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1,513 results for “disturbance”
Data from: Aquatic ecosystem responds differently to press and pulse nutrient disturbances as revealed by a microcosm experiment
<p><span>Due to climate change and increasing anthropogenic activities, lakes are disturbed frequently, usually by press (e.g., diffused pollution, rising temperatures) or pulse (e.g., storms, rainfall, pollution events) disturbances. Both press and pulse disturbances can affect abiotic and biotic environments, changing the structure of ecosystems and affecting ecosystem services. To confront with the effects of climate change and increasing anthropogenic activities, understanding the different effects of press and pulse disturbances on lake ecosystems is essential. This study assessed the effect of press and pulse disturbances of phosphorus on a microcosmic </span><span>aquatic </span><span>eco</span><span>system</span><span> by measuring the total phosphorus (TP), algae density, and physiological indicators of submerged macrophytes. We found that the microcosmic aquatic ecosystem responded differently to press and pulse disturbances. Our results suggested that it had a lower resistance to pulse phosphorus disturbances than to press phosphorus disturbances. There were significantly higher nutrient concentrations and algal densities in the pulse treatment than in the press treatment. Positive feedback was found between the biomass of submerged macrophytes and the water quality. There was a higher submerged macrophytes biomass at low TP concentration and algal density. In the context of climate change, press and pulse disturbances could have severe impacts on lake ecosystems. Our findings will provide some insight for further research and lake management.</span></p>
Monitoring GPS-collared moose by ground versus drone approaches: efficiency and disturbance effects
<p>Efficient wildlife management requires precise monitoring methods, e.g., to estimate population density, reproductive success, and survival. Here, we compared the efficiency of the drone (equipped with an RGB camera) and ground approaches to detect and observe GPS-collared female moose (<em>Alces alces</em>) and their calves. Moreover, we quantified how drone (n = 42) and ground (n = 41) approaches affected moose behavior and space use (n = 24 individuals). The average time used for drone approaches was 17 minutes compared to 97 minutes for ground approaches, with drone detection probability being higher (95% of adult female moose and 88% of moose calves) compared to ground approaches (78% of adult females and 82% of calves). Drone detection success increased at lower drone altitudes (50-70 m). Adult female moose left the site in 35% of drone approaches (with > 40% of those moose becoming disturbed once the drone hovered < 50 m above ground) compared to 56% of ground approaches. We failed to find short-term effects (3-h after approaches) of drone approaches on moose space use, but moose moved > 4-fold greater distances and used larger areas after ground approaches (compared to before the approaches had started). Similarly, longer-term (24-h before and after approaches) space use did not differ between drone approaches compared to days without known disturbance, but moose moved comparatively greater distances during days of ground approaches. In conclusion, we could show that drone approaches were highly efficient in detecting adult moose and their calves in the boreal forest, being faster and less disturbing than ground approaches, making them a useful tool to monitor and study wildlife.</p>
Standing and shed litters alter plant growth in disturbed and undisturbed soils differently
<p>Plant species affect key ecosystem processes like nutrient cycling and overall ecosystem productivity through their litter. The outcome of litter effects is largely determined by its decomposability, which directly effects soil properties. If litter remains standing or unshed (i.e. marcescent), its final decomposability can be increased by photodegradation of recalcitrant structures (like lignin). If the litter is immediately shed, its decomposability largely depends on its original nutrient content. Moreover, plant species may affect soil also through other, more direct effects. It is however unknown whether marcescent and immediately shed litters affect soil, and by that plants, differently, whether direct effects of plants on soil interact with those of marcescent and shed litters, and whether these interactions are consistent under different soil conditions.</p> <p>We set up a pot experiment, where we tested the effects of originally marcescent and shed litters (both added on the soil surface of the pots) on three grassland species (<em>Bromus erectus</em>, <em>Filipendula vulgaris</em>, and <em>Plantago media</em>) in contrasting soils from long-term stable ancient grassland and grassland restored on arable land 20 years before. We also tested how litter types and plant species affect soil chemical properties and microbial community (characterised by PLFA markers).</p> <p>Marcescent litter contained a lower amount of nutrients, but still increased plant biomass more than shed litter, although only for <em>F. vulgaris</em> (likely due to mobilisation of soil nutrients).</p> <p>The effect of litter on soil chemical properties and microbial community was low. These were largely affected by the plant species growing in the pot. The effect of these species on the microbial community was stronger in the undisturbed soil of ancient grasslands, while plant species affected mainly chemical properties in disturbed soil of restored grasslands. <em>B. erectus</em> slowed down the decomposition of both litter types in restored grassland soil.</p> <p>The effect of marcescent litter on living plants was significant but species-specific and depended on soil conditions. Marcescence seems to have a stronger effect on plants in disturbed soil, which indicates its importance for recovery of the ecosystem after disturbance.</p>
Dataset for: Abrupt changes in algal biomass of thousands of US lakes are related to climate and are more likely in low-disturbance watersheds
<p><span>These datasets include both the raw data and the model results from a project exploring causal relationships between climate and lake productivity of a diverse set of 24,452 US lakes over 34 years (1984-2008). <span>Climate change is expected to increase lake productivity and algal blooms and cause regime shifts, particularly in human-impacted ecosystems. First we assessed the potential for</span> nonlinear dynamics in summer median lake chlorophyll (CHL; derived from remote sensing) to demonstrate the potential for regime shifts in these lakes; second, we modeled the causal effects of climate on lake CHL over the 34 years. Climate was causally related to CHL in 34% of lakes; of those, 71% exhibited abrupt shifts, but only 13% had the potential for regime shifts. Climate-influenced lakes had low productivity at environmental extremes and experienced some directional climate change. Our synthesis of 24,452 time series demonstrates that effects of climate on lake productivity depend on recent climate change interacting with human impact and environmental context.</span></p>
Data from: Frequency-dependent tolerance to aircraft disturbance drastically alters predicted impact on shorebirds
<p>This data package includes data and R script belonging to the publication "Frequency-dependent tolerance to aircraft disturbance drastically alters predicted impact on shorebirds" by van der Kolk et al. (2024) in Ecology Letters.</p> <p>The script analysis_figures_vanderKolketal2024.R can be used to reproduce all analysis and figures in the manuscript. The Figures are stored in the Output folder.</p> <p>The data folder includes an excel file with metadata explaining all columns in the csv files.</p>
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 Accompanying "Leveraging successional facilitation to improve restoration of foundational dune grasses along a frequently disturbed coastline"
