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22 results for “disturbance patterns”
Patch metrics and landscape patterns of forest disturbances at the beginning of the 20th Century
<h1>Summary:</h1> <p>The database consists of a compressed .CSV file containing structural information of forest disturbance patches identified between 2002 and 2014 using the Global Forest Change Tree Cover Loss Year dataset version 1.6 (Hansen et al, 2013) available at https://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.6.html. Each row in the database represents a patch (249,149,911 in total). The columns (15) represent the structural metrics calculated for each patch, as well as the landscape patterns identified using kmeans cluster analysis. </p> <p>The methods used for building this database are published in the paper: Acil, N., Sadler, J.P., Senf, C. <em>et al.</em> Landscape patterns in stand-replacing disturbances across the world’s forests. <em>Nat Sustain</em> <strong>8</strong>, 86–98 (2025). <a href="https://doi.org/10.1038/s41893-024-01450-3">https://doi.org/10.1038/s41893-024-01450-3</a></p> <p>Aggregated global maps of the patch metrics can be visualised in <a href="https://ee-treemort-disturbances-nacil.projects.earthengine.app/view/patchmetrics2002-2014">Google Earth Engine</a> and accessed in the asset "http://projects/ee-treemort-disturbances-nacil/assets/PatchMetrics_Means_nonLU_2002-2014/". </p> <p>Some of the scripts associated with this project are hosted in <a href="https://github.com/N-Acil/GlobalForestDisturbances_PatchMetrics">GitHub</a> and <a href="https://code.earthengine.google.com/?accept_repo=users/NXA807/%20GlobalForestDisturbances_PatchMetrics">Google Earth Engine</a>.</p> <p>Additional scripts and data will be made available upon request.</p> <p> </p> <p> </p> <h1>Database structure: </h1> <h2>Patch metrics</h2> <h3>Occurrence: </h3> <p>Patch form and year were retrieved from the Global Forest Change tree cover loss year dataset version 1.6 (Hansen et al, 2013).</p> <table> <tbody> <tr> <td><strong>Column name</strong></td> <td><strong>Description</strong></td> <td><strong>Unit</strong></td> <td><strong>Format</strong></td> <td><strong>Valid values</strong></td> </tr> <tr> <td><strong>PID</strong></td> <td>Patch unique identifier in the format Tile_Year_PatchNumber (e.g. 01U_02_00000001).</td> <td> </td> <td>Characters</td> <td> </td> </tr> <tr> <td><strong>X_INT_deg</strong></td> <td>Longitude of the patch's internal centroid</td> <td>Degrees</td> <td>Float</td> <td>[-180-180]</td> </tr> <tr> <td><strong>Y_INT_deg</strong></td> <td>Latitude of the patch's internal centroid</td> <td>Degrees</td> <td>Float</td> <td>[-90-90]</td> </tr> <tr> <td><strong>YEAR_maj</strong></td> <td>Year of patch majority occurrence. </td> <td> </td> <td>Integer</td> <td>[2-14]</td> </tr> <tr> <td><strong>YEAR_n</strong></td> <td>Number of years over which the patch exhibited continuous growth.</td> <td> </td> <td>Integer</td> <td>>0</td> </tr> </tbody> </table> <h3>Metrics: </h3> <p>These patch and landscape metrics were calculated from the patch delineated.</p> <table> <tbody> <tr> <td><strong>Column name</strong></td> <td><strong>Description</strong></td> <td><strong>Unit</strong></td> <td><strong>Format</strong></td> <td><strong>Valid values</strong></td> </tr> <tr> <td><strong>AREA_G_ha</strong></td> <td>Patch geodesic area</td> <td>Hectares</td> <td>Float</td> <td>>0</td> </tr> <tr> <td><strong>PERIM_G_m</strong></td> <td>Patch geodesic perimeter</td> <td>Meters</td> <td>Float</td> <td>>0</td> </tr> <tr> <td><strong>PARA</strong></td> <td>Perimeter-area ratio</td> <td> </td> <td>Float</td> <td>>0</td> </tr> <tr> <td><strong>SHAPE</strong></td> <td>Shape index</td> <td> </td> <td>Float</td> <td>>=1</td> </tr> <tr> <td><strong>ELONG</strong></td> <td>Elongation index</td> <td> </td> <td>Float</td> <td>[0-1[</td> </tr> <tr> <td><strong>FRAC</strong></td> <td>Fractal dimension index</td> <td> </td> <td>Float</td> <td>[1-2]</td> </tr> <tr> <td><strong>NN5000_T0_n</strong></td> <td>Number of patches assigned the same year within 5 km radius.</td> <td> </td> <td>Integer</td> <td>>0</td> </tr> <tr> <td><strong>NN5000_AREA_T0_perc</strong><strong><br></strong></td> <td>Percent of the total area disturbed over the period 2001-2018 within 5 km radius from the focal patch centroid.</td> <td>%</td> <td>Float</td> <td>[0-100]</td> </tr> </tbody> </table> <h3>Clusters:</h3> <p>Cluster identification was performed using AREA_G_ha, YEAR_n, SHAPE, ELONG, NN5000_T0_n and NN5000_AREA_T0_perc. </p> <table> <tbody> <tr> <td><strong>Column name</strong></td> <td><strong>Description</strong></td> <td><strong>Unit</strong></td> <td><strong>Format</strong></td> <td><strong>Valid values</strong></td> </tr> <tr> <td><strong>CLUSTER_CODE</strong></td> <td>Code assigned to each cluster</td> <td> </td> <td>Integer</td> <td>[1-4]</td> </tr> <tr> <td><strong>CLUSTER_LABEL</strong></td> <td>Name given to the cluster identified. </td> <td> </td> <td>Character</td> <td> <ul> <li>Small-isolated</li> <li>Clustered</li> <li>Complex</li> <li>Large-multiyear</li> </ul> </td> </tr> </tbody> </table> <p> </p>
