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260 results for “Interceptions”
Data from: Shade tolerance controls the spectrum of crown sizes and its response to local competition across European and North American tree species: Implications for light interception strategies
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Discontinued Vegetation Line-Intercept Transects in Transition Zones at the Sevilleta National Wildlife Refuge, New Mexico (1989-1998)
The line-intercept transects included in this data set have been discontinued. These transects were installed to evaluate temporal and spatial dynamics in vegetation transition zones (e.g.black grama grassland/creosote shrubland) at one centimeter resolution. Each study site originally contained four 400 m transects, representing total coverage of 1 sq km. The transects were placed along a roughly north/south azimuth. The northwestern and southwestern transects were 100 meters from the western edge of the 1 sq km study area and the northeastern and southeastern transects were 100 m from the eastern edge, providing 800 meters between the eastern and western transects. The northeastern and northwestern transects began to the north and, after an interval of 200 meters, the southeastern and northeastern transects began, terminating at the southern edge of the study area. Ongoing line-intercept transect data for transect 1, which continues to be sampled at both Deep Well and Five Points, can be found in SEV004.
Deep Well Burn Line-Intercept Vegetation Transects at the Sevilleta National Wildlife Refuge, New Mexico (1995-2009)
A natural burn occurred in the Deep Well area of McKenzie Flats in June, 1995, following which studies were initiated to evaluate the effect of fire on plant species composition and the spatial and temporal dynamics of regrowth. The burn area was approximately 24 hectares, forming a swath about 200 m wide from the initial lightning-ignition source. The fire moved in a westward direction from the ignition point, leaving a relatively straight border along the southern boundary and an irregular edge along the northern boundary. The fire was extinguished naturally.One week after the burn, four 100 m line-intercept transects were established along the southern boundary of the burn. Transects were installed perpendicular to the burn, so that 50 m lay inside the burned area and 50 m outside, in unburned grassland. The first transect (nearest the road) was placed 100 m from the west end of the burn and identified as Transect A. The remaining transects (B,C,D) were located at 200 m intervals from Transect A. Rebar was placed at 0 m, 50 m, and 100 m and these points recorded with a GPS unit. Initial measurements were made in October, 1995. In subsequent years, measurements have been made in late May and late September to evaluate the response of "cool season" and "warm season" plant species. Another fire occurred on June 24, 2001. This burn only affected the unburned southern end of one transect. A prescribed burn in 2003 did not affect the transects.
Small Mammal Exclosure Study (SMES) Vegetation Line Intercept from Chihuahuan Desert Grassland and Shrubland at the Sevilleta National Wildlife Refuge, New Mexico (1995-2005)
The purpose of this study is to determine whether or not the activities of small mammals regulate plant community structure, plant species diversity, and spatial vegetation patterns in Chihuahuan Desert shrublands and grasslands. What role if any do indigenous small mammal consumers have in maintaining desertified landscapes in the Chihuahuan Desert? Additionally, how do the effects of small mammals interact with changing climate to affect vegetation patterns over time? This is data for perennial plant vegetation canopy cover measured from all SMES study plots, fall 1995 and fall 2005. The purpose of this data is to provide ground-truth data for comparison with low-level aerial photographs of each study plot. Three, 29 meter lines were measured along three of six rows of the permanent vegetation measurement quadrats. Each line was measured at 10cm resolution for intercepts of perennial plant live canopy cover, and for bare ground. 10cm resolution is comparable to the resolution of the aerial photos. All plants were identified to the species level. These line-intercept measurements are taken once every ten years, at the same time that low-level aerial photographs are taken. These data will be compared to both decadal air photos, and annual measures ofvegetation from one-meter2 quadrats on each plot to provide information on vegetation change over time relative to the various animal exclosure treatments.
