 days after thinner application. These results show that Vis/NIR is a promising tool to predict chemical thinner efficacy. This technology had high prediction accuracies over a range of fruitlet abscission potential and two growing seasons. Further development and testing of the model over cultivars, chemical thinner timings, and growing regions would facilitate commercialization of the technology.

Multistep chemical thinning programs have been widely recommended in the eastern United States; however, adoption of bloom thinners is limited. With caustic blossom thinners, narrow effective application timings and concerns related to spring frost damage are barriers for commercial use in this region. If effective and safe, use of hormonal blossom thinners for apple would be an attractive alternative. We evaluated the effects and interactions of bloom thinners [6-benzyladenine (BA) and lime sulfur (LS, or calcium polysulfide) + stylet oil (LS+SO)] and a postbloom thinner (NAA) in the context of a multistep, carbaryl-free thinning program across three locations. Experiments were conducted in 2017 and 2018 on mature ‘Gala’ in North Carolina, Massachusetts, and Pennsylvania, USA. In four of six studies, BA at bloom increased the efficacy of postbloom NAA and reduced crop density (P < 0.08). Postbloom NAA generally increased fruit relative growth rate (RGR) and reduced crop density. However, where NAA failed to reduce crop load, there was a negative influence on RGR. BA and LS+SO increased RGR in one of six studies; however, BA was generally ineffective as a blossom thinner, whereas LS+SO was more effective. Nevertheless, BA applied at bloom may have utility as part of a multistep thinning program. As a part of a multistep thinning program, BA applied at bloom may be useful in increasing efficacy of postbloom applications, particularly when use of caustic blossom thinners is not permitted.

AbstractThe open waters of large lakes can sometimes become so depleted in important metals that phytoplankton communities become either growth limited or limited in some metabolic function. Metals such as Fe, Ni, Mo, and Zn are used as co-factors for enzymes by phytoplankton in core metabolic functions, as well as metabolic pathways that allow phytoplankton to use less preferred forms of N and P (e.g. nitrates, urea, and organic phosphorus). In the Laurentian Great Lakes, metal limitation has been observed primarily in waters that are isolated from tributary inputs and sediment exchange. These are situations where the supply of metals is very low relative to demand. We hypothesized that another situation where metal limitation could occur is within algal blooms, where the demand for metals is high because preferred forms of N and P are often low or absent and the phytoplankton biomass is extremely high. As a preliminary test of this hypothesis, we performed seven laboratory incubation experiments on naturally occurring phytoplankton communities from two nearshore habitats that frequently experience blooms (Green Bay in Lake Michigan and Maumee Bay in Lake Erie). Metals and labile nutrients (inorganic N and P) were often present at low concentrations or below the method detection limit. Amendments of inorganic N (5 experiments) and P (1 one experiment) resulted in increased chlorophyll in laboratory incubations, but metal amendments alone never appeared to stimulate growth. Although we attempted to sample during conditions when we hypothesized metal limitation would be most likely, we cannot rule out the possibility that metal limitation is occurring at other times in these eutrophic nearshore areas. Further, metal availability could affect other aspects of the phytoplankton community, such as the production of cyanotoxins or the interactions between different phytoplankton taxa.