The influence of human disturbances on the spatio-temporal habitat selection patterns of roe deer near Trento (Italy)
<p>This is the dataset used for the MSc. thesis of Matthijs Hinkamp for the master Earth Sciences (Environmental Management track) at the University of Amsterdam.</p> <p>In this thesis the Individual Movement Sequence Analysis Method (IM-SAM) was applied to analyse the influence of human disturbances on the sequential habitat use of roe deer in northern Italy. While it is known that in this area the roe deer populations are affected by anthropogenic pressures, the actual spatial and temporal implications of such pressures are unknown.</p> <p>The input for IM-SAM consisted of habitat sequences, which were obtained through tracking data from the Fondazione Edmund Mach, land use and land cover maps and temporal information. Based on exploratory dissimilarity trees for the real behavioural sequences, several simulation profiles were established, each with a different habitat use pattern.</p> <p>The results show that most roe deer prefer isolated forest areas, but alternating patterns are definitely present. Several co variables were assessed: the influence of the hunting season, increased pressure during weekends, differences between protected and unprotected areas and changes in the average NDVI. It seems that roe deer are affected by the hunting pressure in September. This month shows an increase in the prevalence of alternating profiles, which indicates that roe deer tend to change their habitat use during periods of the day when hunting takes place. It cannot be concluded that habitat use patterns are altered during the weekends and the differences between sequences in protected and unprotected areas seem to be relatively small. However, some results indicate that alternating habitat use is a strategy for some roe deer in protected areas. When looking at the NDVI values, it becomes clear that the average NDVI is higher overall for the alternating profiles, but this just underlines the general conclusions drawn about the habitat use strategies in September.</p>
Wildlife Diversity and the Impact of Human Disturbance on Activity Patterns: A Case Study of the Labagoumen Nature Reserve, Beijing, China
<p>This version updates the dataset to reflect revised analyses in the resubmitted manuscript to Ecology and Evolution.</p> <p><strong>Title:</strong><br><strong>Data and Code for "Wildlife Diversity and the Impact of Human Disturbance on Activity Patterns: A Case Study of the Labagoumen Nature Reserve, Beijing, China"</strong></p> <p><strong>Description:</strong><br>This dataset contains the raw data and R scripts used to generate specific figures in the manuscript <em>"Wildlife Diversity and the Impact of Human Disturbance on Activity Patterns: A Case Study of the Labagoumen Nature Reserve, Beijing, China,"</em> submitted to <em>Ecology and Evolution</em>. The data were collected from infrared camera traps deployed in the Labagoumen Nature Reserve, Beijing, China, between 2019 and 2022. The dataset includes species detection records, timestamps, and information relevant to assessing the effects of human disturbance on wildlife activity patterns.</p> <p>The accompanying R scripts facilitate data processing, statistical analyses, and figure generation, enabling reproduction of the key results. This dataset may be useful for researchers interested in spatiotemporal wildlife monitoring, human-wildlife interactions, and disturbance ecology.</p> <p><strong>Contents:</strong></p> <ul> <li>raw data (Excel format, <code>.xlsx</code>)</li> <li>R scripts for data analysis and figure generation of <strong>Figures 3-5</strong> (from the raw data file "raw data.xlsx") (Text format, .doc).</li> <li> <p><strong>Figure 1</strong>: Created using <span>ArcMap 10.8 software</span> and Photoshop software. <span>ArcMap 10.8 software </span>was used for processing spatial data and map creation, while Photoshop was used for post-processing and image enhancement.</p> </li> <li> <p><strong>Figure 2 and Appendix Figure. A1</strong>: Designed and modified using Photoshop software.</p> </li> </ul>
Temporal patterns of gut microbiota in lemurs (Eulemur rubriventer) living in intact and disturbed habitats.
