Estimates of the residual nitrogen benefit of groundnut to maize in Northeast Thailand

Four cultivars of groundnut were grown in upland soil in Northeast Thailand to study the residual benefit of the stover to a subsequent maize crop. An N-balance estimate of the total residual N in the maize supplied by the groundnut was made. In addition three independent estimates were made of the residual benefits to maize when the groundnut stover was returned to the land and incorporated. The first estimate (Estimate 1) was an N-balance estimate. A dual labelling approach was used where ¹⁵N-labelled stover was added to unlabelled microplots (Estimate 2) or unlabelled stover was added to ¹⁵N-labelled soil microplots (Estimate 3). The nodulating groundnut cultivars fixed between 59–64% of their nitrogen (as estimated by the ¹⁵N isotope dilution method using non-nodulating groundnut as a non-fixing reference) producing between 100 and 130 kg N ha^-1 in their stover. Although the following maize crop suffered from drought stress, maize grain N and dry weights were up to 80% and 65% greater respectively in the plots where the stover was returned as compared with the plots where the stover was removed. These benefits were comparable with applications of 75 kg N ha^-1 nitrogen in the form of urea. The total residual N estimates of the contribution of the nodulated groundnut to the maize ranged from 16.4–27.5 kg N ha^-1. Estimates of the residual N supplied by the stover and fallen leaves ranged from 11.9–21.3 kg N ha^-1 using the N-balance method (Estimate 1), from 6.3–9.6 kg N ha^-1 with the labelled stover method (Estimate 2) and from 0–11.4 kg N ha^-1 with the labelled soil method. There was closest agreement between the two ¹⁵N based estimates suggesting that apparent added nitrogen interactions in these soils may not be important and that N balance estimates can overestimate the residual N in crops following legumes, even in very poor soils. This work also indicates the considerable ability of local groundnut cultivars to fix atmospheric nitrogen and the potential benefits from returning and incorporating legume residues to the soil in the upland cropping systems of Northeast Thailand. The applicability of the ¹⁵N methodology used here and possible reasons for the discrepancies between estimates 1, 2 and 3 are discussed.     

The influence of sampling method on the classification of wetland macroinvertebrate communities

Macroinvertebrate communities sampled by a corer, plankton net and sweep net from five wetlands on the Swan Coastal Plain were compared. The composition of the fauna collected in sweeps and tows was generally similar and differed from that collected in the cores. Cores caught fewer species than tows and sweeps at all wetlands and did not capture fast swimming hemipterans or less abundant taxa. The highest species richness was recorded in sweep samples in four out of the five wetlands. Classification (TWIN-SPAN) and ordination (SSH) of the samples collected in sweeps and tows gave good separation of the wetlands, whereas classification of core samples did not. Coring appeared to be the least suitable sampling method for describing the major components of the macroinvertebrate communities of these wetlands. Plankton tows were useful if the time available for sorting was limited as these samples were free of sediments and generally gave similar results to those obtained with sweeps. Sweeps appeared to be the most useful method for a large classification study as they collected more species and resulted in the best discrimination amongst wetlands.     

四种主要大豆食叶害虫种群空间分布型及其应用研究

通过分层随机与连片调查获得114个样本．利用微机分别对豆天蛾卵和豆天蛾．银纹夜蛾．棉铃虫．豆灰蝶及混合种群的幼虫．进行了4种频次分布型检验和6项聚集度指标的测定．结果表明．上述害虫在豆田内均属零集分布．中分析了聚集原因．提出了“Z”字型10样点,每样点以1／3m双行为单位的抽样方法．确立了在两种允许误差下的抽样数量．进行了序贯抽样分析。     

Protocol for Development of American Association of Clinical Endocrinology Clinical Practice Guidelines and Consensus Statements: Summary of Methodology,Process, and Policy – 2023 Update

