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Long-term data from field erosion plot studies in eastern Austria

The data include measured data for three different soil tillage practices from three experimental sites in eastern Austria. The Tables 1-3 include for each site and each year the period of operation, the planted crop, the annual precipitation, the surface runoff in mm, the soil loss in t/ha and the surface losses of total nitrogen, total phosphorus and soil organic carbon in kg/ha. Crop yields were determined from 45 m² large plots with one or two replications. Yields in kg/ha are not available for all years, but relative yield in % are. The experiments were conducted at three sites in eastern Austria: in Mistelbach, Pixendorf and Pyhra. The soils in Mistelbach and Pyhra are classified as Typic Argiudolls while the soil in Pixendorf is an Entic Hapludoll. Soil textures range from silt loam to loam. Average annual rainfall (1994-2018) at the sites amounts from 621 to 916 mm with average annual air temperatures between 9.4 and 10.4 °C. Following soil tillage treatments were investigated: (1) conventional tillage system with ploughing in fall (CT), (2) mulch tillage with cover crops during winter (MT) and (3) no-till with cover crops during winter (NT). The study design was a randomized block and each treatment was replicated twice. Each treatment was equipped with one field runoff plot. The experimental plots were 6 m wide and – depending on site conditions - between 40 and 80 m long. The study design consisted of 3 (Mistelbach) and 4 m wide (Pixendorf, Pyhra) and 15 m long runoff plots for each management variation. Each plot was bordered by stainless steel metal sheets. At the lower end of the plot surface runoff and soil loss were collected in a trough and then diverted by a 100-mm PVC pipe to an Automated Erosion Wheel (AEW). The design of this AEW is similar to a tipping bucket and consists of four equal sections of five liters resulting in a resolution of each tip of 0.08 mm for 60 m² plots.  A magnetic sensor system was used for continuous runoff measurement. Soil-water-suspension was divided by an adapted multi-tube divisor taking 3.3% of the sample that is collected in a 60 L collection tank. After each erosive storm the collection tank was emptied and the runoff sample was brought to the laboratory, weighed and dried until constant mass was achieved to determine sediment concentration. Based on the continuously measured runoff data from the data logging system and the sediment concentration the amount of soil loss from the plots was calculated for each erosive event. Throughout the investigation period soil erosion, surface runoff and nutrient and carbon losses and partly also pesticide losses due to erosion processes were determined for all sites and tillage systems. Immediately after planting/seeding of summer crops the erosion plots were installed and then operated until harvest. After the harvest the equipment was removed. No measurements were performed during winter due to limited accessibility and frost damages to the equipment. At each site an automatic tipping bucket rain gauge was placed to measure rainfall in 5-min intervals. Crop yield was determined from each treatment with three replications. Total nitrogen and total carbon in sediment samples was analysed by dry combustion [3](OeNorm L1080, 1989) using a C/N Analyzer (Vario Max CN, Elementar). Soil organic carbon content was obtained by subtracting inorganic carbon content measured volumetrically by the Scheibler method with a Calcimeter  (OeNorm L1084, 1989). Total phosphorus of the sediment was determined using a UV/VIS spectral photometer (DU-640 Beckmann). Pesticides were extracted from water by solid phase extraction and from sediments using distilled water or organic solvent [6]. After shaking for several hours and centrifugation, the sample passed through a solid phase extraction. After evaporation of the extract the pesticide residues were redissolved in another solvent and analysed with high performance liquid chromatography (HPLC).

opennotspecifiedJan 2020View details →

Figure 2 in Compositionı characteristics and long-term variability of the freshwater microcrustacean fauna of the Faroe Islands

Figure 2. CCA of the microcrustacean communities in the surveyed water bodies on the Faroe Islands.

Fig. 5 in Spatial and temporal distribution of Gymnorhamphichthys rondoni (Gymnotiformes: Rhamphichthyidae) in a long-term study of an Amazonian terra firme stream, Leticia - Colombia

Fig. 5. Heat map showing the probability of finding Gymnorhamphichthys rondoni individuals within any quadrant of the grid located in a terra firme stream in Leticia, Amazonas. White represents zero probability. Dark blue represents the lowest probability for quadrants in which G. rondoni rested during the day (1.45%) while red represents the highest probability (36.2%) of finding an individual resting within a given quadrant. Notice that individuals were never found in the white quadrants, which dried out during low water periods.