<div> <h1>Experimental Data accompanying "Leveraging successional facilitation to improve restoration of foundational dune grasses along a frequently disturbed coastline"</h1> Authors: Hallie Fischman, Copeland Cromwell, Joe Morton, Ralph Temmink, Tjisse van der Heide, Pete Adams, Christine Angelini <h1>Manuscript Abstract</h1> <a href="https://github.com/halliefischman1/Dune-Succession/blob/main/README.md#manuscript-abstract"></a></div> <p>Coastal ecosystems provide critical storm and flood protection services, but are rapidly degrading worldwide, making their restoration urgent. Here, we evaluated whether successional facilitation, where pioneers facilitate climax species, could be leveraged to accelerate coastal dune revegetation. A survey spanning 270km of Southeast US coastline revealed that Panicum amarum (bitter panicum) supported higher plant richness than Uniola paniculata (sea oats), and that sea oat cover was 230% greater on mature dunes than disturbed dunes, suggesting bitter panicum functions as a pioneer and sea oats is a climax species. A reciprocal transplant experiment confirmed this interpretation: bitter panicum stem production and height fell by 37% and >20 cm, respectively, when planted proximate to sea oats versus in isolation, whereas sea oats produced 38% more and >12 cm taller stems when planted proximate to bitter panicum versus in isolation. A second experiment evaluating the density-dependence of this facilitative interaction revealed that sea oats transplanted into low densities of bitter panicum grew >15% taller than isolated and high-density treatments. However, within seven months, wave inundation eliminated >60% propagules in both experiments. To explore foredune inundation frequency and its implications for dune revegetation, we applied empirical wave runup models at 101 locations throughout Volusia County, Florida. While disturbance frequency varied seasonally and annually, sites with low dune crests and steep beach slopes experienced frequent inundation (>50 events/year). Given the interactions between geomorphology and vegetation success, we present decision matrix to guide managers in determining optimal revegetation methods tailored to project goals and site conditions.</p> <div> <h1>Methods and Data Description</h1> <a href="https://github.com/halliefischman1/Dune-Succession/blob/main/README.md#methods-and-data-description"></a></div> <p>Experiment 1: Uniola paniculata (sea oats) and panicum amarum (bitter panicum) were planted in one of three treatments. Controls are in bare areas, Adjacent treatments (adj) are planted 50cm away from naturally occuring patches of the other species (ie, SO-adj-NPA is sea oats planted adjacent to natural bitter panicum), and Within treatments are planted in a naturally occuring patch of the other species (ie, SO-in-NPA is sea oats planted into a patch of natural bitter panicum). Each replicate consisted of 5 transplant propagules in an X configuration. At each monitoring, all stems were counted and the maximum height of each plot was measured. Plot treatments were reassigned during monitoring, if needed, such that any plot with the heterospecific growing within the 0.25 m2 area was considered a “within plot” and any plot with the heterospecific <50 cm away was considered an “adjacent plot”. See maunscript for additional details.</p> <p>Experiment 2: Sea oats were planted in the same configuration (5 propagules in an X) surrounded by varrying densities of natural bitter panicum. At each monitoring, we counted all bitter panicum stems within a 1m radius of the transplant, all propogule stems, and measured the height of the tallest transplant in each plot. Treatments were binned based on the number of surrounding bitter panicum stems at the final monitoring point: “Zero”, containing no stems within the 1 m radius (n=20 plots); “Low”, 1-9 stems in the surrounding 1 m radius (n=46 plots); “Mid” 10-34 stems in the 1 m radius (n=29 plots); and “High”, 35-70 stems in the 1m radius (n=25 plots). See manuscript for additional details.</p> <p>Datasets contains stem counts and heights of planted grasses over time. Stem counts are provided for each of the 5 propagules that comprise a single experimental unit, and a single maximum height is provided per plot. Plots were monitored approximately bimonthly until grasses were eroded by waves (see manuscript). Additional information on treatments are provided in the manuscript and data methods sections.</p>
Data from: Behavioural responses of brown bears to roads and hunting disturbance
<p>Harvest regulations commonly attenuate the consequences of hunting on specific segments of a population. However, regulations may not protect individuals from non-lethal effects of hunting and their consequences remain poorly understood. In this study, we compared the movement rates of Scandinavian brown bears (Ursus arctos, n = 47) across spatiotemporal variations in risk in relation to the onset of bear hunting. We tested two alternative hypotheses based on whether behavioural responses to hunting involve hiding or escaping. If bears try to reduce risk exposure by avoiding being detected by hunters, we expect individuals from all demographic groups to reduce their movement rate during the hunting season. On the other hand, if bear avoid hunters by escaping, we expect them to increase their movement rate in order to leave high-risk areas faster. We found an increased movement rate in females accompanied by dependent offspring during the morning hours of the bear hunting season, a general decrease in movement rate in adult lone females, and no changes in males and subadult females. The increased movement rate that we observed in females with dependant offspring during the hunting season was likely an antipredator response because it only occurred in areas located closer to roads, whereas the decreased movement rate in lone females could be either part of a seasonal activity patterns or be associated with an increased selection for better concealment. Our study suggests that female brown bears accompanied by offspring likely move faster in high-risk areas to minimize risk exposure as well as the costly trade-offs (i.e., time spent foraging versus time spent hiding) typically associated with anti-predator tactics that involve changes in resource selection. Our study also highlights the importance of modeling fine-scale spatiotemporal variations in risk to adequately capture the complexity in behavioural responses caused by human activities in wildlife.</p>
Data from: Lianas associated with continued forest biomass losses following large-scale disturbances
<p>Lianas are important to rainforest ecosystems but often impede tree growth and increase tree mortality and stem damage after disturbances that favour their growth. Understanding how lianas affect biomass recovery and rates of carbon sequestration following disturbance is therefore of crucial importance. In this study, we determine how a tropical forest recovers biomass following a large-scale disturbance and test how this varies with liana dominance and stem damage<em>. </em>We use remote sensing methods to develop a model, validated by field data from 40 20 m x 20 m vegetation plots, to measure change in tree above-ground biomass eight years after Tropical Cyclone Yasi damaged logged forests in the Australian Wet Tropics. We related tree biomass changes to field measures of current liana dominance over trees, expressed as liana: tree basal area ratio, and assessed how these measures related to tree stem damage. Biomass declined in 34 of the 40 plots during the eight years post-disturbance, with loss rates and proportions of damaged tree stems increasing with the liana: tree ratio. From spatial upscaling, we found a net loss in biomass across the study landscape over the same period. Our results show that, following disturbances, lianas not only limit tree biomass recovery but are also associated with further biomass declines, most likely through their contribution to stem damage and delayed mortality. Furthermore, our finding of net biomass loss across the landscape since the cyclone shows that, post-disturbance, rainforests can act as a carbon source with consequences for the global carbon sink<em>. </em></p>
FIG. 1 in Response of bryophytes to disturbances in managed forests. A case study from a Polish forest
FIG. 1. — Number of bryophyte species in the four types of substrates considered.