Apple (Malus ×domestica) growers can incur significant economic losses when fruit drop before they can be harvested [preharvest fruit drop (PFD)]. In some years and cultivars, more than 30% of potential yield can be lost. Growers frequently apply plant bioregulators to reduce PFD, either via delay in maturity [aminoethoxyvinylglycine (AVG), 1-methylcycolpropene] or via inhibition in production of cell hydrolysis enzymes in the fruit pedicel [naphthalene acetic acid (NAA)]. Finding a physiological indicator of PFD would allow growers to assess the susceptibility of fruit to PFD. Due to its lignification, xylem is believed to be the last tissue to break down in the fruit pedicel, leading to PFD. To determine whether loss in xylem functionality can be used as an indicator of PFD potential, studies were conducted in 2020 and 2021 with ‘Red Delicious’ treated with AVG (132 µL·L−1), NAA (10 µL·L−1), and an ethylene-producing compound [ethephon (150 µL·L−1 in 2020, 200 µL·L−1 in 2021)] to generate a range of PFD potentials. Xylem functionality was assessed in the fruit cortex. Internal ethylene content (IEC), fruit maturity indices, and PFD rates were quantified weekly throughout the harvest period. Expression of genes encoding for cell hydrolysis enzymes (MdEG1 and MdPG2) was quantified to relate xylem functionality to fruit abscission mechanisms. In 2020 and 2021, AVG reduced PFD compared with the untreated control by decreasing IEC. Although ethephon did not result in higher PFD than untreated fruit, NAA reduced PFD in 2020 but not 2021. For all treatments in both years, there was a linear decrease in xylem functionality throughout the measurement period. Cumulative PFD exponentially decreased as xylem functionality neared zero and the climacteric rise in ethylene began. Concurrent with the rise in IEC and PFD was an increase in the expression of MdEG1 and MdPG2 in the fruit pedicel of the control compared with AVG-treated fruit. AVG-treated fruit lost xylem functionality at a similar rate to the untreated control but had lower expression of MdEG1 and MdPG2. These results indicate that xylem functionality is not a sole direct indicator of PFD. The concurrent increase in PFD and expression of MdEG1/MdPG2 supports previous research indicating that these two genes may serve as potential markers for PFD.

Carbohydrates play a key role in apple fruit growth and development. Carbohydrates are needed for cell division/expansion, regulate fruitlet abscission, and influence fruit maturation and quality. Current methods to quantify fruit carbohydrates are labor intensive and expensive. We quantified carbohydrates throughout a growing season in two cultivars and evaluated the use of near infrared spectroscopy (NIR) to predict apple carbohydrate content throughout changes in fruit development. Carbohydrates were quantified with high performance liquid chromatography (HPLC) at five timepoints between early fruitlet growth and harvest in ‘Gala’ and ‘Red Delicious’ apples. NIR spectra was collected for freeze-dried fruit samples using a benchtop near infrared spectrometer. Sorbitol was the major carbohydrate early in the growing season (~40% of total carbohydrates). However, the relative contribution of sorbitol to total carbohydrates rapidly decreased by 59 days after full bloom (r2 ranged from 0.60 to 0.96. These results show that NIR can accurately estimate carbohydrates throughout the growing season and offers an efficient alternative to liquid or gas chromatography.

Abstract Since the early 2000s, Lake Erie has been experiencing annual cyanobacterial blooms that often cover large portions of the western basin and even reach into the central basin. These blooms have affected several ecosystem services provided by Lake Erie to surrounding communities (notably drinking water quality). Several modeling efforts have identified the springtime total bioavailable phosphorus (TBP) load as a major driver of maximum cyanobacterial biomass in western Lake Erie, and on this basis, international water management bodies have set a phosphorus (P) reduction goal. This P reduction goal is intended to reduce maximum cyanobacterial biomass, but there has been very limited effort to identify the specific locations within the western basin of Lake Erie that will likely experience the most benefits. Here, we used pixel‐specific linear regression to identify where annual variation in spring TBP loads is most strongly associated with cyanobacterial abundance, as inferred from satellite imagery. Using this approach, we find that annual TBP loads are most strongly associated with cyanobacterial abundance in the central and southern areas of the western basin. At the location of the Toledo water intake, the association between TBP load and cyanobacterial abundance is moderate, and in Maumee Bay (near Toledo, Ohio), the association between TBP and cyanobacterial abundance is no better than a null model. Both of these locations are important for the delivery of specific ecosystem services, but this analysis indicates that P load reductions would not be expected to substantially improve maximum annual cyanobacterial abundance in these locations. These results are preliminary in the sense that only a limited set of models were tested in this analysis, but these results illustrate the importance of identifying whether the spatial distribution of management benefits (in this case P load reduction) matches the spatial distribution of management goals (reducing the effects of cyanobacteria on important ecosystem services).

