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opencc-by-4.0Jul 2024View details →

Figure 3 in A reliable method for quick comparisons of enchytraeid (Oligochaeta) densities in soil and their seasonal changes under cultivated and natural fields in central Greece

Figure 3. Seasonal fluctuations of the mean soil moisture up to 15 cm depth and of the soil temperature at 10 cm depth in the alfalfa plantation and its boundary zone in Kopaida valley.

opencc-by-4.0Jul 2024View details →

Figure 1 in A reliable method for quick comparisons of enchytraeid (Oligochaeta) densities in soil and their seasonal changes under cultivated and natural fields in central Greece

Figure 1. Left: Extraction efficiency (enchytraeid individuals m-2) of sucrose centrifugation, wet extraction with filter and wet extraction without filter. Bars and error bars denote means and 95% confidence intervals respectively. Means that are significantly different in multiple comparisons using Wilcoxon test are represented by different letters above bars (P <0.05). Right: Relationship between Enchytraeidae populations extracted with wet extraction without filter and a) sucrose centrifugation, and b) wet extraction with filter.

Fig. 3 in Field sampling methods for Asiatic garden beetle (Coleoptera: Scarabaeidae) adult movement and flight in the Great Lakes region

Fig. 3. Mean number of Maladera formosae adults captured in milkjug traps containing either water, ethylene glycol antifreeze, or propylene glycol antifreeze, from 14 to 21 Jul 2021 (a) and from 21 to 28 Jul 2021 (b) in soybean at the Fulton3 site near Wauseon, Ohio. Uppercase letter(s) above each bar indicates significant differences at the P ≤ 0.05 level from pairwise comparison analyses.

Fig. 2 in Field sampling methods for Asiatic garden beetle (Coleoptera: Scarabaeidae) adult movement and flight in the Great Lakes region

Fig. 2. Mean number of Maladera formosae adults captured in pitfall traps during individual evaluation periods at Fulton1 (a) and Fulton2 (b) sites, in northwest Ohio. Uppercase letter(s) above each bar indicates significant differences at the P ≤ 0.05 level from pairwise comparison analyses. Traps were deployed on 28 Jun 2017, 1 wk prior to the sampling data indicated in each figure.

Fig. 1 in Field sampling methods for Asiatic garden beetle (Coleoptera: Scarabaeidae) adult movement and flight in the Great Lakes region

Fig. 1. Sampling methods for Maladera formosae adults: within field – pitfall trap (a) and yellow sticky card (b); at field edge – blacklight trap (c), and antifreeze milkjug trap (d). Photo credit: Adrian Pekarcik, The Ohio State University, Wooster, Ohio, USA.

opencc-by-4.0Apr 2019View details →

Fig. 1 in Effects of irrigation method on pollination and pollinators (Hymenoptera: Apoidea) in an open-field tomato crop

Fig. 1. Fruit set (A) and weight of fruit (B) in relation to type of irrigation and type of pollination. OM = open + mechanical pollination.

opencc-by-4.0Sep 2024View details →

Comparing greenhouse and field biocrust cultivation methods in the Sonoran Desert

Summary 1.     Developing methods to use biocrusts in restoration is becoming more important as land use and climate change impact the health and intactness of high-stress ecosystems. Methods of cultivation to maximize production of biocrusts for use in restoration activities is necessary because salvage opportunities are limited. Our objective for this research was to determine an optimal method for scalable biocrust cultivation. 2.     We tested two Field and one Greenhouse cultivation methods. The Field cultivation methods had a base layer of weed cloth, soil, and irrigation with either 1) shade cloth immediately over the surface (Quesadilla method), or 2) with shade cloth over a 1m tall hoophouse (Hoophouse method). The Greenhouse method had nested basins with water wicking up to the soil surface and biocrust from below, with shade cloth attached to basins. We crossed these methods with the addition of native soil or sand and with and without a base of jute using salvaged biocrusts from the Sonoran Desert. 3.     All methods led to at least doubling biocrust cover in 11 weeks. The Greenhouse method led to the highest cover of cyanobacteria and mosses, whereas the field Quesadilla method and the addition of native soil in all cultivation methods led to higher abundance of lichens. There were interactions of cultivation method and soil type, with Greenhouse cultivation and native soil promoting the highest cyanobacteria cover and chlorophyll a. We measured exopolysaccharide sheaths (EPS) in native soil and all cultivation conditions, finding no differences for tightly bound sheath fractions, but higher quantities of the loosely bound EPS in the Greenhouse. We also quantified native and non-native plants in cultivation, finding few plants in Greenhouse cultivation, but high abundance in both Field methods, and particularly with native soil and without jute for native plants. 4.     Synthesis and applications: Together, these results demonstrate that all three cultivation methods are successful for bulking biocrust materials for restoration, and preference should be given to the method that is the easiest and most accessible for practitioners.

