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5,312 results for “New Zealand”
Figure 1 in Ancient DNA from the extinct New Zealand grayling (Prototroctes oxyrhynchus) reveals evidence for Miocene marine dispersal
Figure 1. The extinct New Zealand grayling (Prototroctes oxyrhynchus). Artwork by Frank Edward Clarke. Annotations in figure contain a nomen nudum. Museum of New Zealand Te Papa Tongarewa CC BY-NC-ND 4.0.
FIGURE 44 in JIA-WEI SHEN & RICHARD A. B. LESCHEN (2020) Revision of Eupines King of New Zealand (Coleoptera: Staphylinidae: Pselaphinae: Goniaceritae) Zootaxa, 4777: 001-084.
FIGURE 44. Diagnostic characters of E. (B.) protibialis sp. n. A) Habitus. B) Antenna, in dorsal view. C) Same, in lateral view. D) Protrochanter. E) Protibia. F) Ventrite 2. G) Ventrite 6. H) Aedeagus, in dorsal view. I) Same, in lateral view. J) Same, in ventral view. Scale bars: A = 1 mm, B–F = 0.2 mm, G–J = 0.1 mm.
Figs 7–9 in Even more paradoxical: Paradoxa paradoxa sp. n. (Diptera: Mycetophilidae) from South Africa, closest relative of the New Zealand Paradoxa fusca Marshall
Figs 7–9. Paradoxa paradoxa sp. n.: (7) male terminalia, ventral view; (8) male terminalia, dorsal view; (9) aedeagal complex and associated structures, lateral view. Abbreviations: A – ejaculatory apodeme; B – aedeagal complex; C – cercus; D – dorsal lobe of gonocoxite; E – gonocoxite; F – gonostylus; G – hypoproct; H – sternite 9; I – tergite 9; J – transverse ridge on gonocoxite; K – ventral lobe of gonocoxite; L – parameral apodeme; M – anterior portion of gonocoxal apodeme; N – posterior portion of gonocoxal apodeme. Scale bar = 0.05 mm (Fig. 9) and 0.1 mm (Figs 7 and 8).
Figs 10–13 in Peripatopsidae (Onychophora) from New Zealand - observations on selected morphs of the 'Peripatoides novaezealandiae-complex' in culture: morphological and reproductive aspects
Figs 10–13. Sketches of posterior ventral body surface. 10. Juvenile from Boundary stream, 2 months, genital area and papillae of anal cone still undifferntiated (30 x). 11. Juvenile from Boundary Stream, 5 months, female (30 x). 12. Juvenile from Woodville Gorge, 2 months, genital area and papillae of anal cone still undifferentiated (30 x). 13. Juvenile from Paengora Mataroa, 2 months, male (30 x).
Figs 6–9. Selected hatchlings and juveniles. 6 in Peripatopsidae (Onychophora) from New Zealand - observations on selected morphs of the 'Peripatoides novaezealandiae-complex' in culture: morphological and reproductive aspects
Figs 6–9. Selected hatchlings and juveniles. 6. Boundary Stream: premature hatchling with slime gland (25 x). 7. Juvenile from Ngapaerera: stage A (7 x). 8. Juvenile from Boundary Stream: stage A (7 x). 9. Juvenile from Monckton: stage C (10 x).
Figs 3–5 in Peripatopsidae (Onychophora) from New Zealand - observations on selected morphs of the 'Peripatoides novaezealandiae-complex' in culture: morphological and reproductive aspects
Figs 3–5. Diagram, micrograph and photograph of selected morphs. 3. Schematic sketch of Mohi Bush male: fifth leg, ventral view (Scale bar = 163 m). 4. SEM micrograph of genital pore: Monckton male (Fig. rotated approx. 45˚). 5. Monckton: premature hatchling (25 x).
Fig. 1 in Peripatopsidae (Onychophora) from New Zealand - observations on selected morphs of the 'Peripatoides novaezealandiae-complex' in culture: morphological and reproductive aspects
Fig. 1: New Zealand localities of observed Peripatopsidae: the abbreviations are for Mount Auckland, Boundary Stream, Paengaroa Mataroa, Mohi Bush, Monckton, Woodville Gorge, Kapiti Island, and Ngapaerera. Part of 'base-map': Modified after Crosby et al. (1976).
FIG. 5 in Ulva L. (Ulvales, Chlorophyta) from Manawatāwhi/ Three Kings Islands, New Zealand: Ulva piritoka Ngāti Kuri, Heesch & W.A.Nelson, sp. nov. and records of two nonnative species, U. compressa and U. rigida
FIG. 5. — Ulva piritoka Ngāti Kuri, Heesch & W.A.Nelson, sp. nov.: A, surface view showing rhizoids extending from cells; B, rhizoidal clump from lower surface of thallus. Scale bars: A, 20 µm; B, 50 µm
FIG. 3 in Ulva L. (Ulvales, Chlorophyta) from Manawatāwhi/ Three Kings Islands, New Zealand: Ulva piritoka Ngāti Kuri, Heesch & W.A.Nelson, sp. nov. and records of two nonnative species, U. compressa and U. rigida
FIG. 3. — Phylogenetic tree inferred by Maximum Likelihood analysis from partial rbcL sequences of Ulvacean species. Numbers above lines indicate ML bootstrap support values (BS) and Bayesian posterior probabilities (PP). BS values below 60% and PP values below 0.9 are not shown. Species names (reflecting current nomenclature; Guiry & Guiry 2021) are followed by GenBank/ENA accession numbers and origin of the sample (see Table 2 for references). New sequences are set in bold.