Tracking invasions of a destructive defoliator, the gypsy moth (Erebidae: Lymantria dispar): population structure, origin of intercepted specimens, and Asian introgression into North America
Genetic data can help elucidate the dynamics of biological invasions, which are fueled by the constant expansion of international trade. The introduction of European gypsy moth (<i>Lymantria dispar dispar</i>) into North America is a classic example of human-aided invasion that has caused tremendous damage to North American temperate forests. Recently, the even more destructive Asian gypsy moth (mainly <i>L. d. asiatica</i> and <i>L. d. japonica</i>) has been intercepted in North America, mostly transported by cargo ships. To track invasion pathways, we developed a diagnostic panel of 60 DNA loci (55 nuclear and 5 mitochondrial) to characterize worldwide genetic differentiation within <i>L. dispar</i> and its sister species <i>L. umbrosa</i>. Hierarchical analyses supported strong differentiation and recovered five geographic groups that correspond to 1) North America, 2) Europe plus North Africa and Middle East, 3) the Urals, Central Asia, and Russian Siberia, 4) continental East Asia, and 5) the Japanese islands. Interestingly, <i>L. umbrosa</i> was grouped with <i>L. d. japonica</i>, and the introduced North American population exhibits remarkable distinctiveness from contemporary European counterparts. Each geographic group, with the exception of North America, shows additional lower-level structures when analyzed individually, which provided the basis for inference of the origin of invasive specimens. Two assignment approaches consistently identified a coastal area of continental East Asia as the major source for Asian invasion during 2014–2015, with Japan being another source. By analyzing simulation and laboratory crosses, we further provided evidence for the occurrence of natural Asian-North American hybrids in the Pacific Northwest, raising concerns for introgression of Asian alleles that may accelerate range expansion of gypsy moth in North America. Our study demonstrates how genetic data contribute to bio-surveillance of invasive species with results that can inform regulatory management and reduce the frequency of trade-associated invasions.
Impact of intercept trap type on plume structure: a potential mechanism for differential performance of intercept trap designs for Monochamus species
<p>Studies have demonstrated that semiochemical-baited intercept traps differ in their performance for sampling insects, but we have an incomplete understanding of how and why intercept trap design effects vary among insects. This can significantly delay both the development of new and optimization of existing survey and detection tools. The development of a mechanistic understanding of why trap performance varies within and among species would mitigate this delay. The primary objective of this study was to develop methods to characterize and compare the odor plumes associated with intercept traps that differ in their performance for forest Coleoptera. We released CO<sub>2</sub> and measured fluctuations of this tracer gas from 175-point locations arranged in a 2-by-3-by-2-m grid cuboid downwind of a standard multiple-funnel, a modified multiple-funnel, a panel, a canopy malaise trap, and a blank control (i.e., no trap) in a greenhouse. Significant differences in trapping efficacy between these different trap designs were observed for <i>Monochamus scutellatus</i> (Say) and <i>Monochamus notatus</i> (Drury) in a field trial. Significant differences were also observed in how CO<sub>2</sub> accumulated in time at different positions downwind among these different trap designs. Turbulent dispersion is the dominant force structuring odor plumes and creates intermittency in the odor plume that is important for sustained upwind flight in insects. Methodological and instrumental limitations resulted in the inability to determine instantaneous plume structures and vortex shedding frequencies for different intercept trap designs. Although we observed differences in the odor plumes emanating downwind of the different intercept trap designs, we were unable to reconcile these differences with capture rates of the different trap designs for <i>M. scutellatus</i> and <i>M. notatus</i>.</p>
Dataset from "Impact of intercepted and sub-canopy snow microstructure on snowpack response to rain-on-snow events under a boreal canopy"