charmm2gmx: An Automated Method to Port the CHARMM Additive Force Field to GROMACS

Validation dataset for the paper "charmm2gmx: An Automated Method to Port the CHARMM Additive Force Field to GROMACS". The dataset includes molecular dynamics input and output files, as well as scripts for running the simulations and analyzing the results, used for validating the ported CHARMM parameters. CHARMM is one of the most widely used biomolecular force fields. Although developed in close connection with a dedicated molecular simulation engine of the same name, it is also usable with other codes. GROMACS is a well-established, highly optimized and multi-purpose software for molecular dynamics, versatile enough to accommodate many different force field potential functions and the associated algorithms. Due to conceptional differences related to software design and the large amount of numeric data inherent to residue topologies and parameter sets, conversion from one software format to another is not straightforward. Here, we present an automated and validated means to port the CHARMM force field to a format read by the GROMACS engine, harmonizing the different capabilities of the two codes in a self-documenting and reproducible way, with a bare minimum of user interaction required. Being based entirely on the upstream data files, the presented approach does not involve any hard-wired/boilerplate code, in contrast with previous attempts to solve the same problem. The heuristic approach used for perceiving local internal geometry is directly applicable for analogous transformations of other force fields.

opencc-by-4.0Dec 2016View details →

Figure 4 in First Field Collection of the Rough Sweetpotato Weevil, Blosyrus asellus (Olivier) (Coleoptera: Curculionidae), on Hawaii Island, with Notes on Detection Methods

Figure 4. Average (+ SEM) catch of adult rough sweetpotato weevils/trap/day in green light traps with and without added attractant(s). Treatments having the same letter above the error bar are not significantly different at the α = 0.05 level. Only results of treatments which included green light (Treatments 5–9) are presented here because there was no catch in this trial in traps of any of the treatments where the green light was off (Treatments 1–4).

opencc-by-4.0Dec 2016View details →

Figure 2 in First Field Collection of the Rough Sweetpotato Weevil, Blosyrus asellus (Olivier) (Coleoptera: Curculionidae), on Hawaii Island, with Notes on Detection Methods

Figure 2. Locations on Hawaii island (marked with filled circles) where adult rough sweetpotato weevils have been recovered (map developed using ArcGIS [ESRI 2012]).

opencc-by-4.0Dec 2016View details →

Figure 3 in First Field Collection of the Rough Sweetpotato Weevil, Blosyrus asellus (Olivier) (Coleoptera: Curculionidae), on Hawaii Island, with Notes on Detection Methods

Figure 3. Trap used for rough sweetpotato weevil detection ('Treatment 9'). (A) Flash picture taken at night to show the sweetpotato root section held underneath the green light and the water container inside the trap holding a sweetpotato leaf. (B) Picture taken without flash to show the appearance of the trap at night.

dryad40/100

Quantifying animal social behaviour with ecological field methods

Open the record for dataset details and reuse information.

publicDec 2024View details →

edi40/100

Nitrogen mineralization was determined on Arctic LTERToolik and Sag River tussock tundra using the buried bag method, Toolik Field Station, Alaska, Arctic LTER 1989-2013.

Nitrogen mineralization was determined on LTER and Sag River tussock tundra using the buried bag method. Yearly bags have been deployed every August since 1990.

openOpenDec 2015View details →

opencc-by-4.0Dec 2020View details →

Data archive for the peer-reviewed journal article "Detailed characterization of the CAPS single scattering albedo monitor (CAPS PMssa) as a field-deployable instrument for measuring aerosol light absorption with the extinction-minus-scattering method"

Data archive accompanying the peer-reviewed journal article "Detailed characterization of the CAPS single scattering albedo monitor (CAPS PMssa) as a field-deployable instrument for measuring aerosol light absorption with the extinction-minus-scattering method". In 2020 this article was accepted for publication in the journal Atmospheric Measurement Techniques. Data are uploaded in the form of ascii text files, Igor Pro experiment files (.pxp), and Jupyter notebook files. In addition, a Jupyter notebook file is included containing an implementation of the error model used in the paper.

opencc-by-4.0Jan 2021View details →

SAXS calculations for Refinement of 𝛼-synuclein ensembles against SAXS data: Comparison of force fields and methods

SAXS curves calculated from MD simulations used as input to reweighting as described in preprint Refinement of 𝛼-synuclein ensembles against SAXS data: Comparison of force fields and methods

dryad36/100

Data from: Apparent annual survival estimates of tropical songbirds better reflect life history variation when based on intensive field methods