Disturbance amplifies sensitivity of dryland productivity to precipitation variability
<p>Variability of the terrestrial global carbon sink is largely determined by the response of dryland productivity to annual precipitation. Despite extensive disturbance in drylands, how disturbance alters productivity-precipitation relationships remains poorly understood. Using remote-sensing to pair over 5600 km of natural gas pipeline corridors with neighboring undisturbed areas in North American drylands, we found that disturbance reduced average annual production 6-29% and caused up to a five-fold increase in the sensitivity of net primary productivity (NPP) to interannual variation in precipitation. Disturbance impacts were larger and longer-lasting at locations with higher precipitation (>450 mm mean annual precipitation). Disturbance effects on NPP dynamics were mostly explained by shifts from woody to herbaceous vegetation. Severe disturbance will amplify effects of increasing precipitation variability on NPP in drylands.</p>
Data and code for 'Disturbances can facilitate prior invasions more than subsequent invasions in microbial communities'
<p>Data and R code for 'Disturbances can facilitate prior invasions more than subsequent invasions in microbial communities'.</p><p>Information about the files can be found in the README.txt file.</p>
MineSegSAT: An automated system to evaluate mining disturbed area extents from Sentinel-2 imagery
<p>This dataset includes segmentation maps of environmentally impacted areas of mineral extraction sites in Canada and corresponding atmospherically corrected Sentinel-2 data from 2021. </p> <p>To look at an example of how to use the uncompressed assets, see this GitHub repository here: https://github.com/macdonaldezra/MineSegSAT. </p> <p>This dataset and code accompany the paper published at ECRS 2023 which can be found on the conference website at https://doi.org/10.3390/ECRS2023-16886 or at the Arxiv link http://arxiv.org/abs/2311.01676.</p>
Ant and termite assemblages along a tropical forest disturbance gradient in Sabah, Malaysia: A study of co-variation and trophic interactions
<b>Description: </b><p>Termite community composition from soil pits and deadwood</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/103"><b>Ant and termite assemblages along a tropical forest disturbance gradient in Sabah, Malaysia: A study of co-variation and trophic interactions</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=38">here</a></p><p><b>Data worksheets: </b>There are 3 data worksheets in this dataset:</p><ol><li><p><b>Functional traits</b> (Worksheet Function)</p><p>Dimensions: 36 rows by 3 columns</p><p>Description: Functional traits associated with each genus</p><p>Fields: </p><ul><li><b>Genus</b>: Genus ID (Field type: Taxa)</li><li><b>Functional.group</b>: Humification gradient (Field type: Categorical Trait)</li></ul><br></li><li><p><b>Soil pit data</b> (Worksheet SoilPits)</p><p>Dimensions: 954 rows by 35 columns</p><p>Description: Termite community composition from soil pits</p><p>Fields: </p><ul><li><b>2nd.order.point</b>: SAFE Project sample site (Field type: Location)</li><li><b>Quadrat.number.(in.my.study)</b>: Quadrat number (Field type: ID)</li><li><b>Date</b>: Date of sample collection (Field type: Date)</li><li><b>Pit.number</b>: Pit number within the plot (Field type: Replicate)</li><li><b>Time</b>: Time samples were collected (Field type: Time)</li><li><b>No..of.termites</b>: Number adult termites (Field type: Abundance)</li><li><b>No.juvenile.termites</b>: Number juvenile termites (Field type: Abundance)</li><li><b>Unknown</b>: Number of damaged individuals or individuals that can't definitively be assigned to genera (Field type: Abundance)</li><li><b>Dicuspiditermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Schedorhinotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Prohamitermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Malaysiotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Mirocapritermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Hypotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Procapritermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Homatermes.undescribed.genus</b>: Number of individuals (Field type: Abundance)</li><li><b>Termes</b>: Number of individuals (Field type: Abundance)</li><li><b>Syncapritermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Pericapritermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Microcerotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Macrotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Globitermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Lacessititermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Pseudocapritermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Homallotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Oriencapritermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Oriensublitermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Labritermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Euramitermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Rhinotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Nasutitermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Bulbitermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Odontotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Heterotermes</b>: Number of individuals (Field type: Abundance)</li></ul><br></li><li><p><b>Deadwood data</b> (Worksheet Deadwood)</p><p>Dimensions: 138 rows by 23 columns</p><p>Description: Termite community composition from deadwood</p><p>Fields: </p><ul><li><b>2nd.order.point</b>: SAFE Project sample site (Field type: Location)</li><li><b>Quadrat.number.(in.my.study)</b>: Quadrat number (Field type: ID)</li><li><b>Date</b>: Date of sample collection (Field type: Date)</li><li><b>Wood.sample</b>: Wood piece within Quadrat (Field type: Replicate)</li><li><b>Time</b>: Time samples were collected (Field type: Time)</li><li><b>No..of.termites</b>: Number adult termites (Field type: Abundance)</li><li><b>No.juvenile.termites</b>: Number juvenile termites (Field type: Abundance)</li><li><b>Unknown</b>: Number of damaged individuals or individuals that can't definitively be assigned to genera (Field type: Abundance)</li><li><b>Dicuspiditermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Schedorhinotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Homallotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Bulbitermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Macrotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Globitermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Nasutitermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Heterotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Syncapritermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Malaysiotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Parrhinotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Pericapritermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Rhinotermes</b>: Number of individuals (Field type: Abundance)</li><li><b>Aciculitermes</b>: Number of individuals (Field type: Abundance)</li></ul><br></li></ol><p><b>Date range: </b>2010-04-21 to 2010-05-25</p><p><b>Latitudinal extent: </b>4.6353 to 4.7520</p><p><b>Longitudinal extent: </b>116.9542 to 117.6288</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div>Animalia<br> - Arthropoda<br> -  - Insecta<br> -  -  - Isoptera<br> -  -  -  -  - <i>Aciculitermes</i><br> -  -  -  -  - [<i>Euramitermes</i>]<br> -  -  -  -  - <i>Homallotermes</i><br> -  -  -  -  - <i>Hypotermes</i><br> -  -  -  -  - <i>Mirocapritermes</i><br> -  -  -  -  - <i>Procapritermes</i><br> -  -  -  -  - <i>Prohamitermes</i><br> -  -  -  -  - <i>Pseudocapritermes</i><br> -  -  -  - Rhinotermitidae<br> -  -  -  -  - <i>Heterotermes</i><br> -  -  -  -  - <i>Parrhinotermes</i><br> -  -  -  -  - <i>Rhinotermes</i><br> -  -  -  -  - <i>Schedorhinotermes</i><br> -  -  -  - Termitidae<br> -  -  -  -  - <i>Bulbitermes</i><br> -  -  -  -  - <i>Dicuspiditermes</i><br> -  -  -  -  - <i>Globitermes</i><br> -  -  -  -  - <i>Labritermes</i><br> -  -  -  -  - [<i>Lacessititermes</i>]<br> -  -  -  -  - <i>Macrotermes</i><br> -  -  -  -  - <i>Malaysiotermes</i><br> -  -  -  -  - <i>Microcerotermes</i><br> -  -  -  -  - <i>Nasutitermes</i><br> -  -  -  -  - <i>Odontotermes</i><br> -  -  -  -  - <i>Oriencapritermes</i><br> -  -  -  -  - <i>Oriensubulitermes</i><br> -  -  -  -  - <i>Pericapritermes</i><br> -  -  -  -  - <i>Syncapritermes</i><br> -  -  -  -  - <i>Termes</i><br> -  -  -  -  - <i>Hodotermes</i><br> -  - [Homatermes.undescribed.genus]<br></div><p></p>