Abstract Water level (WL) fluctuations substantially alter the fauna, flora, and microbial community of nearshore aquatic ecosystems. Water level management therefore has the potential to strongly influence a wide variety of ecosystem processes. Many northern temperate lake food webs experience substantial methylmercury contamination, which is partially mediated by the action of sulfate‐reducing bacteria occurring in sediments that are periodically inundated. For lakes with elevated methylmercury, WL management could be designed to reduce methylmercury contamination. At the lake scale, this concept is supported by studies that identified statistical associations between fish mercury content and water level (WL) fluctuations. Here, we compiled a long‐term dataset (1997–2015) of mercury content in young‐of‐year Yellow Perch (Perca flavescens) from six lakes on the border of the United States and Canada and examined whether mercury content was associated with WL fluctuation. Many WL metrics covary and appear to have strong associations with Yellow Perch mercury. However, these associations appear to vary by lake, and lake‐specific models are needed to identify relationships between WL fluctuation and Yellow Perch mercury content. We used partial least‐squares regression (PLSR) to identify the associations between Yellow Perch mercury content and WL metrics, temperature, and annual deposition data for lakes in northern Minnesota. These PLSR models not only showed some variation among lakes, but also supported strong associations between WL fluctuations and annual variation in Yellow Perch mercury content. The study lakes underwent a change in WL management in 2000, when winter WL minimums were increased by about 1 m in five of the six study lakes, which reduced annual WL fluctuation on those lakes. Using the PLSR models, we estimated how this change in WL management would have affected Yellow Perch mercury content. In four of the five study lakes in which annual WL fluctuation was reduced in 2000, the change in WL management likely reduced Yellow Perch mercury content, relative to the previous WL management regime.

Similarity in community composition declines as distance between locations increases, a phenomenon that has been observed in a wide variety of freshwater, marine and terrestrial ecosystems. One driver of the distance-similarity relationship is the presence of environmental gradients that alter the suitability of sites for particular species. Although some environmental gradients, such as geology, do not change on a year-to-year basis, others, such as temperature, vary annually and over longer time periods. Here, we used a 21-year dataset of fish communities in the upper Mississippi River to examine the effect of distance on variation in community composition and to assess whether the effect of distance is primarily due to its effect on thermal regime. Because the Mississippi River is aligned mostly north-to-south, larger distances along the river roughly correspond to larger differences in latitude and therefore thermal regime. As expected, there was a moderate distance-similarity relationship, suggesting greater distance leads to less similarity. The effect of distance appeared to increase slightly over time. Using a subset of data for which air temperature was available, we compared models that incorporated both difference among sites in degree days (a surrogate for thermal regime) and physical distance (river km). Although physical distance presumably incorporates more environmental gradients than just temperature (and other potential mechanisms), temperature alone appears to be more strongly associated with differences in the Mississippi River fish community than distance.

Water level (WL) fluctuations in lakes influence many aspects of ecosystem processes. Concern about the potential impact of WL fluctuations on fisheries was one of the factors that motivated the decision in 2000 to alter the management of WL in the Rainy-Namakan reservoir complex (on the border between the U.S. state of Minnesota and the Canadian province of Ontario). We used a Before-After, Control-Impact (BACI) framework to identify potential impacts of the change in WL management to Walleye, Northern Pike and Yellow Perch catch per unit effort (CPUE). The CPUE of these species from 1990-1999 and from 2005-2014 were compared in four impact lakes (Lake Kabetogama, Namakan Lake, Rainy Lake and Sand Point Lake) and two control lakes (Lake of the Woods and Lake Vermilion) using a simple Bayesian model. Changes in fish CPUE in the impact lakes were often similar to changes that occurred in at least one control lake. The only change that was not similar to changes in control lakes was an increase of Yellow Perch in Lake Kabetogama. The two control lakes often differed substantially from each other, such that if only one had been available our conclusions about the role of WL management on fisheries would be very different. In general, identifying cause-and-effect relationships in observational field data is very difficult, and the BACI analysis used here does not specify a causative mechanism, so co-occurring environmental and management changes may obscure the effect of WL management.

