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The emerging sectors of agriculture, such as organics, urban, and local food, tend to be dominated by farms that are smaller, more transient, more diverse, and more dispersed than the traditional farms in the rural areas of the United States. As a consequence, a list frame of all farms within one of these sectors is difficult to construct and, even with the best of efforts, is incomplete. The United States Department of Agriculture’s (USDA’s) National Agricultural Statistics Service (NASS) maintains a list frame of all known and potential U.S. farms and uses this list frame as the sampling frame for most of its surveys. Traditionally, NASS has used its area frame to assess undercoverage. However, getting a good measure of the incompleteness of the NASS list frame using an area frame is cost prohibitive for farms in these emerging sectors that tend to be located within and near urban areas. In 2016, NASS conducted the Local Food Marketing Practices (LFMP) survey. Independent samples were drawn from (1) the NASS list frame and (2) a web-scraped list of local food farms. Using these two samples and capture–recapture methods, the total number and sales of local food operations at the United States, regional, and state levels were estimated. To our knowledge, the LFMP survey is the first survey in which a web-scraped list frame has been used to assess undercoverage in a capture–recapture setting to produce official statistics. In this article, the methods are presented, and the challenges encountered are reviewed. Best practices and open research questions for conducting surveys using web-scraped list frames and capture–recapture methods are discussed.

Crop forecasting is important to national and international trade and food security. Although sample surveys continue to have a role in many national crop forecasting programs, the increasing challenges of list frame undercoverage, declining response rates, increasing response burden, and increasing costs are leading government agencies to replace some or all of survey data with data from other sources. This article reviews the primary approaches currently being used to produce official statistics, including surveys, remote sensing, and the integration of these with meteorological, administrative, or other data. The research opportunities for improving current methods of forecasting crop yield and quantifying the uncertainty associated with the prediction are highlighted.

The United States Department of Agriculture’s National Agricultural Statistics Service (NASS) has the responsibility of quantifying the nation’s agricultural production. Historically, it has focused on large production agriculture. With interest and activity increasing in urban areas, NASS has begun exploring how to better quantify urban agriculture. This segment of agriculture is particularly challenging to enumerate because the agricultural holdings tend to be small, diverse, widely dispersed, and more transient than the predominantly large farms in rural areas. In collaboration with the Multi-Agency Collaboration Environment (MACE), a new approach to list building was explored in a pilot study conducted in the City of Baltimore, Maryland. Using a big data approach, areas of potential agricultural activity were identified by gathering information (state and local permits, Facebook and twitter feeds, interest groups, etc.) via the web. A sample was drawn from the list, and an in-person survey was conducted to assess whether or not the identified areas had agricultural activity. The results of the pilot study are presented. Lessons learned from the study and next steps are discussed.

The United States Department of Agriculture’s National Agricultural Statistics Service (NASS) has the responsibility of quantifying the nation’s agricultural production. Historically, it has focused on large production agriculture. With interest and activity increasing in urban areas, NASS has begun exploring how to better quantify urban agriculture. This segment of agriculture is particularly challenging to enumerate because the agricultural holdings tend to be small, diverse, widely dispersed, and more transient than the predominantly large farms in rural areas. In collaboration with the Multi-Agency Collaboration Environment (MACE), a new approach to list building was explored in a pilot study conducted in the City of Baltimore, Maryland. Using a big data approach, areas of potential agricultural activity were identified by gathering information (state and local permits, Facebook and twitter feeds, interest groups, etc.) via the web. A sample was drawn from the list, and an in-person survey was conducted to assess whether or not the identified areas had agricultural activity. The results of the pilot study are presented. Lessons learned from the study and next steps are discussed.

The United States Department of Agriculture’s National Agricultural Statistics Service (NASS) conducts the June Agricultural Survey (JAS) annually. Substantial misclassification occurs during the prescreening process and from field-estimating farm status for nonresponse and inaccessible records, resulting in a biased estimate of the number of US farms from the JAS. Here, the Annual Land Utilization Survey (ALUS) is proposed as a follow-on survey to the JAS to adjust the estimates of the number of US farms and other important variables. A three-phase survey design-based estimator is developed for the JAS-ALUS with nonresponse adjustment for the second phase (ALUS). A design-unbiased estimator of the variance is provided in explicit form.