<p>The dataset presented below is described in the paper "Impact of rain-on-snow events on snowpack structure and runoff under a boreal canopy" by Bouchard et al. (submitted in December 2023) in the journal The Cryosphere.</p><p>The original dataset includes <strong>sub-canopy snow monitoring data</strong> collected at the Montmorency Forest site (MF; 47.29°N, 71.17°W, elev. » 850 m above mean sea level (AMSL)) from 2018 to 2023 and at the Bernard River Valley site (BRV; 50.91°N; 63.37°W, elev. » 250 m. AMSL) from 2019 to 2023. MF is a balsam fir-white birch stand on a 12° northeast-facing slope. BRV is a valley surrounded by plateaus 200 m higher. The dataset covers the period from October 15 to June 15 of each year. In the monitoring dataset you can find the hourly time step:</p><ul><li>Snow height (cm) <i>– all years at both sites</i></li><li>Soil-snow interface temperature (°C) <i>– 2020 to 2023 at both sites</i></li><li>Snow temperature every 15 cm from the ground surface (°C)<i> – 2020 to 2023 at both sites</i></li><li>Snow surface temperature (°C) –<i> 2018-19 and from 2020 to 2023 at MF site</i></li><li>Air temperature (°C)<i> – 2020 to 2023 at both sites</i></li></ul><p>The dataset also includes a total of <strong>48 sub-canopy snow pit observations</strong> taken at the MF (42 snow pits) and BRV (6 snow pits) sites during the study period. Each snow pit contains the vertical profile of snow stratigraphy (grain type) and snow density. The snow pit height corresponds to the upper limit of the top snow layer in the stratigraphic profile. For density measurements, the height value corresponds to the center of the 3 cm thick box cutter. Grain type codes for the snowpack stratigraphy correspond to the International Classification for Seasonal Snow (Fierz et al., 2009):</p><ul><li>PP: precipitation particles</li><li>DF: decomposed and fragmented precipitation particles</li><li>RG: rounded grains</li><li>FC: faceted crystals</li><li>FCxr: rounding faceted particles</li><li>DH: depth hoar</li><li>MFpc: melt forms – rounded polycrystals</li><li>MF: melt forms – clustered rounded grains</li><li>MFcr: melt forms – melt-freeze crusts</li><li>IF: ice formations</li></ul><p>Finally, the dataset includes <strong>all observed rain-on-snow (ROS) events</strong> at both sites from November to March, covering the period 2018-2023 at the MF site and the period 2019-2023 at the BRV site. In the ROS dataset, we present the start and end dates, as well as the duration, rainfall amount, and mean air temperature of each event.</p>
Fig. 1. V in Scaphisomatini of Arizona (Coleoptera, Staphylinidae, Scaphidiinae) collected by V-Flight Intercept Traps
Fig. 1. V-flight intercept trap, with metal frame.
Avoiding obstacles while intercepting a moving target: A miniature fly's solution
<p>The miniature robber fly <i>Holcocephala fusca<i> </i></i>intercepts its targets using a system whose behaviour is approximated by the proportional navigation guidance law. During predatory trials, we challenged <em>Holcocephala</em>'s interception performance by placing a large object in its potential flight path. In response, <em>Holcocephala</em> deviated from the path predicted by pure-proportional navigation, but in many cases still eventually contacted the target. We show that such flight deviations can be explained as the output of two competing navigational systems; pure-proportional navigation and a simple obstacle avoidance algorithm. Obstacle avoidance by <em>Holcocephala</em> is here described by a simple feedback loop that uses the visual expansion of the approaching obstacle to mediate the magnitude of the turning-away response. We name the integration of this this steering law with pro-nav "Combined Guidance". The results demonstrate that predatory intent does not operate a monopoly on the fly's steering when attacking a target, and that simple guidance combinations can explain obstacle avoidance during interceptive tasks.</p>
Fine intervals are required when using point intercept transects to assess coral reef status
The Point Intercept Transect (PIT) method has commonly been used in recent decades for estimating the status of coral reef benthic communities. It is a simple method that is efficiently performed underwater, as benthic components are recorded only as presence or absence at specific interval points along transects. Therefore, PIT is also popular in citizen science activities such as Reef Check programs. Longer intervals are commonly associated with longer transects, yet sampling interval length can significantly influence benthic coverage calculations. Despite this, the relative accuracy of longer or shorter intervals related to transect length has not been tested for PIT. In this study, we tested the optimum intervals of PIT for several commonly used transect lengths using the bootstrap method on empirical data collected on tropical coral reefs and non-reefal coral communities. Our results recommend fine intervals of 10 cm or shorter, depending on the length of the transect, to increase the accuracy of estimating benthic community status on coral reefs. Permanent transects should also be considered in long-term monitoring programs to improve data quality.
Canopy Interception and Throughfall of Turfgrass
<p>Datasets including precipitation (rain_mm) and throughfall (rain_zoy and rain_bent) for two turfgrass species.</p> <p>Example python notebook for filtering data is included based on date range.</p>
Dataset for "Is the linear relationship between the slope and intercept observed in field emission S-K plots an artifact?"