<p>This data set includes the R scripts (combined into one R markdown document) and input files needed to create the main text figures and major analyses for the paper "Grieneisen L, Hays A, Cook E, Blekhman R, and Tecot S. 2024. Temporal patterns of gut microbiota in lemurs (<em>Eulemur rubriventer</em>) living in intact and disturbed habitats. American Journal of Primatology." </p>
Data from: Human disturbance and the activity patterns and temporal overlap of tapirs and jaguars in reserves of NW Belize.
<p>Human disturbance from tourism and other non-consumptive activities in protected areas may be stressful to wildlife. Animals may move away in space or time to avoid human interaction. For species of particular conservation concern, such as Baird's tapirs (<i>Tapirus bairdii)</i> and jaguars (<i>Panthera onca</i>), a better understanding of how they respond to different levels and types of disturbance is needed in order to manage human visitation to parks in ways that minimize negative outcomes for wildlife. We describe the overlap of activity patterns of tapirs, jaguars, and humans at logged and unlogged sites and at places with low versus high human visitation using camera survey data from protected areas of northwest Belize, 2013-2016. Tapirs were nocturnal in all study sites, with >80 percent of all tapir detections occurring between 1900 h and 0500 h. Their activity patterns were not different in unlogged versus logged sites and did not change with increased human traffic. Jaguars were cathemeral across sites, but had more nocturnal activity at the site with the most human impact. Activity pattern overlap between tapirs and jaguars did not differ significantly between logged and unlogged sites, nor between areas with low and high human activity. Human traffic increased from 2013-2016 at most of the study locations. In conclusion, this camera trap dataset suggests that non-consumptive human disturbance does not alter the activity patterns of tapirs and jaguars in protected areas lacking hunting pressure.</p>
Data from: Contrasting patterns of population structure at large and fine scales in an avian disturbance specialist of braided river ecosystems
Aim: To understand the population structure and its potential drivers at different spatial scales in a migratory bird, the black-fronted tern (Chlidonias albostriatus); a specialist of the spatially and temporally dynamic environments of braided rivers. Location: New Zealand Methods: We used a three-pronged approach based on 17 microsatellites, two mitochondrial loci (cytochrome b / control region), and phenotypic data (head-bill length, bill depth, wing length, weight). We determined large-scale genetic structure throughout the whole breeding range (approx. 150,000 km2), calculated genetic divergence of breeding populations, and tested for isolation-by-distance between populations. We investigated the level of fine-scale genetic structure based on spatial autocorrelation analyses and assessed the presence of a body size cline based on phenotypic data. Lastly, we compared phenotypic divergence (PST) and the level of divergence by genetic drift (FST) among breeding populations to test for underlying mechanisms of population differentiation. Results: Nuclear and mitochondrial DNA showed that across their range black-fronted terns were effectively panmictic, with low genetic divergence between breeding colonies overall and no isolation-by-distance. However, at fine geographical scales black-fronted terns accrued significant genetic structure for distances up to 75 km, primarily driven by males, indicating more frequent female dispersal. Furthermore, a phenotypic cline in accordance with Bergmann's rule was evident. PST exceeded FST in three traits, suggestive of local adaptation. Main conclusions: Significant fine-scale structure can be present in highly mobile, specialist species while not affecting spatial structures at larger scales. Hence, methodologies applied to both whole landscapes and local scales are important to appropriately estimate connectivity in dynamic metapopulations and investigate the processes behind connectivity. Conservation management will need to include protecting currently uninhabited patches to facilitate natural colonisation of suitable habitat. For black-fronted terns, managing whole catchments throughout the entire breeding range would be preferable to managing single patches.