The United States Department of Agriculture’s National Agricultural Statistics Service (NASS) conducts the June Agricultural Survey (JAS) annually. Substantial misclassification occurs during the prescreening process and from field-estimating farm status for nonresponse and inaccessible records, resulting in a biased estimate of the number of US farms from the JAS. Here, the Annual Land Utilization Survey (ALUS) is proposed as a follow-on survey to the JAS to adjust the estimates of the number of US farms and other important variables. A three-phase survey design-based estimator is developed for the JAS-ALUS with nonresponse adjustment for the second phase (ALUS). A design-unbiased estimator of the variance is provided in explicit form.

Understanding current residential irrigation behaviors is essential for selecting the most effective conservation measures and determining which customers should be targeted for conservation outreach programs. This study stratified single-family residential customers without access to reuse water into irrigating groups. Irrigation demands were calculated using monthly total (indoor and outdoor combined) water billing and parcel records for more than 165,000 customers in southwest Florida over approximately 10 years. Gross irrigation required (GIR) was calculated using parcel and high-resolution site data. Seven-and-a-half percent of customers used no irrigation over the study period, 67% of customers used 1 in./month or less, and 84% used less than the average monthly GIR of 2.2 in./month. Eighty-five percent of customers were classified as occasional irrigators, whereas only 2% were classified as high irrigators. With such low estimated irrigation demands, this study reinforces the importance of selecting conservation methods so as to not inadvertently increase irrigation.

Purpose Totally implantable venous access systems (ports) are commonly placed and have a low complication rate. The most common complication is infection, which can have very negative effects on patients resulting in hospitalization and/or treatment delay in the setting of neoplasm. While a number of variables have been studied in relation to diminishing infectious rates, one remaining question is the effect of accessing the port on day of placement, which is the aim of this retrospective study.Materials and methods After internal review board approval the electronic medical records of 2,006 patients who underwent port placement between 10/1/2008 and 9/30/2013 were reviewed. Of these patients 628 were excluded as they did not have complete placement and removal data available, leaving 1378 patients in our cohort.Results There was a significantly longer number of infection-free catheter days in the out-patient cohort as compared to the in-patient cohort (p = 0.027). In-patients mean day after placement when the port was first accessed (DAP) (0.5) was statistically earlier (closer to placement) than the out-patients DAP (7.2) (p<0.0001). However, the increased likelihood of infection could not be explained by DAP (p = 0.2029) even when controlling for in-patient and out-patient status (p = 0.97).Conclusions Accessing the port on the day of placement does not significantly contribute to an increased likelihood of infection. This study seems to indicate that placing a port on the first day of outpatient therapy likely optimally balances respect for patient time with infection control.

Agroforestry, the deliberate integration of trees into agricultural operations, sequesters carbon (C) while providing valuable services on agricultural lands. However, methods to quantify present and projected C stocks in these open‐grown woody systems are limited. As an initial step to address C accounting in agroforestry systems, a spatial Markov random field model for predicting the natural logarithm (log) of the mean aboveground volume of green ash (Fraxinus pennsylvanicaMarsh.) within a shelterbelt, referred to as the log of aboveground volume, was developed using data from an earlier study and web‐available soil and climate information. Windbreak characteristics, site, and climate variables were used to model the large‐scale trend of the log of aboveground volume. The residuals from this initial model were correlated among sites up to 24 km from a point of interest. Therefore, a spatial dependence parameter was used to incorporate information from sites within 24 km into the prediction of the log of the aboveground volume. Age is an important windbreak characteristic in the model. Thus, the log of aboveground volume can be predicted for a given windbreak age and for values of other explanatory variables associated with a site of interest. Such predictions can be exponentiated to obtain predictions of aboveground volume for windbreaks without repeated inventory. With the capability of quantifying uncertainty, the model has the potential for large regional planning efforts and C stock assessments for many deciduous tree species used in windbreaks and riparian buffers once it is calibrated.

Interviews with Pamela Allenstein, North American Plant Collections Consortium (NAPCC) manager, and Andrew Bunting, NAPCC Standing Committee chairman, are presented. Allenstein says that they continue to recruit collections and in 2007, they have added 28 collections and 15 gardens. Bunting explains that their association with Scott Arboretum has helped established their dedication to the care and management of the collections. Allenstein cites that in the future, they want to expand the number of collection holders, particularly those underrepresented.