The role of competition in structuring ant community composition across a tropical forest disturbance gradient
<b>Description: </b><p>Leaf litter ant community composition and competition</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/34"><b>The role of competition in structuring ant community composition across a tropical forest disturbance gradient.</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=1">here</a></p><p><b>Data worksheets: </b>There are 3 data worksheets in this dataset:</p><ol><li><p><b>Ant community composition</b> (Worksheet Composition)</p><p>Dimensions: 430 rows by 69 columns</p><p>Description: Site x species matrix of ant community composition</p><p>Fields: </p><ul><li><b>Forest Type</b>: Shows the two forest types used in the study (Field type: Categorical)</li><li><b>Site</b>: Represents the site/day sampled. 10 Sampling sites were used in each forest type (Field type: Location)</li><li><b>Time</b>: Represents the time in the day points were sampled (Field type: Time)</li><li><b>Point</b>: Represents the column of 3 sampling points for each time of day (Field type: Replicate)</li><li><b>ID</b>: Represents individual sampling point. Order is: Site(Day)/Time/Type/Sampling point no. Logged ID's also have LF at the start (Field type: ID)</li><li><b>Method</b>: Method used to record community (Field type: Categorical)</li><li><b>Diacamma</b>: Number of individuals (Field type: Abundance)</li><li><b>Odontoponera</b>: Number of individuals (Field type: Abundance)</li><li><b>Pheidole</b>: Number of individuals (Field type: Abundance)</li><li><b>Leptogenys</b>: Number of individuals (Field type: Abundance)</li><li><b>Pheidologeton</b>: Number of individuals (Field type: Abundance)</li><li><b>Crematogaster</b>: Number of individuals (Field type: Abundance)</li><li><b>Odontomachus</b>: Number of individuals (Field type: Abundance)</li><li><b>Aphaenogaster</b>: Number of individuals (Field type: Abundance)</li><li><b>Acanthomyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Nylanderia</b>: Number of individuals (Field type: Abundance)</li><li><b>Camponotus</b>: Number of individuals (Field type: Abundance)</li><li><b>Cardiocondyla</b>: Number of individuals (Field type: Abundance)</li><li><b>Anochetus</b>: Number of individuals (Field type: Abundance)</li><li><b>Technomyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Monomorium</b>: Number of individuals (Field type: Abundance)</li><li><b>Recurvidris</b>: Number of individuals (Field type: Abundance)</li><li><b>Polyrhachis</b>: Number of individuals (Field type: Abundance)</li><li><b>Cladomyrma</b>: Number of individuals (Field type: Abundance)</li><li><b>Lophomyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Harpegnathos</b>: Number of individuals (Field type: Abundance)</li><li><b>Carebara</b>: Number of individuals (Field type: Abundance)</li><li><b>Cataulacus</b>: Number of individuals (Field type: Abundance)</li><li><b>Pachycondyla</b>: Number of individuals (Field type: Abundance)</li><li><b>Lordomyrma</b>: Number of individuals (Field type: Abundance)</li><li><b>Myrmecina</b>: Number of individuals (Field type: Abundance)</li><li><b>Proatta</b>: Number of individuals (Field type: Abundance)</li><li><b>Euprenolepis</b>: Number of individuals (Field type: Abundance)</li><li><b>Rhytidoponera</b>: Number of individuals (Field type: Abundance)</li><li><b>Paratrechina</b>: Number of individuals (Field type: Abundance)</li><li><b>Paraparatrechina</b>: Number of individuals (Field type: Abundance)</li><li><b>Tetramorium</b>: Number of individuals (Field type: Abundance)</li><li><b>Paratopula</b>: Number of individuals (Field type: Abundance)</li><li><b>Strumigenys</b>: Number of individuals (Field type: Abundance)</li><li><b>Pyramica</b>: Number of individuals (Field type: Abundance)</li><li><b>Ponera</b>: Number of individuals (Field type: Abundance)</li><li><b>Hypoponera</b>: Number of individuals (Field type: Abundance)</li><li><b>Tetraponera</b>: Number of individuals (Field type: Abundance)</li><li><b>Emeryopone</b>: Number of individuals (Field type: Abundance)</li><li><b>Centromyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Tapinoma</b>: Number of individuals (Field type: Abundance)</li><li><b>Myrmicaria</b>: Number of individuals (Field type: Abundance)</li><li><b>Rotrastruma</b>: Number of individuals (Field type: Abundance)</li><li><b>Prionopelta</b>: Number of individuals (Field type: Abundance)</li><li><b>Gnamptogenys</b>: Number of individuals (Field type: Abundance)</li><li><b>Eurhopalothrix</b>: Number of individuals (Field type: Abundance)</li><li><b>Myrmoteras</b>: Number of individuals (Field type: Abundance)</li><li><b>Oecophylla</b>: Number of individuals (Field type: Abundance)</li><li><b>Myopias</b>: Number of individuals (Field type: Abundance)</li><li><b>Pseudolasius</b>: Number of individuals (Field type: Abundance)</li><li><b>Plagiolepis</b>: Number of individuals (Field type: Abundance)</li><li><b>Dacetinops</b>: Number of individuals (Field type: Abundance)</li><li><b>Mystrium</b>: Number of individuals (Field type: Abundance)</li><li><b>Echinopla</b>: Number of individuals (Field type: Abundance)</li><li><b>Philidris</b>: Number of individuals (Field type: Abundance)</li><li><b>Vollenhovia</b>: Number of individuals (Field type: Abundance)</li><li><b>Rhoptromyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Anillomyrma</b>: Number of individuals (Field type: Abundance)</li><li><b>Cryptopone</b>: Number of individuals (Field type: Abundance)</li><li><b>Aenictus</b>: Number of individuals (Field type: Abundance)</li><li><b>Calyptomyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Amblyopone</b>: Number of individuals (Field type: Abundance)</li><li><b>Prenolepis</b>: Number of individuals (Field type: Abundance)</li></ul><br></li><li><p><b>Morphometrics</b> (Worksheet Morpho)</p><p>Dimensions: 72 rows by 4 columns</p><p>Description: Size classes for the genera</p><p>Fields: </p><ul><li><b>Genera</b>: Genus ID (Field type: Taxa)</li><li><b>Size.Min</b>: Minimum body size (Field type: Categorical Trait)</li><li><b>Size.Max</b>: Maximum body size (Field type: Categorical Trait)</li></ul><br></li><li><p><b>Competition</b> (Worksheet Competition)</p><p>Dimensions: 866 rows by 15 columns</p><p>Description: Outcome of competitive interactions among individuals of different genera</p><p>Fields: </p><ul><li><b>Forest Type</b>: Shows the two forest types used in the study (Field type: Categorical)</li><li><b>Site</b>: Represents the site/day sampled. 