Data from: Temporal patterns in the abundance of a critically endangered marsupial relates to disturbance by roads and agriculture
The aim of this study was to investigate how landscape disturbance associated with roads, agriculture and forestry influenced temporal patterns in woylie (Bettongia penicillata) abundance before, during and after periods of rapid population change. Data were collected from an area of approximately 140,000 ha of forest within the Upper Warren region in south-western Australia. Woylie abundance was measured using cage trapping at 22 grid and five transect locations with varying degrees of landscape disturbance between 1994 and 2012. We found evidence that the distribution and abundance of woylies over time appears to be related to the degree of fragmentation by roads and proximity to agriculture. Sites furthest from agriculture supported a greater abundance of woylies and had slower rates of population decline. Sites with fewer roads had a greater abundance of woylies generally and a greater rate of increase in abundance after the implementation of invasive predator control. The results of this study suggest that landscape disturbance is less important at peak population densities, but during times of environmental and population change, sites less dissected by roads and agriculture better support woylie populations. This may be due to the role these factors play in increasing the vulnerability of woylies to introduced predators, population fragmentation, weed species invasion, mortality from road collisions or a reduction in available habitat. Strategies that reduce the impact of disturbance on woylie populations could include the rationalisation of forest tracks and consolidation of contiguous habitat through the acquisition of private property. Reducing the impact of disturbance in the Upper Warren region could improve the resilience of this critically important woylie population during future environmental change.
Deccan region, Madras, India. Genus Vandeleuria is masculine, so widely used specific name oleracea has been changed for gender agreement. Vandeleuria oleraceusis possibly a composite of species. Polytypic, but subspecific taxonomy requires reassessment. Distribution. Widespread in S Asia (India, Nepal, Bhutan, Bangladesh, and Sri Lan-ka), S China (W & S Yunnan), and mainland SE Asia N of the Isthmus of Kra. Descriptive notes. Head-body 68 mm, tail 105 mm, ear 13 mm, hindfoot 17 mm; weight 10 g. The Indomalayan Long-tailed Climbing Mouse is small, with flat nail on outer finger and outertoe; tail is slender, brown, twice as long as head-body length, and lacks distal tuft. Dorsal pelageis silky and salmon in color; venter is white, with fulvous hues. Habitat. Tall cane and tangled vines in primary and secondary forest such as bamboo forest, moist deciduous forest, temperate forests, montane wet zone, and disturbed secondary forests, and perhaps agricultural areas at elevations of 150-1500 m. Food and Feeding. Indomalayan [Long-tailed Climbing Mice eat fruits, buds, and flowers. Breeding. Litters of the Indomalayan Long-tailed Climbing Mouse have 3-6 young. Activity patterns. Indomalayan Long-tailed Climbing Mice are arboreal and nocturnal, although one individual was caught duringthe day. Movements, Home range and Social organization. Indomalayan Long-tailed Climbing Mice build nests in tall bushes or cane to rear their young. Status and Conservation. Classified as Least Concern on The IUCN Red Last (as V. olacea). The Indomalayan Long-tailed Climbing Mouse occurs in several habitats and a wide distribution that includes national parks. Further taxonomical studies are required to assess conservation status ofthis potentially diverse species complex. Bibliography. Corbet & Hill (1992), Dang Huy Huynh et al. (1994), Ellerman (1941), Marshall (1977b), Musser & Carleton (2005), Osgood (1932), Phillips (1980), Wang Yingxiang (2003). in Muridae
Deccan region, Madras, India. Genus Vandeleuria is masculine, so widely used specific name oleracea has been changed for gender agreement. Vandeleuria oleraceusis possibly a composite of species. Polytypic, but subspecific taxonomy requires reassessment. Distribution. Widespread in S Asia (India, Nepal, Bhutan, Bangladesh, and Sri Lan-ka), S China (W & S Yunnan), and mainland SE Asia N of the Isthmus of Kra. Descriptive notes. Head-body 68 mm, tail 105 mm, ear 13 mm, hindfoot 17 mm; weight 10 g. The Indomalayan Long-tailed Climbing Mouse is small, with flat nail on outer finger and outertoe; tail is slender, brown, twice as long as head-body length, and lacks distal tuft. Dorsal pelageis silky and salmon in color; venter is white, with fulvous hues. Habitat. Tall cane and tangled vines in primary and secondary forest such as bamboo forest, moist deciduous forest, temperate forests, montane wet zone, and disturbed secondary forests, and perhaps agricultural areas at elevations of 150-1500 m. Food and Feeding. Indomalayan [Long-tailed Climbing Mice eat fruits, buds, and flowers. Breeding. Litters of the Indomalayan Long-tailed Climbing Mouse have 3-6 young. Activity patterns. Indomalayan Long-tailed Climbing Mice are arboreal and nocturnal, although one individual was caught duringthe day. Movements, Home range and Social organization. Indomalayan Long-tailed Climbing Mice build nests in tall bushes or cane to rear their young. Status and Conservation. Classified as Least Concern on The IUCN Red Last (as V. olacea). The Indomalayan Long-tailed Climbing Mouse occurs in several habitats and a wide distribution that includes national parks. Further taxonomical studies are required to assess conservation status ofthis potentially diverse species complex. Bibliography. Corbet & Hill (1992), Dang Huy Huynh et al. (1994), Ellerman (1941), Marshall (1977b), Musser & Carleton (2005), Osgood (1932), Phillips (1980), Wang Yingxiang (2003).