Poststroke depression (PSD) is common among stroke survivors, and it is associated with worse functional outcomes and increased poststroke mortality. Limited information is available about its impact on healthcare use. This study assessed the impact of PSD on healthcare use by veterans with acute stroke.

Irrigation of the mastoid with a quinolone antibiotic-steroid solution may mitigate hearing loss caused by iatrogenic semicircular canal injury in the presence of Pseudomonas aeruginosa(PA) otitis media (OM).

Abstract.: Sequential tests to decide among three binomial probabilities are needed in many situations, such as acceptance sampling used to determine the proportion of defective items and presence and absence sampling to decide whether pest species are causing economic damage to a crop such as corn. Approximate error probabilities associated with Armitage's (1950, JRSS B) method of simultaneously conducting three sequential probability ratio tests (SPRTs) are derived for the binomial distribution. These approximations provide a basis for adjusting the error rates used to establish the individual SPRTs so that the desired overall error rates are attained. Monte Carlo simulation is used to evaluate the revised procedure.

We obtain bounds for the difference between the median and mean of the beta and negative binomial distributions using elementary methods.

A large sample approximation of the least favorable configuration for a fixed sample size selection procedure for negative binomial populations is proposed. A normal approximation of the selection procedure is also presented. Optimal sample sizes required to be drawn from each population and the bounds for the sample sizes are tabulated. Sample sizes obtained using the approximate least favorable configuration are compared with those obtained using the exact least favorable configuration. Alternate form of the normal approximation to the probability of correct selection is also presented. The relation between the required sample size and the number of populations involved is studied.

In most instances referees are indicated at the end of each paper which they referee. The help of the following individuals who have refereed papers for this journal is hereby acknowledged. Individuals who refereed papers which were handled during the period covered by Issues 1 through 4 of this volume are included in this list. The Editors wish to express their thanks to all of these.

The European corn borer, Ostrinia nubilalis (Hübner), causes economic damage to corn, Zea mays L., throughout the Corn Belt. Because this insect has become the primary target of Bacillus thuringiensis Berliner (Bt) transgenic corn, current efforts addressing the management of O. nubilalis resistance to Bt corn require information on adult European corn borer dispersal and factors affecting its dispersal. In 1998 we conducted mark-release-recapture, release-recapture, and caged-mating studies to directly measure and compare local dispersal patterns of O. nubilalis adults within and proximal to irrigated and non-irrigated cornfields. Releases of marked adults were made corresponding to the first and second flight of O. nubilalis in eastern Nebraska. Adult dispersal was significantly different between irrigated and non-irrigated cornfields. Released adults tended to remain in and near irrigated cornfields, but dispersed out of and away from non-irrigated cornfields. When released at the edge of the cornfield, neither male nor unmated female O. nubilalis displayed an initial tendency to move out of irrigated corn and into the mixed smooth bromegrass (Bromus inermis Leyss) and broadleaf-weed field edge. Mating efficiency in a late-season cornfield was not significantly different than in dense foxtail (Setaria spp.). Generally, we found that adult O. nubilalis dispersal may vary depending on variables such as action-site availability and agronomic practices and their interaction with O. nubilalis life history.

The European corn borer, Ostrinia nubilalis (Hübner), causes economic damage to corn, Zea mays L., throughout the Corn Belt. Because this insect has become the primary target of Bacillus thuringiensis Berliner (Bt) transgenic corn, current efforts addressing the management of O. nubilalis resistance to Bt corn require information on adult European corn borer dispersal and factors affecting its dispersal. In 1998 we conducted mark-release-recapture, release-recapture, and caged-mating studies to directly measure and compare local dispersal patterns of O. nubilalis adults within and proximal to irrigated and non-irrigated cornfields. Releases of marked adults were made corresponding to the first and second flight of O. nubilalis in eastern Nebraska. Adult dispersal was significantly different between irrigated and non-irrigated cornfields. Released adults tended to remain in and near irrigated cornfields, but dispersed out of and away from non-irrigated cornfields. When released at the edge of the cornfield, neither male nor unmated female O. nubilalis displayed an initial tendency to move out of irrigated corn and into the mixed smooth bromegrass (Bromus inermis Leyss) and broadleaf-weed field edge. Mating efficiency in a late-season cornfield was not significantly different than in dense foxtail (Setaria spp.). Generally, we found that adult O. nubilalis dispersal may vary depending on variables such as action-site availability and agronomic practices and their interaction with O. nubilalis life history.