Freshwater mussels are ecologically and economically important members of many aquatic ecosystems, but are globally among the most imperiled taxa. Propagation techniques for mussels have been developed and used to boost declining and restore extirpated populations. Here we use a cohort of propagated mussels to estimate the intrinsic variability in size and growth rate of Lampsilis siliquoidea (a commonly propagated species). Understanding the magnitude and pattern of variation in data is critical to determining whether effects observed in nature or experimental treatments are likely to be important. The coefficient of variation (CV) of L. siliquoidea soft tissues (6.0%) was less than the CV of linear shell dimensions (25.1-66.9%). Size-weight relationships were best when mussel width (the maximum left-right dimension with both valves appressed) was used as a predictor, but 95% credible intervals on these predictions for soft tissues were ∼145 mg wide (about 50% of the mean soft tissue mass). Mussels in this study were treated identically, raised from a single cohort and yet variation in soft tissue mass at a particular size class (as determined by shell dimensions) was still high. High variability in mussel size is often acknowledged, but seldom discussed in the context of mussel conservation. High variability will influence the survival of stocked juvenile cohorts, may affect the ability to experimentally detect sublethal stressors and may lead to incongruities between the effects that mussels have on structure (via hard shells) and biogeochemical cycles (via soft tissue metabolism). Given their imperiled status and longevity, there is often reluctance to destructively sample unionid mussel soft tissues even in metabolic studies (e.g., studies of nutrient cycling). High intrinsic variability suggests that using shell dimensions (particularly shell length) as a response variable in studies of sublethal stressors or metabolic processes will make confident identifications of smaller effect sizes difficult.

Spatial variation in food resources strongly influences many aspects of aquatic consumer ecology. Although large-scale controls over spatial variation in many aspects of food resources are well known, others have received little study. Here we investigated variation in the fatty acid (FA) composition of seston and primary consumers within (i.e., among habitats) and among tributary systems of Lake Michigan, USA. FA composition of food is important because all metazoans require certain FAs for proper growth and development that cannot be produced de novo, including many polyunsaturated fatty acids (PUFAs). Here we sampled three habitat types (river, rivermouth and nearshore zone) in 11 tributaries of Lake Michigan to assess the amount of FA in seston and primary consumers of seston. We hypothesize that among-system and among-habitat variation in FAs at the base of food webs would be related to algal production, which in turn is influenced by three land cover characteristics: 1) combined agriculture and urban lands (an indication of anthropogenic nutrient inputs that fuel algal production), 2) the proportion of surface waters (an indication of water residence times that allow algal producers to accumulate) and 3) the extent of riparian forested buffers (an indication of stream shading that reduces algal production). Of these three land cover characteristics, only intense land use appeared to strongly related to seston and consumer FA and this effect was only strong in rivermouth and nearshore lake sites. River seston and consumer FA composition was highly variable, but that variation does not appear to be driven by the watershed land cover characteristics investigated here. Whether the spatial variation in FA content at the base of these food webs significantly influences the production of economically important species higher in the food web should be a focus of future research.

Terrestrial agricultural activities strongly influence riverine nitrogen (N) dynamics, which is reflected in the δ(15)N of riverine consumer tissues. However, processes within aquatic ecosystems also influence consumer tissue δ(15)N. As aquatic processes become more important terrestrial inputs may become a weaker predictor of consumer tissue δ(15)N. In a previous study, this terrestrial-consumer tissue δ(15)N connection was very strong at river sites, but was disrupted by processes occurring in rivermouths (the 'rivermouth effect'). This suggested that watershed indicators of N loading might be accurate in riverine settings, but could be inaccurate when considering N loading to the nearshore of large lakes and oceans. In this study, the rivermouth effect was examined on twenty-five sites spread across the Laurentian Great Lakes. Relationships between agriculture and consumer tissue δ(15)N occurred in both upstream rivers and at the outlets where rivermouths connect to the nearshore zone, but agriculture explained less variation and had a weaker effect at the outlet. These results suggest that rivermouths may sometimes be significant sources or sinks of N, which would cause N loading estimates to the nearshore zone that are typically made at discharge gages further upstream to be inaccurate. Identifying definitively the controls over the rivermouth effect on N loading (and other nutrients) will require integration of biogeochemical and hydrologic models.