Analyzing Gait Pattern Using Insole-type Gait Analyzer in Patient With Gait Disturbance
ClinicalTrials.gov study NCT06442982. IPD Sharing: NO. Countries: 1. Publications: 8.
Data from: Human disturbance and the activity patterns and temporal overlap of tapirs and jaguars in reserves of NW Belize.
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Data from: Contrasting patterns of population structure at large and fine scales in an avian disturbance specialist of braided river ecosystems
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Data from: Temporal patterns in the abundance of a critically endangered marsupial relates to disturbance by roads and agriculture
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Data from: Linking radial growth patterns and moderate-severity disturbance dynamics in boreal old-growth forests driven by recurrent insect outbreaks: a tale of opportunities, successes, and failures
<p>In boreal landscapes, emphasis is currently placed on close-to-nature management strategies, which aim to maintain the biodiversity and ecosystem services related to old-growth forests. The success of these strategies, however, depends on an accurate understanding of the dynamics within these forests. This study aims to reconstruct the disturbance and post-disturbance dynamics in boreal old-growth forests that are driven by recurrent moderate-severity disturbances. We studied eight old-growth forests in Québec, Canada, that has recorded recurrent and moderate to severe spruce budworm (Choristoneura fumiferana [Clem.]) outbreaks over the 20th century. To reconstruct the disturbance history and the post-disturbance dynamics of the study sites, we used dendrochronological data and k-means clustering to identify growth releases and growth patterns in the studied trees. We identified nine growth patterns; these patterns represented trees differing in age, size, and canopy layer, and indicated different tree histories. Spruce budworm outbreaks caused recurrent moderate-severity disturbances within the study sites. The canopy gaps created by these disturbances were filled mainly by understorey trees, which responded by single and significant increases in radial growth and height. In contrast, overstorey trees had little influence on gap filling; thus, trees were mostly from the dominant and codominant canopy layers. Our study underlines the resistance of boreal old-growth forests to recurrent and moderate-severity disturbances, as understorey trees can rapidly fill the resulting gaps. However, trees that are unable to attain the canopy following the disturbance then tend to remain in the lower canopy layers. Therefore, reaching the canopy represents a once-in-a-lifetime opportunity, where success or failure depends on a relatively short window of time. This gap-filling dynamic produces, however, a vertical structure that is often similar to the expected structure in even-aged forests. Our results highlight the efficacy of identifying tree growth patterns to reconstruct stand disturbance dynamics and contribute to developing closer to nature forest management strategies.</p>
Temporal patterns of forest seedling emergence across different disturbance histories data
<p>Forest ecosystems experience a myriad of natural and anthropogenic disturbances that shape ecological communities. Seedling emergence is a critical, preliminary stage in the recovery of forests post-disturbance and is triggered by a series of abiotic and biotic changes. However, the long-term influence of different disturbance histories on patterns of seedling emergence is poorly understood.</p> <p>Here, we address this research gap by using an 11-year dataset gathered between 2009 and 2020 to quantify the influence of different histories of natural (wildfire) and anthropogenic (clearcut and post-fire salvage logging) disturbances on emerging seedlings in early successional Mountain Ash forests in south-eastern Australia. We also describe patterns of seedling emergence across older successional forests varying in stand age (stands that regenerated in <1900s, 1939, 1970-90 and 2007-11).</p> <p>Seedling emergence was highest in the first three years post-disturbance. Stand age and disturbance history significantly influenced the composition and abundance of plant seedlings. Specifically, in salvage logged forests, plant seedlings were the most different from similarly aged forests with other disturbance histories. For instance, relative to clearcut and unlogged, burnt forests of the same age, salvage logging had the lowest overall richness, the lowest counts of <i>Acacia </i>seedlings, and an absence of common species including <i>Acacia obliquinervia, Acacia frigescens, Cassinia arcuealta, Olearia argophylla, Pimelea axiflora, Polyscias sambucifolia </i>and <i>Prosanthera melissifolia</i> over the survey period.</p> <p><i>Synthesis:</i> Our findings provide important new insights into the influence of different disturbance histories on regenerating forests and can help predict plant community responses to future disturbances, which may influence forest recovery under altered disturbance regimes.</p>