The spatial pattern and probability distribution of Mexican bean beetle, Epilachna varivestis Mulsant, egg masses were studied in four dry bean, Phaseolus vulgaris L., fields near Scottsbluff, NE, during the 1994 and 1995 growing seasons. Sampling was conducted in a regular and uniform grid to guarantee coverage of the field. The experimental unit in all fields was 0.30 row-m, and five measurements were made at 0.76-m intervals. A total of 12,290 locations was sampled. Geostatistics and discrete statistics were used to describe the egg mass distribution. Regression was used to detect and separate macroscale trends from the microscale variation. The presence of macroscale variation indicated a significant edge effect with ovipositing females moving into dry bean fields from their overwintering sites. The microscale variation estimated from the estimated residuals from regressions to estimate trends was studied using semivariograms for all fields. Semivariograms strongly indicate that Mexican bean beetle eggs are randomly distributed across the field and that this random distribution holds across 10-fold differences in population densities. As a result of the significant macroscale trends observed, we conclude that egg mass densities may be greater in areas of the field near edges adjacent to beetle overwintering sites. The probability distribution that best fit the data was the negative binomial. Our results illustrate the importance of scale in discussing and characterizing distribution. Although there is evidence of edge effect at the field level, there is no evidence of spatial dependence between egg samples at the sampling region level. At an even lower level, the egg mass itself, eggs are aggregated.

Field studies were designed to more clearly determine how adult western corn rootworm, Diabrotica virgifera virgifera LeConte, population distribution patterns are altered over time by changes and contrasts in corn (Zea mays L.) plant phenology using whole-plant beetle counts as the sampling tool. In 1994, studies were conducted in a model system consisting of a late-planted corn strip placed in the middle of an early-planted cornfield. The system was replicated over three fields. Large-scale variation was modeled using trend-surface regression analysis to describe the relationship between beetle counts and distance from the center of the late-planted strip. In each field, the beetle distribution became greatly skewed toward the late-planted strip when the strip was either in the tassel or silk stage and the surrounding field was = blister stage. In 1995, studies were conducted in and at the interface of two adjacent cornfields that were planted 9 d apart. Count data were analyzed to quantify population density changes at different sampling locations within and among fields over time as crop phenology changed. Rapid positive or negative changes in beetle densities occurred within and among fields as contrasts in corn phenology changed. In both years, the stability of the beetle distribution was strongly influenced by the length of time that a contrast in plant phenology was maintained between adjacent patches of corn. Directional movements of beetles toward pollinating corn and associated semiochemicals could be inferred from both 1994 and 1995 data analyses. Data suggest that contrasts in crop phenology at the interface and among cornfields should be considered when developing beetle sampling programs and interpreting scouting data to improve the accuracy of rootworm management decisions.

Field studies were conducted in 1994 and 1995 to characterize the spatial distribution of western corn rootworm, Diabrotica virgifera virgifera LeConte, adults in field corn using whole-plant counts as the sampling tool. Geostatistical methods were used to determine the small-scale spatial relationships of adults within fields during different corn phenology periods and as beetle population densities changed. Because the focus was on small-scale spatial variation, trend surface regression methods were used to remove large-scale variation. Geostatistical analysis of whole-plant count data indicated that no small-scale spatial correlation was present among samples taken > 5.3 m apart in 5 of 55 semivariograms that were plotted. The 3 significant small-scale spatial relationships occurred around peak pollination periods, and during this time, samples were spatially dependent at distances of <30–40 m apart. No small-scale spatial correlation was detected during other growth stages. The small-scale spatial patterns detected also appeared to be independent of beetle density within the range of densities (0.1–5.0 beetles per plant) that were sampled. Data suggest that beetle spatial patterns can be affected by changes in crop phenology. Contrasts in corn phenology within and among fields should be considered when developing sampling programs based on visual beetle counts.