10 Sampling sites were used in each forest type (Field type: Location)</li><li><b>Time</b>: Represents the time in the day points were sampled (Field type: Time)</li><li><b>ID</b>: Represents individual sampling point. Order is: Site(Day)/Time/Type/Sampling point no. Logged ID's also have LF at the start (Field type: ID)</li><li><b>Method</b>: Method used to record interaction (Field type: Categorical)</li><li><b>Genera1</b>: Genus ID of the first interacting individual (Field type: Taxa)</li><li><b>Genera2</b>: Genus ID of the second interacting individual (Field type: Taxa)</li><li><b>TimeG1</b>: The arrival time of the first genus in the interaction to the bait card in seconds (Field type: Numeric)</li><li><b>TimeG2</b>: The arrival time of the second genus in the interaction to the bait card in seconds (Field type: Numeric)</li><li><b>IntG1</b>: The competitive status of the first genus in the interaction (Field type: Categorical Interaction)</li><li><b>IntG2</b>: The competitive status of the second genus in the interaction (Field type: Categorical Interaction)</li><li><b>Interaction</b>: The type of interaction occuring between the two genera (Field type: Categorical Interaction)</li><li><b>GroupG1</b>: Whether or not the first genus was part of a group of individuals when interacting on the bait card (Field type: Categorical)</li><li><b>GroupG2</b>: Whether or not the second genus was part of a group of individuals when interacting on the bait card (Field type: Categorical)</li></ul><br></li></ol><p><b>Date range: </b>2016-02-02 to 2016-06-05</p><p><b>Latitudinal extent: </b>4.7273 to 4.7463</p><p><b>Longitudinal extent: </b>116.9669 to 117.5969</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div>Animalia<br> - Arthropoda<br> -  - Insecta<br> -  -  - Hymenoptera<br> -  -  -  - Formicidae<br> -  -  -  -  - <i>Acanthomyrmex</i><br> -  -  -  -  - <i>Aenictus</i><br> -  -  -  -  - <i>Amblyopone</i><br> -  -  -  -  - <i>Anillomyrma</i><br> -  -  -  -  - <i>Anochetus</i><br> -  -  -  -  - <i>Aphaenogaster</i><br> -  -  -  -  - <i>Calyptomyrmex</i><br> -  -  -  -  - <i>Camponotus</i><br> -  -  -  -  - <i>Cardiocondyla</i><br> -  -  -  -  - <i>Carebara</i><br> -  -  -  -  - <i>Cataulacus</i><br> -  -  -  -  - <i>Centromyrmex</i><br> -  -  -  -  - <i>Cladomyrma</i><br> -  -  -  -  - <i>Crematogaster</i><br> -  -  -  -  - <i>Cryptopone</i><br> -  -  -  -  - <i>Dacetinops</i><br> -  -  -  -  - <i>Diacamma</i><br> -  -  -  -  - <i>Echinopla</i><br> -  -  -  -  - <i>Emeryopone</i><br> -  -  -  -  - <i>Euprenolepis</i><br> -  -  -  -  - <i>Eurhopalothrix</i><br> -  -  -  -  - <i>Gnamptogenys</i><br> -  -  -  -  - <i>Harpegnathos</i><br> -  -  -  -  - <i>Hypoponera</i><br> -  -  -  -  - <i>Leptogenys</i><br> -  -  -  -  - <i>Lophomyrmex</i><br> -  -  -  -  - <i>Lordomyrma</i><br> -  -  -  -  - <i>Monomorium</i><br> -  -  -  -  - <i>Myopias</i><br> -  -  -  -  - <i>Myrmecina</i><br> -  -  -  -  - <i>Myrmicaria</i><br> -  -  -  -  - <i>Myrmoteras</i><br> -  -  -  -  - <i>Mystrium</i><br> -  -  -  -  - <i>Nylanderia</i><br> -  -  -  -  - <i>Odontomachus</i><br> -  -  -  -  - <i>Odontoponera</i><br> -  -  -  -  - <i>Oecophylla</i><br> -  -  -  -  - <i>Pachycondyla</i><br> -  -  -  -  - <i>Paraparatrechina</i><br> -  -  -  -  - <i>Paratopula</i><br> -  -  -  -  - <i>Paratrechina</i><br> -  -  -  -  - <i>Pheidole</i><br> -  -  -  -  - <i>Pheidologeton</i><br> -  -  -  -  - <i>Philidris</i><br> -  -  -  -  - <i>Plagiolepis</i><br> -  -  -  -  - <i>Polyrhachis</i><br> -  -  -  -  - <i>Ponera</i><br> -  -  -  -  - <i>Prenolepis</i><br> -  -  -  -  - <i>Prionopelta</i><br> -  -  -  -  - <i>Proatta</i><br> -  -  -  -  - <i>Pseudolasius</i><br> -  -  -  -  - <i>Pyramica</i><br> -  -  -  -  - <i>Recurvidris</i><br> -  -  -  -  - <i>Rhoptromyrmex</i><br> -  -  -  -  - <i>Rhytidoponera</i><br> -  -  -  -  - [<i>Rotrastruma</i>]<br> -  -  -  -  - <i>Strumigenys</i><br> -  -  -  -  - <i>Tapinoma</i><br> -  -  -  -  - <i>Technomyrmex</i><br> -  -  -  -  - <i>Tetramorium</i><br> -  -  -  -  - <i>Tetraponera</i><br> -  -  -  -  - <i>Vollenhovia</i><br></div><p></p>
Microclimate change, forest disturbance and twig-dwelling ants
<b>Description: </b><p>Data and twig colonisation experiments on twig-nesting ant communities</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/33"><b>Microclimate change, forest disturbance and twig-dwelling ants</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=74">here</a></p><p><b>Data worksheets: </b>There are 6 data worksheets in this dataset:</p><ol><li><p><b>Plot locality information</b> (Worksheet Plot.Locations)</p><p>Dimensions: 28 rows by 5 columns</p><p>Description: Identifies the nearest SAFE Project sampling site to survey plots</p><p>Fields: </p><ul><li><b>Forest.area </b>: SAFE Project Block in which sampling took place (Field type: ID)</li><li><b>Plot</b>: Plot within Forest.area (Field type: ID)</li><li><b>Location</b>: SAFE Project sample site (Field type: Location)</li><li><b>SAFE.Code</b>: SAFE Project sample site (Field type: ID)</li></ul><br></li><li><p><b>Twig-nesting ant communities</b> (Worksheet Observed.Colonies)</p><p>Dimensions: 154 rows by 10 columns</p><p>Description: Plot surveys of naturally occurring twig-nesting ant communities</p><p>Fields: </p><ul><li><b>Location</b>: SAFE project sampling point (Field type: Location)</li><li><b>Forest.area</b>: SAFE Project Block in which sampling took place (Field type: ID)</li><li><b>Plot</b>: Plot within Forest.area (Field type: ID)</li><li><b>SAFE.Code</b>: SAFE project sampling point (Field type: ID)</li><li><b>Subplot</b>: Sub-plot within Plot (Field type: ID)</li><li><b>Genus</b>: Genus identity (Field type: Taxa)</li><li><b>Date</b>: Day on which the survey took place (Field type: Date)</li><li><b>No.Searched</b>: The number of twigs examined for ant colonies in the 1m sub-plot quadrat. Fifteen person-minutes of searching time was put in at each sub-plot to search for colonies of twig-dwelling ants. To locate potential colonies, all twigs of up to 4 cm in diameter found within the search time were broken open to detect any ants living in twig cavities. (Field type: Numeric)</li><li><b>No.Colonies.Found</b>: The number of colonies found in the 1m sub-plot quadrat, during the searching time. A colony was defined as by Sagata et al. (2010) as a group of ants with at least one queen, or at least two workers with brood. (Field type: Numeric)</li></ul><br></li><li><p><b>Experimental colonisation of twigs</b> (Worksheet Twig.Opening)</p><p>Dimensions: 905 rows by 14 columns</p><p>Description: Observations of twig-ant colonisation of experimental twigs</p><p>Fields: </p><ul><li><b>Location</b>: SAFE project sampling point (Field type: Location)</li><li><b>Forest.area</b>: SAFE Project Block in which sampling took place (Field type: ID)</li><li><b>Plot</b>: Plot within Forest.area (Field type: ID)</li><li><b>SAFE.Code</b>: SAFE project sampling point (Field type: ID)</li><li><b>Subplot</b>: Sub-plot within Plot (Field type: ID)</li><li><b>Twig</b>: The identification number of an individual artificial twig (Field type: ID)</li><li><b>Date.out</b>: The date the individual artificial twig was placed in the subplo (Field type: Date)</li><li><b>Date.check</b>: The date on which the artificial twig was watched to deterimine whether it was occupied (Field type: Date)</li><li><b>Prediction</b>: Was the twig predicted to be occupied by ants based on visual observation? (Field type: Categorical)</li><li><b>Open.results</b>: Is an ant colonYpresent in the twig? (Field type: Categorical)</li><li><b>Genus</b>: Genus identity (Field type: Taxa)</li><li><b>Termites</b>: Did the twig have termites inside when cut open? (Field type: Categorical)</li><li><b>Comments</b>: Comments on problems, or weather if it may have affected the prediction. (Field type: Comments)</li></ul><br></li><li><p><b>Environmental data</b> (Worksheet Environ.Data)</p><p>Dimensions: 943 rows by 18 columns</p><p>Description: Microclimate conditions at each of the survey plots</p><p>Fields: </p><ul><li><b>Location</b>: SAFE project sampling point (Field type: Location)</li><li><b>Forest.area</b>: SAFE Project Block in which sampling took place (Field type: ID)</li><li><b>Plot</b>: Plot within Forest.area (Field type: ID)</li><li><b>SAFE.Code</b>: SAFE project sampling point (Field type: ID)</li><li><b>Subplot</b>: Sub-plot within Plot (Field type: ID)</li><li><b>Date</b>: Date the data was collected (Field type: Date)</li><li><b>Time</b>: Time the data was collected (Field type: Time)</li><li><b>Tair </b>: Air temperatures (Field type: Numeric)</li><li><b>Tsoil</b>: Soil temperature (Field type: Numeric)</li><li><b>Hum</b>: Humidity (Field type: Numeric)</li><li><b>Lux</b>: Light level (Field type: Numeric)</li><li><b>Tsurf1</b>: Surface temperature (one of four measurements in the plot) (Field type: Numeric)</li><li><b>Tsurf2</b>: Surface temperature (one of four measurements in the plot) (Field type: Numeric)</li><li><b>Tsurf3</b>: Surface temperature (one of four measurements in the plot) (Field type: Numeric)</li><li><b>Tsurf4</b>: Surface temperature (one of four measurements in the plot) (Field type: Numeric)</li><li><b>Sun</b>: An estimate of the amount of direct sunlight on the ground of the subplot. (Field type: Numeric)</li><li><b>Comments</b>: Observations about weather conditions impacting environmental measurements (Field type: Comments)</li></ul><br></li><li><p><b>Colonisation observations</b> (Worksheet Colonisation)</p><p>Dimensions: 14489 rows by 11 columns</p><p>Description: Visual observation of colonisation status of experimental twigs</p><p>Fields: </p><ul><li><b>Location</b>: SAFE project sampling point (Field type: Location)</li><li><b>Forest.area</b>: SAFE Project Block in which sampling took place (Field type: ID)</li><li><b>Plot</b>: Plot within Forest.area (Field type: ID)</li><li><b>SAFE.Code</b>: SAFE project sampling point (Field type: ID)</li><li><b>Subplot</b>: Sub-plot within Plot (Field type: ID)</li><li><b>Twig</b>: The identification number of an individual artificial twig (Field type: ID)</li><li><b>Date.out</b>: The date the individual artificial twig was placed in the subplo (Field type: Date)</li><li><b>Date.check</b>: The date on which the artificial twig was watched to deterimine whether it was occupied (Field type: Date)</li><li><b>Status</b>: Was the twig predicted to be occupied by ants based oNvisual observation? (Field type: Categorical)</li><li><b>Comments</b>: Additional comments on the state of the twig, if termites were seen, or if there were weather conditions which may have interfered with the survey. (Field type: Comments)</li></ul><br></li><li><p><b>Ant thermotolerance</b> (Worksheet Boiling.Data)</p><p>Dimensions: 605 rows by 4 columns</p><p>Description: Experimental tests of ant thermotolerance</p><p>Fields: </p><ul><li><b>Genus</b>: Genus identity (Field type: Taxa)</li><li><b>T.Max</b>: The temperature at which the ant lost motor control and either crunched up and became still/died, or fell over and began jerking uncontrollably, without recovery. (Field type: Numeric)</li><li><b>Comments</b>: A description of features of the ant if not a worker, of anything that went wrong during the experiement, and of whether the ant was found alive following exposure to T.Max. (Field type: Comments)</li></ul><br></li></ol><p><b>Date range: </b>2015-04-07 to 2016-06-15</p><p><b>Latitudinal extent: </b>4.6373 to 4.7116</p><p><b>Longitudinal extent: </b>117.4523 to 117.6242</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div>Animalia<br> - Arthropoda<br> -  - Insecta<br> -  -  - Hymenoptera<br> -  -  -  - Formicidae<br> -  -  -  -  - <i>Acanthomyrmex</i><br> -  -  -  -  - <i>Bothriomyrmex</i><br> -  -  -  -  - <i>Camponotus</i><br> -  -  -  -  - <i>Cardiocondyla</i><br> -  -  -  -  - <i>Carebara</i><br> -  -  -  -  - <i>Cataulacus</i><br> -  -  -  -  - <i>Centromyrmex</i><br> -  -  -  -  - <i>Cerapachys</i><br> -  -  -  -  - <i>Crematogaster</i><br> -  -  -  -  - <i>Echinopla</i><br> -  -  -  -  - <i>Forelophilus</i><br> -  -  -  -  - <i>Hypoponera</i><br> -  -  -  -  - <i>Lepisiota</i><br> -  -  -  -  - <i>Meranoplus</i><br> -  -  -  -  - <i>Nylanderia</i><br> -  -  -  -  - <i>Pachycondyla</i><br> -  -  -  -  - <i>Paraparatrechina</i><br> -  -  -  -  - <i>Pheidole</i><br> -  -  -  -  - <i>Pheidologeton</i><br> -  -  -  -  - <i>Plagiolepis</i><br> -  -  -  -  - <i>Polyrhachis</i><br> -  -  -  -  - <i>Prenolepis</i><br> -  -  -  -  - <i>Pseudolasius</i><br> -  -  -  -  - <i>Rhoptromyrmex</i><br> -  -  -  -  - <i>Strumigenys</i><br> -  -  -  -  - <i>Tetramorium</i><br> -  -  -  -  - <i>Tetraponera</i><br> -  -  -  -  - [VT4]<br> -  -  -  -  - <i>Vollenhovia</i><br></div><p></p>
Observations of low-latitude traveling ionospheric disturbances by a 630-nm airglow imager and the CHAMP satellite over Indonesia
<p>We report the first comparison of ground and satellite measurements of low-latitude traveling ionospheric disturbances (TIDs). Three TID events were simultaneously observed by a 630-nm airglow imager and the CHAMP satellite on April 30, 2006 (event 1), September 28, 2006 (event 2), and April 12, 2004 (event 3) at Kototabang, Indonesia (geographic coordinates: 0.2$^\circ$S, 100.3$^\circ$E, geomagnetic latitude: 10.6$^\circ$S). In 630-nm airglow images of all three events, there are clear southward-moving structures. Events 1 and 2 are a single pulse with horizontal scales of $\sim$500--1000 km. Event 3 shows five wave fronts with a horizontal scale size of 500--1000 km. All three TIDs are medium-scale TIDs. Horizontal wavelengths of both airglow intensity at an average emission altitude of 250 km and CHAMP neutral density variations measured at 400 km are estimated by fitting a sinusoidal function to the observed data. For events 1 and 3, estimated horizontal wavelengths are nearly equal, indicating both instruments are observing the same wave. For event 1, the CHAMP electron density mapped along the geomagnetic field line onto the airglow altitude does not show wave structure similar<br> to the airglow variation. For events 2 and 3, the relationship of electron density and airglow intensity is unclear. These results suggest that the cause of the observed TID is not caused by ionospheric plasma instability but by gravity waves in the thermosphere. According to these results, we conclude that the observed TIDs in all three cases are caused by gravity waves in the thermosphere.</p>
Repository for Jupiter Equatorial Zone Disturbance Data
<p>Antuñano et al. (2018) used Jupiter infrared data captured by 8 different ground-based instruments mounted on the Infrared Telescope Facility (IRTF) on Maunakea and Very Large Telescope (VLT) in Paranal between 1984 and 2017, to investigate a pattern of cloud clearance events at Jupiter's equatorial zone at 5 µm.This repository contains (i) cylindrical maps of Jupiter's 5-µm images from 1999-2000 and 2006-2007 captured by NSFCam and NSFCam2 instruments, respectively, mounted on the IRTF, showing Jupiter's Equatorial Zone disturbance, and (ii) a data file showing the brightness scans from ±7° latitude as a function of time used to build Figure 2.</p> <p>DATA</p> <p>As descibed in Antuñano et al. (2018), the normalised average brightness from 1984-2017 was used to charcterise three different cloud clearance events of Jupiter's equatorial zone at 5 µm. The normalised average brightness of the equatorial zone between ±7° latitude is given in "Brightness_scans_1984-2017.dat", where the first column represents the Julian date, the second column represents the latitude in planetocentric degrees, the third column represents the normalised average brightness and the fourth column gives the standard deviation of the normalised average brightness.</p>
Species richness, composition and microhabitat characteristics of non-volant terrestrial mammals in disturbed habitats