Disturbance and the (surprising?) role of ecosystem engineering in explaining spatial patterns of non-native plant establishment
<p>The Intermediate Disturbance Hypothesis is widely considered to be wrong but is rarely tested against alternative hypotheses. It predicts that soil disturbances and herbivory have identical impacts on species richness via identical mechanisms (reduction in biomass and in competition). An alternative hypothesis is that the specific traits of disturbance agents (small mammals) and plants differentially affects richness or abundance of different plant groups. We tested these hypotheses on a degu (<em>Octodon degus</em>) colony in central Chile. We ask whether native and non-native forbs respond differently to degu bioturbation on runways vs. herbivory on grazing lawns. We ask whether this can explain the increase in non-native plants on degu colonies. We found that biopedturbation did not explain the locations of non-native plants. We did not find direct evidence of grazing increasing non-native herbs either, but a grazing effect appears to be mediated by grass, which is the dominant cover. Further, we provide supplementary evidence to support our interpretation that a key mechanism of non-native spread is the formation of dry soil conditions on grazing lawns. Thus ecosystem engineering (alteration of soil qualities) may be an outcome of disturbances, which each interact with specific plant traits, to create the observed pattern of non-native spread in the colony. Based on these results we propose to extend Jentsch & White's (2019) concept of combined pulse/ disturbance events to the long-term process duality of ecosystem engineering/ disturbance.</p>
Edge disturbance shapes liana diversity and abundance but not liana-tree interaction network patterns in moist semi-deciduous forests, Ghana
<p>Edge disturbance can drive liana community changes and alter liana-tree interaction networks, with ramifications for forest functioning. Understanding edge effects on liana community structure and liana-tree interactions is therefore essential for forest management and conservation. We evaluated the response of liana community structure and the patterns of liana-tree interaction structure to forest edge in two moist semi-deciduous forests in Ghana (Asenanyo and Suhuma Forest Reserves: AFR and SFR, respectively). Liana community structure and liana-tree interactions were assessed in 24 50 × 50 m randomly located plots in three forest sites in each forest: edge, interior and deep-interior established at 0-50 m, 200 m and 400 m from edge. Edge effects positively and negatively influenced liana diversity in forest edges of AFR and SFR, respectively. There was a positive influence of edge disturbance on liana abundance in both forests. We observed anti-nested structure in all the liana-tree networks in AFR, while no nestedness was observed in the networks in SFR. The networks in both forests were less connected, and thus more modular and specialised than their null models. Many liana and tree species were specialised, with specialisation tending to be symmetrical. The plant species played different roles in relation to modularity. Most of the species acted as peripherals (specialists), with only a few species having structural importance to the networks. The latter species group consisted of connectors (generalists) and hubs (highly connected generalists). Some of the species showed consistency in their roles across the sites, while the roles of other species changed. Generally, liana species co-occurred randomly on tree species in all the forest sites, except edge site in AFR where lianas showed positive co-occurrence. Our findings deepen our understanding of the response of liana communities and liana-tree interactions to forest edge disturbance, which are useful for managing forest edge.</p>
Temporal patterns of forest seedling emergence across different disturbance histories data
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Edge disturbance shapes liana diversity and abundance but not liana-tree interaction network patterns in moist semi-deciduous forests, Ghana
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Data from: Linking radial growth patterns and moderate-severity disturbance dynamics in boreal old-growth forests driven by recurrent insect outbreaks: a tale of opportunities, successes, and failures
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Disturbance and the (surprising?) role of ecosystem engineering in explaining spatial patterns of non-native plant establishment
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.