FIG. 4. — A in Ulva L. (Ulvales, Chlorophyta) from Manawatāwhi/ Three Kings Islands, New Zealand: Ulva piritoka Ngāti Kuri, Heesch & W.A.Nelson, sp. nov. and records of two nonnative species, U. compressa and U. rigida
FIG. 4. — A, Holotype Ulva piritoka Ngāti Kuri, Heesch & W.A.Nelson, sp. nov.; B, section through distromatic blade; C, section in region of rhizodal clump showing deeper adaxial cell layer and rhizoids arising from cells of both thallus layers. Scale bars: A, 2 cm; B, C, 50 µm
Large marine predator aerial survey data for Hauraki Gulf, New Zealand
<p>Large marine predators, such as cetaceans and sharks, play a crucial role in maintaining biodiversity patterns and ecosystem health. Despite the recognised importance of these animals and their over-representation as threatened species, distribution data at appropriate temporal and spatial scales is often lacking or insufficient for effective conservation. </p> <p>Here, we present sightings of large marine megafauna recorded from a replicate systematic aerial survey undertaken in the Hauraki Gulf, Aotearoa New Zealand during a full year. Using flexible machine learning models (Boosted Regression Tree models), we use these sightings data to investigate relationships between large marine predator occurrence (Bryde's whales, common and bottlenose dolphins, bronze whalers, pelagic and immature hammerhead sharks) and spatially explicit environmental and biotic variables to predict species richness of large marine predators and investigate their fine-scale spatiotemporal distribution patterns. All models were considered informative (all, AUC > 0.78), and temporally dynamic variables, such as the distribution of prey, were important in predicting the occurrence of the study species and species groups. </p> <p>Our approach and data highlight the value of multi-species surveys and the importance of considering temporally variable abiotic and biotic drivers for understanding biodiversity patterns when informing ecosystem-scale conservation planning and dynamic ocean management.</p> <p>We provide data files of:</p> <ul> <li>Locations of species presence / pseudo absence location over time (in .csv format) and associated environmental and biotic variables for Bryde's whales, common and bottlenose dolphins, bronze whaler, pelagic and immature hammerhead sharks.</li> <li>Monthly estimates of 14 high-resolution spatially explicit environmental and biotic variables (1 km grid resolution): Bathymetry; Slope; Distance from shore; Distance to 40m depth; Sand; Mud; Gravel; Seabed disturbance; Tidal current; Chlorophyll a; Sea surface temp; Distance to plankton; Distance to prey (saved as .R data)</li> <li>Model objects, R code, and model outputs of the Boosted Regression Tree modelling.</li> <li>Predicted monthly distributions (and associated spatially explicit uncertainty) of Bryde's whales, common dolphins, bottlenose dolphins, bronze whaler sharks, pelagic sharks, immature hammerhead sharks, and richness of large marine predators in the Hauraki Gulf, New Zealand, (January to December). Monthly richness estimates of large marine predators.</li> </ul>
Figure 1 in First record of genus Paradota Ludwig & Heding in New Zealand waters and description of a new species (Echinodermata: Holothuroidea: Synaptida)
Figure 1. Paradota plentyensis sp. nov. holotype (A–D, NIWA 87163): A, specimen view; B, anterior view including tentacle crown; C, close up of tentacles showing 10 lobes; D, ossicle rods from tentacles.