<b>Description: </b><p>A study on the small mammals communities was carried out in disturbed habitats aroundsabah, namely university malaysia sabah (ums), klias peat swamp forest reserve(klias), kawang forest reserve (kawang), kalabakan forest reserve (safe) and maliaubasin conservation area (maliau). the objectives were (1) to determine the speciesrichness and composition of non-volant small mammal communities in disturbedhabitats; (2) to characterize the microhabitat-use patterns of the non-volant smallmammal communities in disturbed habitats; and (3) to determine the microhabitatpreferences of the non-volant small mammal communities in disturbed habitats. the aimof this study was to investigate how the habitat disturbance affects the species richness,community compositions and microhabitat-use pattern of the small mammals. this studywas conducted from october 2014 to march 2015 with a total sampling effort of 540trap-nights. overall, 71 individuals representing 14 species were successfully caughtduring this study. the species richness peaked at safe, and then declined at the rest ofthe study sites. habitat variables analysis showed that all study sites were divided intothree distinctive groups in terms of habitat types. canonical discriminant functionanalysis were used to analyze the microhabitat preferences and use-pattern of smallmammals and results showed the preferences of small mammals towards shrub cover(rattus rattus and callosciurus notatus), litter cover (callosciurus prevostii and echinorexgymnurus) and herbs limber (tupaia gracilis). The locations of the traps have not been given longitute and latitute as there were set on animal trails approximately 20metres from one another. </p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/150"><b>Species richness, composition and microhabitat characteristics of non-volant terrestrial mammals in disturbed habitats</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Universiti Malaysia Sabah (Grant)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiverstiy Council (Research licence NA)</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3265704">here</a></p><p><b>Files: </b>This consists of 1 file: Veg_Volent_mammals.xlsx</p><p><b>Veg_Volent_mammals.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Vegetation cover</b> (described in worksheet Vegetation_cover)</p><p>Description: The estimated canopy cover and percentage of ground cover of traps across disturbed habitats</p><p>Number of fields: 19</p><p>Number of data rows: 180</p><p>Fields: </p><ul><li><b>Date</b>: Date the vegetation cover was collected (Field type: Date)</li><li><b>Location</b>: Where data was collected (Field type: Location)</li><li><b>Habitat_type</b>: Habitat type (Field type: Categorical)</li><li><b>Trap_station</b>: Transect and trap number (Field type: ID)</li><li><b>Canopy_cover</b>: Percentage of canopy cover (Field type: Numeric)</li><li><b>Canopy_height</b>: Canopy height (Field type: Numeric)</li><li><b>Herbs_Climber</b>: Any climbers seen on trees for example vines and lianas (Field type: Numeric)</li><li><b>Tree_GBH_>10CM</b>: Tree girth at breast height of 10 cm (Field type: Numeric)</li><li><b>Tree_GBH_>30CM</b>: Tree girth at breast height of 30 cm (Field type: Numeric)</li><li><b>Tree_GBH_>60CM</b>: Tree girth at breast height of 60 cm (Field type: Numeric)</li><li><b>Tree_GBH_>90CM</b>: Tree girth at breast height of 90 cm (Field type: Numeric)</li><li><b>Fallen_trees_bran</b>: Percentage cover (Field type: Numeric)</li><li><b>Bareground</b>: Percentage cover (Field type: Numeric)</li><li><b>Shrub</b>: Percentage cover (Field type: Numeric)</li><li><b>grass</b>: Percentage cover (Field type: Numeric)</li><li><b>Rock</b>: Percentage cover (Field type: Numeric)</li><li><b>Litter</b>: Percentage cover (Field type: Numeric)</li><li><b>Water</b>: Percentage cover (Field type: Numeric)</li><li><b>Twig</b>: Percentage cover (Field type: Numeric)</li></ul></li><li><p><b>Non volent mammal abundance</b> (described in worksheet Non_volent_mammals)</p><p>Description: The abundance of non-volant terrestrails mammals caught across disturbed habitats. Growth and sex measurements takens</p><p>Number of fields: 17</p><p>Number of data rows: 490</p><p>Fields: </p><ul><li><b>Date</b>: Date the vegetation cover was collected (Field type: Date)</li><li><b>Location</b>: Where data was collected (Field type: Location)</li><li><b>Transect</b>: Transect number (Field type: ID)</li><li><b>Habitat</b>: Habitat type (Field type: Categorical)</li><li><b>Trap_station</b>: Transect and trap number (Field type: ID)</li><li><b>Species</b>: Species of non volent mammals caught in trap (Field type: Taxa)</li><li><b>Weight</b>: Weight of caught non volent mammal (Field type: Numeric)</li><li><b>Ear</b>: Ear measurment of caught non volent mammal (Field type: Numeric)</li><li><b>Hind_leg</b>: Hind leg measurement of caught non-volent mammal (Field type: Numeric)</li><li><b>Head_body</b>: Head to body measurement of caught non volent mammal (Field type: Numeric)</li><li><b>Tail</b>: Tail length of caught non volent mammal (Field type: Numeric)</li><li><b>Sex</b>: Sex of caught non volent mammal (Field type: Categorical)</li><li><b>Sexual_activity</b>: Sexual maturity of caught non volent mammal (Field type: Categorical)</li><li><b>Age</b>: Age class of caught non volent mammal (Field type: Categorical)</li><li><b>Trap_condition</b>: Trap condition (Field type: Categorical)</li><li><b>Trap_open_closed</b>: Trap open or closed (Field type: Categorical)</li><li><b>Bait</b>: Bait taken or intact (Field type: Categorical)</li></ul></li></ol><p><b>Date range: </b>2014-10-22 to 2015-03-30</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div>Animalia<br> - Chordata<br> -  - Mammalia<br> -  -  - Erinaceomorpha<br> -  -  -  - Erinaceidae<br> -  -  -  -  - <i>Echinosorex</i><br> -  -  -  -  -  - <i>Echinosorex gymnura</i><br> -  -  - Rodentia<br> -  -  -  - Muridae<br> -  -  -  -  - <i>Lenothrix</i><br> -  -  -  -  -  - <i>Lenothrix canus</i><br> -  -  -  -  - <i>Leopoldamys</i><br> -  -  -  -  -  - <i>Leopoldamys sabanus</i><br> -  -  -  -  - <i>Maxomys</i><br> -  -  -  -  -  - <i>Maxomys rajah</i><br> -  -  -  -  -  - <i>Maxomys surifer</i><br> -  -  -  -  - <i>Niviventer</i><br> -  -  -  -  -  - <i>Niviventer cremoriventer</i><br> -  -  -  -  - <i>Rattus</i><br> -  -  -  -  -  - <i>Rattus rattus</i><br> -  -  -  - Sciuridae<br> -  -  -  -  - <i>Callosciurus</i><br> -  -  -  -  -  - <i>Callosciurus adamsi</i><br> -  -  -  -  -  - <i>Callosciurus notatus</i><br> -  -  -  -  -  - <i>Callosciurus prevostii</i><br> -  -  -  -  - <i>Sundasciurus</i><br> -  -  -  -  -  - <i>Sundasciurus lowii</i><br> -  -  - Scandentia<br> -  -  -  - Tupaiidae<br> -  -  -  -  - <i>Tupaia</i><br> -  -  -  -  -  - <i>Tupaia dorsalis</i><br> -  -  -  -  -  - <i>Tupaia glis</i><br> -  -  -  -  -  - <i>Tupaia gracilis</i><br></div><p></p>
Impacts of habitat disturbance on population health of Bornean frogs
<b>Description: </b><p>The raw data required for estimates of size, body condition and fluctuating asymmetry of riparian anurans across a series of streams within the SAFE landscape, providing insight into the population health of frog populations at these sites. Streams were selected to provide a habitat disturbance gradient enabling identification of any effect of habitat disturbance on the population health indices. Stream characteristics were measured to provide estimates of habitat disturbance sorrounding the streams (canopy cover) and enable the impact of any potentially confounding variables (stream width and slope) to be eliminated. </p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/205"><b>The impact of habitat modification on feeding interactions between riparian anuran communities and their arthropod prey </b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3485086">here</a></p><p><b>Files: </b>This consists of 1 file: Fluctuating_Asymmetry_and_Body_Condition_of_Anurans_in_the_SAFE_Project.xlsx</p><p><b>Fluctuating_Asymmetry_and_Body_Condition_of_Anurans_in_the_SAFE_Project.