ObjectiveThis 2023 updated protocol summarizes the American Association of Clinical Endocrinology’s (AACE’s) new framework for the development of clinical practice guidelines and other guidance documents that includes changes to methodology, processes, and policies.MethodsAACE has critically reviewed its development processes for guidance documents over the last several years against the National Academy of Medicine Standards for Developing Trustworthy Clinical Practice Guidelines and the Council of Medical Specialty Societies Principles for Development of Specialty Society Clinical Guidelines to determine areas for improvement.ResultsThe new AACE framework for development of guidance documents incorporates many changes, including a revised conflicts of interest (COI) policy; strengthened commitment to collection of disclosures and management of relevant COI during development; open calls to membership for authors; new requirements for authors; new diversity, equity, and inclusion (DEI) policy; new empanelment process that incorporates consideration of DEI; and adoption of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology to increase the quality of evidence assessment and standardize recommendation grades and statements, among other improvements.ConclusionsAACE has revised its policies and adopted a completely new methodology for guideline development in support of the mission to elevate the practice of clinical endocrinology to improve patient care. With the use of an evidence-based medicine framework and by continually assessing and improving its processes for development of guidance, AACE strives to deliver trustworthy, unbiased, and up-to-date information that ensures clinician and patient confidence in AACE content. Further, AACE hopes that these enhancements foster a more collaborative approach to development and increase engagement with the worldwide medical community to improve global health.     

Nonparametric and semiparametric estimation with sequentially truncated survival data

In observational cohort studies with complex sampling schemes, truncation arises when the time to event of interest is observed only when it falls below or exceeds another random time, that is, the truncation time. In more complex settings, observation may require a particular ordering of event times; we refer to this as sequential truncation. Estimators of the event time distribution have been developed for simple left-truncated or right-truncated data. However, these estimators may be inconsistent under sequential truncation. We propose nonparametric and semiparametric maximum likelihood estimators for the distribution of the event time of interest in the presence of sequential truncation, under two truncation models. We show the equivalence of an inverse probability weighted estimator and a product limit estimator under one of these models. We study the large sample properties of the proposed estimators and derive their asymptotic variance estimators. We evaluate the proposed methods through simulation studies and apply the methods to an Alzheimer's disease study. We have developed an R package, seqTrun , for implementation of our method.     

Enhancing estimation methods for integrating probability and nonprobability survey samples with machine-learning techniques. An application to a Survey on the impact of the COVID-19 pandemic in Spain

Web surveys have replaced Face-to-Face and computer assisted telephone interviewing (CATI) as the main mode of data collection in most countries. This trend was reinforced as a consequence of COVID-19 pandemic-related restrictions. However, this mode still faces significant limitations in obtaining probability-based samples of the general population. For this reason, most web surveys rely on nonprobability survey designs. Whereas probability-based designs continue to be the gold standard in survey sampling, nonprobability web surveys may still prove useful in some situations. For instance, when small subpopulations are the group under study and probability sampling is unlikely to meet sample size requirements, complementing a small probability sample with a larger nonprobability one may improve the efficiency of the estimates. Nonprobability samples may also be designed as a mean for compensating for known biases in probability-based web survey samples by purposely targeting respondent profiles that tend to be underrepresented in these surveys. This is the case in the Survey on the impact of the COVID-19 pandemic in Spain (ESPACOV) that motivates this paper. In this paper, we propose a methodology for combining probability and nonprobability web-based survey samples with the help of machine-learning techniques. We then assess the efficiency of the resulting estimates by comparing them with other strategies that have been used before. Our simulation study and the application of the proposed estimation method to the second wave of the ESPACOV Survey allow us to conclude that this is the best option for reducing the biases observed in our data.     