Fig. 4 in Spatial and temporal distribution of Gymnorhamphichthys rondoni (Gymnotiformes: Rhamphichthyidae) in a long-term study of an Amazonian terra firme stream, Leticia - Colombia

Fig. 4. Monthly distribution of Gymnorhamphichthys rondoni within the grid in the Yahuarcaca terra firme stream in Leticia, Amazonas. The continuous line represents the maximum stream width reached during high water months, and the dashed line the minimum stream width reached in low water months. a. to m. Each sketch represents a sampling month and each number represents the total number of G. rondoni individuals found during five to six days at each quadrant for that particular month.

Fig. 3 in Spatial and temporal distribution of Gymnorhamphichthys rondoni (Gymnotiformes: Rhamphichthyidae) in a long-term study of an Amazonian terra firme stream, Leticia - Colombia

Fig. 3. The EOD pulse in the weakly electric fish Gymnorhamphichthys rondoni. EOD waveform shows four distinctive phases of alternating polarity (Left). Pictures are showing the lateral, dorsal and ventral view of G. rondoni ICN-MHN 6169 (Right). © Institute of Natural Sciences, Faculty of Sciences, Universidad Nacional de Colombia.

Fig. 6 in Spatial and temporal distribution of Gymnorhamphichthys rondoni (Gymnotiformes: Rhamphichthyidae) in a long-term study of an Amazonian terra firme stream, Leticia - Colombia

Fig. 6. Water conductivity and its effects on distance to nearest neighbors and the daily ratio of departure from a random distribution (R). a. The nearest neighbor distance between all individuals of Gymnorhamphichthys rondoni found within the grid for all sampling days during all thirteen months (linear regression, n= 1375; p= 0.45; r2= 0.0004). The daily ratio of departure from a random distribution (R) within the grid for all sampling days during all thirteen months for b. Exponential Model (r2 = 0.09; F = 6.4; p = 0.014) and c. Power Model (r2 = 0.07; F = (1, 62) (1, 62) 4.9; p = 0.03).

Fig. 2 in Spatial and temporal distribution of Gymnorhamphichthys rondoni (Gymnotiformes: Rhamphichthyidae) in a long-term study of an Amazonian terra firme stream, Leticia - Colombia

Fig. 2. Sampling site in the Yahuarcaca terra firme stream in Leticia, Amazonas. a. Image during low water levels. b. Image with high water levels after a local rain.

Fig. 1 in Spatial and temporal distribution of Gymnorhamphichthys rondoni (Gymnotiformes: Rhamphichthyidae) in a long-term study of an Amazonian terra firme stream, Leticia - Colombia

Fig. 1. Geographical position of the sampling site in the Yahuarcaca terra firme stream close to Leticia, Amazonas in Colombia. The picture shows a panoramic view of the sampling site.

FIG. 6 in Functional inferences on the long bones of Ischyrictis zibethoides (Blainville, 1841) (Carnivora, Mustelidae) from the middle Miocene locality of Sansan (Gers, France)

FIG. 6. — Medial view of the left ulna of several species of Mustelidae: Gulo gulo (Linnaeus, 1758) (A), Martes foina (Erxleben, 1777) (B), Meles meles (Schreber, 1778) (C), Taxidea taxus (Linnaeus, 1758) (D), and Ischyrictis zibethoides (Blainville, 1841) from Sansan (E), shown at the same size for a better comparison. Scale bar: 1 cm.

FIG. 3 in Functional inferences on the long bones of Ischyrictis zibethoides (Blainville, 1841) (Carnivora, Mustelidae) from the middle Miocene locality of Sansan (Gers, France)

FIG. 3. — Cranial view of the distal epiphysis of the right humerus of several species of Mustelidae: Gulo gulo (Linnaeus, 1758) (A), Martes foina (Erxleben, 1777) (B), Meles meles (Schreber, 1778) (C), Taxidea taxus (Linnaeus, 1758) (D), and Ischyrictis zibethoides (Blainville, 1841) from Sansan (E), shown at the same size for a better comparison. Scale bar: 1 cm.

FIG. 2 in Functional inferences on the long bones of Ischyrictis zibethoides (Blainville, 1841) (Carnivora, Mustelidae) from the middle Miocene locality of Sansan (Gers, France)

FIG. 2. — Medial view of the proximal epiphysis of the left humerus of several species of Mustelidae: Gulo gulo (Linnaeus, 1758) (A), Martes foina (Erxleben, 1777) (B), Meles meles (Schreber, 1778) (C), Taxidea taxus (Linnaeus, 1758) (D), and Ischyrictis zibethoides (Blainville, 1841) from Sansan (E), shown at the same size for a better comparison. Scale bar: 1 cm.