Seismic dataset for Ruapehu and Whakaari volcanoes in New Zealand
<p>RSAM, MF, HF and DSAR time series for Ruapehu stations FWVZ over the 14 years explored, and for Whakaari stations WIZ over 9 years.</p> <p>Computing datastreams: we harnessed seismic data from a vertical component station for each individual volcano. We applied data processing techniques that resulted in the generation of four distinct time series, with a sampling interval of 10 minutes. Various measures were employed to capture different aspects of the seismic signal. The first measure, known as the Real-time Seismic Amplitude Measurement (RSAM), was obtained by calculating the 10-minute moving average of the velocity recorded by the vertical station This signal was then subjected to bandpass filtering within the frequency range of 2 to 5 Hz, which focuses on tremor signal of frequent volcanic origin while excluding ocean noise at lower frequencies. Similarly, the Median Frequency (MF) and High Frequency (HF) measures were derived using a comparable approach to RSAM, but with specific bandpass filtering applied. MF was obtained by filtering the signal within the frequency range of 4.5 to 8 Hz, while HF was obtained by filtering within the frequency range of 8 to 16 Hz. The 4.5 Hz threshold between RSAM and MF reflects an assumption that tremor mostly radiates energy below 4.5 Hz. To exclude this effect and explore attenuation related to permeability change (such as sealing), this frequency value is used as a threshold. Lastly, the Displacement Seismic Amplitude Ratio (DSAR) was calculated as the ratio of the integrals of the MF and HF signals. High values of DSAR have been inferred to correlate with high gas levels in the edifice, suggesting either reduced fluid motion and/or trapping that has led to a gas-accumulation.</p>
Slip deficit rate realizations for 2023 New Zealand National Seismic Hazard Model geodetic inversions
<p>This data set contains inversion results presented in Johnson et al. (2023) and also Johnson et al. (2022). All calculations involving slip deficit rates in those papers were conducted using the results in the files provided in this data set. </p>
Aotearoa New Zealand RSQSim model outputs for tsunami modelling
<p>RSQSim model outputs to support the publication: "<strong>A Novel Method to Determine Probabilistic Tsunami Hazard using a Physics-based Synthetic Earthquake Catalog: a New Zealand Case Study</strong>" by Hughes et al. (2023; JGR, submitted). In many respects, these model outputs represent an updated version of the New Zealand RSQSim catalogue published by Shaw et al. (2022; <a href="http://doi.org/10.5281/zenodo.5534462">doi.org/10.5281/zenodo.5534462</a>).</p> <p>This archive contains:</p> <ol> <li>The outputs of an updated RSQSim synthetic earthquake catalogue for Aotearoa-New Zealand.</li> <li>A ~30kyr subset of the main catalogue, trimmed to a minimum M<sub>W</sub> of 7.0.</li> <li>Summary figures comparing the statistical properties of the synthetic catalogue to observations of New Zealand seismicity.</li> <li>Python scripts for visualizing the synthetic earthquake catalogue, and calculating seafloor displacements from synthetic earthquakes that can be used as tsunami model inputs.</li> </ol> <p>For more information, please refer to the publications cited above and/or the more detailed README files within the archive.</p>
Data for: Range reshuffling: climate change, invasive species, and the case of Nothofagus forests in Aotearoa New Zealand
<p class="MsoNormal"><strong>Aim: </strong></p> <p class="MsoNormal">The impact of climate change on forest biodiversity and ecosystem services will be partly determined by the relative fortunes of invasive and native forest trees under future conditions. Aotearoa New Zealand has high conservation value native forests and one of the world's worst invasive tree problems. We assess the relative effects of habitat redistribution on native <em>Nothofagus </em>and invasive conifer (Pinaceae) species in New Zealand as a case study on the compounding impacts of climate change and tree invasions.</p> <p class="MsoNormal"><strong>Location: </strong></p> <p class="MsoNormal">Aotearoa New Zealand</p> <p class="MsoNormal"><strong>Methods: </strong></p> <p class="MsoNormal">We use species distribution models (SDMs) to predict the current and future distribution of habitat for five native <em>Nothofagus</em> species and 13 invasive conifer species under two 2070 climate scenarios. We calculate habitat loss/gain for all species and examine overlap between the invasive and native species now and in the future. </p> <p class="MsoNormal"><strong>Results: </strong></p> <p class="MsoNormal">Most species will lose habitat overall. The native species saw large changes in the distribution of habitat with extensive losses in North Island and gains mostly in South Island. Concerningly, we found that most new habitat for <em>Nothofagus </em>was also suitable for at least one invasive species. However, there were refugia for the native species in the wetter parts of the climate space.</p> <p class="MsoNormal"><strong>Main conclusion:</strong></p> <p class="MsoNormal">If the predicted changes in habitat distribution translate to shifts in forest distribution it would cause widespread ecological disruption. We discuss how acclimation, adaptation and biotic interactions may delay some changes. But we also highlight how the poor migration and establishment capacity of native <em>Nothofagus</em> and the competitive ability of invasive conifers will be a persistent conservation challenge in areas of both new habitat and forest retreat. Pinaceae are problematic invaders globally, and our results highlight that control of invasions and active native forest restoration will likely be key to managing forest biodiversity under future climates.</p>
CarbonWatch-NZ: National Scale Inverse Modelling of New Zealand's Carbon Balance
<p>New Zealand flux estimates derived from the CarbonWatch-NZ national scale inverse modelling system (Bukosa<br> et al., 2023; Steinkamp et al., 2017), prepared for the publication "A comprehensive assessment of anthropogenic and natural sources and sinks of Australasia’s carbon budget" by Villalobos et al. (2023), part of the the second phase of the REgional Carbon Cycle Assessment and Processes (RECCAP-2). </p>
[Dataset] Green hydrogen exports in New Zealand and Chile can improve electricity supply security if configured as local energy insurance
<p>This file contains the main outputs of the preprint: "Green hydrogen exports in New Zealand and Chile can improve electricity supply security if configured as local energy insurance"</p>
Genome-wide analysis resolves the radiation of New Zealand’s freshwater Galaxias vulgaris complex and reveals a candidate species obscured by mitochondrial capture
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High-performing plastic clones best explain the spread of yellow monkeyflower from lowland to higher elevation areas in New Zealand
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Allen Brain Atlas
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.