Aim: Adult survival is central to theories explaining latitudinal gradients in life history strategies. Life history theory predicts higher adult survival in tropical than north temperate regions given lower fecundity and parental effort. Early studies were consistent with this prediction, but standard-effort netting studies in recent decades suggested that apparent survival rates in temperate and tropical regions strongly overlap. Such results do not fit with life history theory. Targeted marking and resighting of breeding adults yielded higher survival estimates in the tropics, but this approach is thought to overestimate survival because it does not sample social and age classes with lower survival. We compared the effect of field methods on tropical survival estimates and their relationships with life history traits. Location: Sabah, Malaysian Borneo. Time period: 2008–2016. Major taxon: Passeriformes. Methods: We used standard-effort netting and resighted individuals of all social and age classes of 18 tropical songbird species over 8 years. We compared apparent survival estimates between these two field methods with differing analytical approaches. Results: Estimated detection and apparent survival probabilities from standard-effort netting were similar to those from other tropical studies that used standard-effort netting. Resighting data verified that a high proportion of individuals that were never recaptured in standard-effort netting remained in the study area, and many were observed breeding. Across all analytical approaches, addition of resighting yielded substantially higher survival estimates than did standard-effort netting alone. These apparent survival estimates were higher than for temperate zone species, consistent with latitudinal differences in life histories. Moreover, apparent survival estimates from addition of resighting, but not from standard-effort netting alone, were correlated with parental effort as measured by egg temperature across species. Main conclusions: Inclusion of resighting showed that standard-effort netting alone can negatively bias apparent survival estimates and obscure life history relationships across latitudes and among tropical species.

opencc-zeroDec 2016View details →

opencc-by-4.0Apr 2024View details →

Data mining-based machine learning methods for improving hydrological data: a case study of salinity field in the Western Arctic Ocean

Salinity variations in Arctic Ocean determine the strength of stratification, ocean circulation, and biogeochemical cycles. Therefore, accurate salinity product is of great significance for our study of the Arctic Ocean. The mean density structure and wind-driven surface circulation of the Arctic Ocean are largely dominated by the anti-cyclonic Beaufort Gyre in the Canadian Basin, along with the Transpolar Drift (Hall et al.,2022). We focus on the salinity in Western Arctic Ocean. Multiple machine learning methods were used to reconstruct annual salinity product in the Western Arctic Ocean temporal for the period 2003-2022.

opencc-by-3.0-usJan 2022View details →

Water application method influences survival or growth of Escherichia coli on bulb onions during field curing.

These data are presented in figure 2, 3, 4 and 5 of the publication entitled   "Water application method influences survival or growth of Escherichia coli on bulb onions during field curing" submitted to Journal of Food Protection

opencc-by-4.0Jul 2022View details →

Data from: A Method for Measuring B0 Field Inhomogeneity using Quantitative DESS (qDESS)

Purpose: To develop and validate a method for B0 mapping for knee imaging using the quantitative Double-Echo in Steady-State (qDESS) exploiting the phase difference (∆θ) between the two echoes acquired. Contrary to a standard two-gradient echo (2-GRE) method, the phase accumulation in qDESS depends only on the first echo time. Methods: Bloch simulations were applied to investigate the robustness to noise of the proposed methodology and all imaging studies were validated with phantoms and in vivo simultaneous bilateral knee acquisitions. Two phantoms and 5 healthy subjects were scanned using qDESS, water saturation shift referencing (WASSR), and multi GRE sequences. ∆B0 maps were calculated with the qDESS and the 2-GRE methods and compared against those obtained with WASSR. The comparison was quantitatively assessed by exploiting pixel-wise difference maps, Bland-Altman (BA) analysis, and Lin’s concordance coefficient (ρc). For in-vivo subjects, the comparison was assessed in cartilage using average values in 6 sub-regions. Results: The proposed method for measuring B0 inhomogeneities in phantom and in-vivo scans from a qDESS acquisition provided ∆B0 maps that were in good agreement with those obtained using WASSR. ∆B0 Lin’s coefficients were greater than or equal to 0.98 and 0.90 in phantoms and in vivo, respectively. The agreement between qDESS and WASSR was comparable to that of a standard 2-GRE method. Conclusion: The proposed method may allow B0 correction for qDESS T2 mapping using an inherently co-registered ∆B0 map without requiring an additional B0 measurement sequence. More generally, the method may help shorten knee imaging protocols that require an auxiliary ∆B0 map by exploiting a qDESS acquisition that also provides T2 measurements and high-quality morphological imaging. Conclusion: The proposed method may allow B0 correction for qDESS T2 mapping using an inherently co-registered ∆B0 map without requiring an additional B0 measurement sequence. More generally, the method may help shorten knee imaging protocols that require an auxiliary ∆B0 map by exploiting a qDESS acquisition that also provides T2 measurements and high-quality morphological imaging. This repository contains the data for reproducing the results reported in the paper. For the in-vivo data, python scripts are provided to perform the data analysis described in the paper. The data are provided in NIFTI format.  Please cite the original paper (10.1002/mrm.29465) and this repository if you use any of the data or code contained here.