<p>The dataset are in text format, the files to analyze and generate the figures are in jupyter format for python with a copy in pdf format.</p> <p>Description of files and folders :</p> <p><strong>I) Analyzed</strong></p> <p>This folder contains Fowler-Nordheim analysis of the I-V data in the folder Data, that where obtained in the publication "All field emission experiments are noisy, ... are any meaningful ?"</p> <p><strong>II) Data</strong></p> <p>This folder contains the different experimental I-V data</p> <p><strong>III) Numerical data<br></strong></p> <p>This folder contains the different noisy I-V data generated by the file "Simul"</p> <p><strong>IV) Fig1</strong></p> <p>This file generates the figure "MySK4.svg" based on the data in the folders <strong>I) Analyzed</strong> and <strong>III) Numerical data</strong></p> <p><strong>V) Fig2</strong></p> <p>This file analyses the data in the folder <strong>II) Data</strong> and then extract the parameters of their SK plot.</p> <p>It gathers the SK plot parameters of several work in the litterature.</p> <p>It plots "Slopm4.svg" and "Intm4.svg".</p> <p><strong>VI) Simul</strong></p> <p>This file generates the different noisy I-V data necessary fir Fig1</p> <p><strong>VII) FigSuppl</strong></p> <p>This file shows the different experimental Fowler-Nordheim plots obtained from the files in the folder <strong>II) Data</strong></p>
Global rainfall interception loss based on the global vD-B model
<p>This repository contains datasets required for the paper titled "Multi-decadal dynamics of global rainfall interception and their drivers", including</p> <ol> <li>Annual Ei based on the global vD-B model for the period 1981-2020</li> <li>Annual Ei under different scenarios based on the global vD-B model</li> <li>Annual vegetation storage capacity (Sv) and canopy cover (cc), </li> <li>The Southern Oscillation Index (SOI)</li> <li>Annual Ei from other datasets, including GLEAM v3.8a, PML_MOD, PML_AVHRR</li> <li>Annual P from MSWEP v2.8 and ED from GLEAM 4 (exclude snow periods)<br><br> </li> </ol>
Figure 54. A–C in The identification of the flower thrips, Frankliniella Karny (Thysanoptera: Thripidae) intercepted at U.S. ports of entry
Figure 54. A–C) Frankliniella varipes. A) Body. B) Forewing. C) Head and pronotum.
Figure 41. A–C in The identification of the flower thrips, Frankliniella Karny (Thysanoptera: Thripidae) intercepted at U.S. ports of entry
Figure 41. A–C) Frankliniella minuta. A) Body. B) Head and pronotum. C) Abdominal tergites VIII–X.
Figure 33. A–D in The identification of the flower thrips, Frankliniella Karny (Thysanoptera: Thripidae) intercepted at U.S. ports of entry
Figure 33. A–D) Frankliniella gemina A) Body. B) Head. C) Pronotum. D) Abdominal tergites IX and X.
Corrective saccades influence velocity judgments and interception
<p>Here you can find the data for the paper "Corrective saccades influence velocity judgments and interception" by</p> <p>Alexander Goettker, Eli Brenner, Karl Gegenfurtner & Cristina de la Malla.</p>
The known unknowns in international border interceptions of non-native insects datasets
<p>Set of datasets for analysis in Turner et al. (2024).</p> <p>Turner, R.M., Liebhold, A.M., Nahrung, H.F. <em>et al.</em> The known unknowns in international border interceptions of non-native insects. <em>Biol Invasions</em> <strong>27</strong>, 50 (2025). https://doi.org/10.1007/s10530-024-03502-3</p>
Dataset accompanying: Directional biosonar beams allow echolocating harbour porpoises to actively discriminate and intercept closely-spaced targets
<p>These datasets accompany the manuscript "Directional biosonar beams allow echolocating harbour porpoises to actively discriminate and intercept closely-spaced targets". Three XLSX spreadsheets contain data for trial-specific variables (Dataset A, n=120, used for trial duration, discrimination success, number of scans, buzz duration, range to target at buzz onset, range to target at discrimination), on-axis click candidates (Dataset B, n=1810, used for delta T, delta EL), and true on-axis clicks (Dataset C, n=906, used for SL and bearing calculations). Units of each variable are denoted in the column headers. Details on data collection, curation, and analysis can be found in the Malinka<em> et al</em>. publication ([insert link to DOI once available]).</p> <p>For comments/questions, please contact chloe.e.malinka [at] bio.au.dk</p>
Canopy interception loss of rainfall
<p>Global data of rainfall interception loss (Ei) for the 2000-2020 period, available at 0.5degree and monthly scale. The Ei flux is first separated from eddy covariance measurements of ET using two hybrid machine learning models, and then upscaled to the globe forced by satellite-observed vegetation attributes and ERA5 metereological conditions. </p>
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