This research investigated parasitism of the buffalograss mealybugs Tridiscus sporoboli (Cockerell) and Trionymus sp. by Rhopus nigroclavatus (Ashmead) through rearing and dissection studies, paired comparison tests, and a field survey. Rates of parasitism reported in this article reflect combined parasitism of the 2 mealybug species. In the rearing study, parasitism of adult female mealybugs by R. nigroclavatus was 48.6%, with an average emergence of 1.77 parasitoids per parasitized mealybug. A maximum of 7 R. nigroclavatus adults emerged from a single mealybug female. Mealybug dissections documented parasitism rates by R. nigroclavatus of 78.5, 67.5, and 4.3%, respectively, for adult females, 3rd and 4th (male pupae) instars, and 1st- and 2nd-instar mealybugs. Results revealed the preference of R. nigroclavatus for adult female mealybugs and later instars, and suggested a potential regulating effect of R. nigroclavatus on buffalograss mealybug populations. Paired comparison tests with and without R. nigroclavatus demonstrated the effectiveness of this parasitoid as a biological control agent for buffalograss mealybugs under greenhouse conditions. Significant differences were detected in the number of nonparasitized mealybugs between treatments containing only mealybugs and treatments containing both mealybugs and parasitoids. Sticky trap captures in the field suggested a functional relationship between the seasonal abundance of R. nigroclavatus and its mealybug hosts.

Susceptibility to Cry1Ab and Cry1Ac toxins from Bacillus thuringiensis was determined for 11 populations of neonate European corn borer,Ostrinia nubilalis (Hübner), from the United States and 1 from northern Italy. Corn borer larvae were exposed to artificial diet treated with increasing B. thuringiensis concentrations, and mortality and growth inhibition were evaluated after 7 d. The range of variation in B. thuringiensis susceptibility indicated by growth inhibition was very similar to that indicated by mortality. Although interpopulation variation in susceptibility to both proteins was observed, the magnitude of the differences was small (≤4-fold) and comparable to the variability observed among generations within a particular population (≤3-fold). Additionally, there was no indication that B. thuringiensis susceptibility was influenced by pheromone race, voltine ecotype, or geographic location. These results suggest that the observed susceptibility differences reflect natural variation in B. thuringiensis susceptibility among corn borer populations rather than variation caused by prior exposure to selection pressures. Therefore, European corn borers apparently are susceptible to B. thuringiensis toxins among populations across most of their geographic range.

Sequential sampling plans are appealing because fewer observations are needed than those needed for fixed sampling plans to make a terminating decision when insect populations are sparse or abundant. Wald's Sequential Probability Ratio Test (SPRT) commonly has been used in monitoring insect populations and damages from these populations. At times, particularly for moderate infestations, the SPRT with its parallel boundaries takes longer than a comparable fixed-sample-size method to make a terminating decision. An alternative sequential testing procedure called the 2-SPRT for the negative-binomial parameter P is demonstrated. The value of the exponent k is assumed to be known. In this procedure two one-sided SPRTs are performed simultaneously, which results in the convergent boundary lines. The average number of observations needed for the terminating decision for medium infestations (i.e., for P1 < P < P2) is observed to be considerably smaller than that for the SPRT with a slight increase in sampling effort when infestations are light or heavy. An application of the 2-SPRT is demonstrated using cotton f1eahopper, Pseudatomoscelis seriatus (Reuter), data obtained in southwestern Oklahoma.

Six different detoxification enzymes including general esterase, permethrin hydrolase, total cytochrome P-450, aldrin epoxidase, and glutathione transferase measured with two different substrates were recorded from a variety of terrestrial and aquatic insects. Aquatic insects generally exhibited a well-developed detoxification enzyme system and often displayed activities equal to or greater than those of the terrestrial species tested. Canonical discriminant analysis revealed significant differences in overall activity profiles between terrestrial and aquatic insects. Such differences may contribute to higher sensitivity of aquatic insects to insecticide poisoning but are insufficient to explain overall differences between terrestrial and aquatic insects with regard to insecticide susceptibility.

Recent articles by Perry (1986, J. Econ. Entomol. 79: 1149–1155) and Jones & Matloff (1986, J. Econ. Entomol. 79: 1156–1160) have explored some of the current abuses of statistical hypothesis testing. Jones & Matloff suggest that only estimation, and no statistical hypothesis testing, should be performed. We express the alternative view that there is an inherent relationship in estimation and hypothesis testing and that each provides information which the other does not. We address some of the concerns that have been expressed about statistical hypothesis testing and show how they are present when using estimation. When the goal of sampling is to determine whether an insect population should be controlled chemically, sequential hypothesis testing is preferred to estimation procedures.