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Fluctuating asymmetry and body condition measurements of Bornean riparian anurans</b> (described in worksheet Frogs)</p><p>Description: Species, snout-vent length, mass and limb measurements of anurans sampled across a tropical forest disturbance gradient and within oil palm plantations. </p><p>Number of fields: 37</p><p>Number of data rows: 240</p><p>Fields: </p><ul><li><b>site</b>: SAFE identification code for the location where sampling was conducted (Field type: location)</li><li><b>date</b>: Date of sampling (Field type: date)</li><li><b>identification_code</b>: Code for the distinction of individual sampled frogs (Site of capture followed by the number of the individual within the overall sample taken within the site) (Field type: id)</li><li><b>species</b>: Identification of sampled frog to species level (Field type: taxa)</li><li><b>sex</b>: Sex of the sampled frog (male, female or unknown) (Field type: categorical trait)</li><li><b>svl</b>: Length of the frog from its snout to its vent (Field type: numeric trait)</li><li><b>mass</b>: Mass of the frog (Field type: numeric trait)</li><li><b>left_ru_1</b>: First measurement of the left radio-ulna of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>left_ru_2</b>: Second measurement of the left radio-ulna of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>left_ru_3</b>: Third measurement of the left radio-ulna of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>left_ru_mean</b>: Average of the three measurements of the left radio-ulna of the frog (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li><li><b>right_ru_1</b>: First measurement of the right radio-ulna of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>right_ru_2</b>: Second measurement of the right radio-ulna of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>right_ru_3</b>: Third measurement of the right radio-ulna of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>right_ru_mean</b>: Mean of the three measurements of the right radio-ulna of the frog (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li><li><b>mean_ru_size</b>: Average length of both radio-ulnas (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li><li><b>ru_diff</b>: Difference between the mean length of the right radio-ulna from all three measurements and that of the left (Field type: numeric trait)</li><li><b>left_thigh_1</b>: First measurement of the left thigh of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>left_thigh_2</b>: Second measurement of the left thigh of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>left_thigh_3</b>: Third measurement of the left thigh of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>left_thigh_mean</b>: Average of the three measurements of the left thigh of the frog (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li><li><b>right_thigh_1</b>: First measurement of the right thigh of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>right_thigh_2</b>: Second measurement of the right thigh of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>right_thigh_3</b>: Third measurement of the right thigh of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>right_thigh_mean</b>: Mean of the three measurements of the right thigh of the frog (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li><li><b>mean_thigh_size</b>: Average length of both thighs (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li><li><b>thigh_diff</b>: Difference between the mean length of the right thigh from all three measurements and that of the left (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li><li><b>left_tf_1</b>: First measurement of the left tibio-fibula of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>left_tf_2</b>: Second measurement of the left tibio-fibula of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>left_tf_3</b>: Third measurement of the left tibio-fibula of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>left_tf_mean</b>: Mean of the three measurements of the left tibio-fibula of the frog (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li><li><b>right_tf_1</b>: First measurement of the right tibio-fibula of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>right_tf_2</b>: Second measurement of the right tibio-fibula of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>right_tf_</b>: Third measurement of the right tibio-fibula of the frog (NA indicates that frog escaped before measurement could be completed) (Field type: numeric trait)</li><li><b>right_tf_mean</b>: Mean of the three measurements of the right tibio-fibula of the frog (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li><li><b>mean_tf_length</b>: Average length of both tibio-fibulas (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li><li><b>tf_diff</b>: Difference between the mean length of the right tibio-fibula from all three measurements and that of the left (NA indicates that frog escaped before all measurements could be completed) (Field type: numeric trait)</li></ul></li><li><p><b>Stream morphometrics and riparian canopy cover</b> (described in worksheet Streams)</p><p>Description: The width and slope of, as well as the canopy cover above, the streams along which anurans were sampled.</p><p>Number of fields: 10</p><p>Number of data rows: 260</p><p>Fields: </p><ul><li><b>site</b>: SAFE identification code for the location where sampling was conducted (Field type: location)</li><li><b>date</b>: Date of sampling (Field type: date)</li><li><b>point</b>: 20m interval point along 500m in-stream transect at which measurements were taken (Field type: id)</li><li><b>upstream_%_canopy_cover</b>: Percentage canopy coverage when facing upstream from the centre of the stream at the given sampling point (Field type: numeric)</li><li><b>right_%_canopy</b>: Percentage canopy coverage when facing toward the right bank from the centre of the stream at the given sampling point (Field type: numeric)</li><li><b>downstream_%_canopy_cover</b>: Percentage canopy coverage when facing downstream from the centre of the stream at the given sampling point (Field type: numeric)</li><li><b>left_%_canopy_cover</b>: Percentage canopy coverage when facing toward the left bank from the centre of the stream at the given sampling point (Field type: numeric)</li><li><b>average_cover</b>: Average of the four canopy cover measurements (Field type: numeric)</li><li><b>stream_width</b>: Wetted width of the stream (Field type: numeric)</li><li><b>stream_slope</b>: Slope of the stream (Field type: numeric)</li></ul></li></ol><p><b>Date range: </b>2019-03-23 to 2019-05-16</p><p><b>Latitudinal extent: </b>4.6025 to 4.7317</p><p><b>Longitudinal extent: </b>117.4556 to 117.6414</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Amphibia <br> -  -  -  -  Anura <br> -  -  -  -  -  Bufonidae <br> -  -  -  -  -  -  <i>Phrynoidis</i> <br> -  -  -  -  -  -  -  <i>Phrynoidis juxtaspera</i> <br> -  -  -  -  -  Dicroglossidae <br> -  -  -  -  -  -  <i>Limnonectes</i> <br> -  -  -  -  -  -  -  <i>Limnonectes finchi</i> <br> -  -  -  -  -  -  -  <i>Limnonectes kuhlii</i> <br> -  -  -  -  -  -  -  <i>Limnonectes leporinus</i> <br> -  -  -  -  -  Rhacophoridae <br> -  -  -  -  -  -  <i>Polypedates</i> <br> -  -  -  -  -  -  -  <i>Polypedates otilophus</i> <br> -  -  -  -  -  Ranidae <br> -  -  -  -  -  -  <i>Chalcorana</i> <br> -  -  -  -  -  -  -  [Chalcorana raniceps] <br> -  -  -  -  -  -  <i>Meristogenys</i> <br> -  -  -  -  -  -  -  [Meristogenys orphnocnemus] <br> -  -  -  -  -  -  <i>Staurois</i> <br> -  -  -  -  -  -  -  <i>Staurois guttatus</i> <br> -  -  -  -  -  -  -  <i>Staurois latopalmatus</i> <br> -  -  -  -  -  Megophryidae <br> -  -  -  -  -  -  <i>Leptolalax</i> <br> -  -  -  -  -  -  -  [Leptolalax friteniens] <br> -  -  -  -  -  -  <i>Leptobrachium</i> <br> -  -  -  -  -  -  -  [Leptobrachium abboti] <br></div><p></p>
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.