FIG. 5 in Functional inferences on the long bones of Ischyrictis zibethoides (Blainville, 1841) (Carnivora, Mustelidae) from the middle Miocene locality of Sansan (Gers, France)

FIG. 5. — Caudal view of the right radius of several species of Mustelidae: Gulo gulo (Linnaeus, 1758) (A), Martes foina (Erxleben, 1777) (B), Meles meles (Schreber, 1778) (C), Taxidea taxus (Linnaeus, 1758) (D), and Ischyrictis zibethoides (Blainville, 1841) from Sansan (E), shown at the same size for a better comparison.. Scale bar: 1 cm.

FIG. 8 in Functional inferences on the long bones of Ischyrictis zibethoides (Blainville, 1841) (Carnivora, Mustelidae) from the middle Miocene locality of Sansan (Gers, France)

FIG. 8. — Caudal view of the distal epiphysis of the left femur of several species of Mustelidae: Gulo gulo (Linnaeus, 1758) (A), Martes foina (Erxleben, 1777) (B), Meles meles (Schreber, 1778) (C), Taxidea taxus (Linnaeus, 1758) (D), and Ischyrictis zibethoides (Blainville, 1841) from Sansan (E), shown at the same size for a better comparison. Scale bar: 1 cm.

FIG. 1 in Functional inferences on the long bones of Ischyrictis zibethoides (Blainville, 1841) (Carnivora, Mustelidae) from the middle Miocene locality of Sansan (Gers, France)

FIG. 1. — Proximal view of the head of the right humerus of several species of Mustelidae: Gulo gulo (Linnaeus, 1758) (A), Martes foina (Erxleben, 1777) (B), Meles meles (Schreber, 1778) (C), Taxidea taxus (Linnaeus, 1758) (D), and Ischyrictis zibethoides (Blainville, 1841) from Sansan (E), shown at the same size for a better comparison. Scale bar: 1 cm.

FIG. 7 in Functional inferences on the long bones of Ischyrictis zibethoides (Blainville, 1841) (Carnivora, Mustelidae) from the middle Miocene locality of Sansan (Gers, France)

FIG. 7. — Caudal view of the proximal epiphysis of the left femur of several species of Mustelidae: Gulo gulo (Linnaeus, 1758) (A), Martes foina (Erxleben, 1777) (B), Meles meles (Schreber, 1778) (C), Taxidea taxus (Linnaeus, 1758) (D), and Ischyrictis zibethoides (Blainville, 1841) from Sansan (E),, shown at the same size for a better comparison. Scale bar: 1 cm.

opencc-by-4.0Mar 2020View details →

Predicting the Long-Term Stability of Compact Multi-Planet Systems

REBOUND N-body simulation archives used to train and test the machine learning models in Tamayo et al. (2020), 'Predicting the Long-Term Stability of Compact Multi-Planet Systems'. See https://github.com/dtamayo/spock for scripts to process the data, train and test the SPOCK XGBoost model.

opencc-by-4.0May 2020View details →

phytoplankton dataset: Marine diatoms in a warming world: phospholipidome model experiments and long-term field analysis

Phytoplankton data set for Marine diatoms in a warming world: phospholipidome model experiments and long-term field analysis. The data set includes abundances of total phytoplankton and of Chaetoceros pseudocurvisetus.

opencc-by-4.0Apr 2020View details →

A dataset of long-term consistency values of resting-state fMRI connectivity maps in a single individual derived at multiple sites and vendors using the Canadian Dementia Imaging Protocol

This dataset contains preprocessed resting state fMRI data (.nii.gz) with accompanying confound files (.tsv) from the Single Individual volunteer for Multiple Observations across Networks (SIMON; http://fcon_1000.projects.nitrc.org/indi/retro/SIMON.html) dataset that has been minimally preprocessed using the NeuroImaging Analysis Kit (NIAK; http://niak.simexp-lab.org/build/html/PREPROCESSING.html). Preprocessing steps included:  (1) Slice timing correction; (2) Estimation of rigid-body motion in fMRI runs, both within- and between sessions; (3) Linear or non-linear coregistration of the structural scan in stereotaxic space; (4) Individual coregistration between structural and functional scans; (5) Resampling of functional scans in stereotaxic space. Confound files (.tsv) have been included for purposes of scrubbing and regression of confounds using NIAK or other analysis software, allowing for further processing without conflicts.

opencc-by-4.0May 2020View details →

Complete mitogenome of the invasive land flatworm Parakontikia ventrolineata, the second Geoplanidae (Platyhelminthes) to display an unusually long cox2 gene

Complete mitogenome of the invasive flatworm Parakontikia ventrolineata as fasta file.