Spatial sampling to detect slug abundance in an arable field

Overuse of molluscicides by farmers in arable systems can lead to environmental and product contamination. Here we assess a simple and inexpensive surface trapping method for monitoring populations of slugs (Deroceras reticulatum and Arion intermedius). This method was biased against small slugs, and against A. intermedius, when compared to direct soil sampling. Regression was used to model the relationship between the results of surface trapping and soil sampling methods. Spatial Analysis by Distance IndicEs (SADIE) algorithms were used to describe the spatial relationships between the two sets of samples. Using both traditional statistical methods and spatial statistics, the spatial information collected from surface traps was sufficient to identify patches and gaps in slug numbers and possibly to allow the spot application of slug control, and thus provide land managers who experience slug damage with a way of reducing molluscicides use, whilst maintaining slug control. Further improvements and applications of the model are discussed.     

Two-phase species–time relationships in North American land birds

The species–time relationship (STR) is a macroecological pattern describing the increase in the observed species richness with the length of time censused. Understanding STRs is important for understanding the ecological processes underlying temporal turnover and species richness. However, accurate characterization of the STR has been hampered by the influence of sampling. I analysed STRs for 521 breeding bird survey communities. I used a model of sampling effects to demonstrate that the increase in richness was not due exclusively to sampling. I estimated the time scale at which ecological processes became dominant over sampling effects using a two‐phase model combining a sampling phase and either a power function or logarithmic ecological phase. These two‐phase models performed significantly better than sampling alone and better than simple power and logarithmic functions. Most community dynamics were dominated by ecological processes over scales <5 years. This technique provides an example of a rigorous, quantitative approach to separating sampling from ecological processes.     

A Comparison of Remote Sensing and Ground-Based Methods for Monitoring Wetland Restoration Success

Abstract Efficient and accurate vegetation sampling techniques are essential for the assessment of wetland restoration success. Remotely acquired data, used extensively in many locations, have not been widely used to monitor restored wetlands. We compared three different vegetation sampling techniques to determine the accuracy associated with each method when used to determine species composition and cover in restored Pacific coast wetlands dominated by Salicornia virginica (perennial pickleweed). Two ground‐based techniques, using quadrat and line intercept sampling, and a remote sensing technique, using low altitude, high resolution, color and color infrared photographs, were applied to estimate cover in three small restoration sites. The remote technique provided an accurate and efficient means of sampling vegetation cover, but individual species could not be identified, precluding estimates of species density and distribution. Aerial photography was determined to be an effective tool for vegetation monitoring of simple (i.e., single‐species) habitat types or when species identities are not important (e.g., when vegetation is developing on a new restoration site). The efficiency associated with these vegetation sampling techniques was dependent on the scale of the assessment, with aerial photography more efficient than ground‐based sampling methods for assessing large areas. However, the inability of aerial photography to identify individual species, especially mixed‐species stands common in southern California salt marshes, limits its usefulness for monitoring restoration success. A combination of aerial photography and ground‐based methods may be the most effective means of monitoring the success of large wetland restoration projects.     

Population genetic structure of the butterfly Melitaea didyma (Nymphalidae) along a northern distribution range border

The population genetic structure of the butterfly Melitaea didyma was studied along the northern distribution range border in Central Germany by means of allozyme electrophoresis. Individuals were sampled from a total of 21 habitat patches from four regions, and two provinces. Sampling was designed to estimate local vs. regional differentiation. High levels of variability were found, H _e= 0.14–0.21. The mean expected sample heterozygosity from one region, Mosel, was significantly lower than from the Hammelburg region, H _e= 0.17 and 0.19, respectively. Two hierarchical levels of genetic differentiation were found. Within regions individuals sampled from different patches behaved as belonging to one population with high levels of gene flow (Hammelburg F _ST= 0.015, Mosel F _ST= 0.044), though local isolation barriers did create a substructuring of these populations. The inbreeding coefficients, F _IS, were constant over all sample levels, suggesting a similar distribution of habitat patches within regions. Between regions gene flow was limited. An isolation by distance analysis indicated that the hierarchical structure, at the provincial level, may be breaking down due to isolation of regional populations. A more general observation was that the sampling design may greatly have influenced the estimation of genetic differentiation. Depending on which samples were included, overall F _ST estimates ranged from 0.059–0.090.