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102 results for “logged forest”
Data from: Spatio-temporal effects of logging and fire on tall, wet temperate eucalypt forest birds
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Data from: Inter-annual dynamics and persistence of small mammal communities in a selectively logged tropical forest in Borneo
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Data from: How persistent are the impacts of logging roads on Central African forest vegetation?
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Data from: Mating system and genetic diversity of progenies before and after logging: a case study of Bagassa guianensis (Moraceae), a low-density dioecious tree of the Amazonian forest
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Data from: Temporal dynamics in animal community assembly during post-logging succession in boreal forest
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Data from: Selective logging in tropical forests decreases the robustness of liana-tree interaction networks to the loss of host tree species
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Data from: Selective logging intensity in an East African rain forest predicts reductions in ant diversity
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Data from: Log moisture capacity does not predict epixylic bryophyte growth under thinned and unthinned forest canopies
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Data from: Fine-root exploitation strategies differ in tropical old-growth and logged-over forests in Ghana
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Data from: Multiple stages of tree seedling recruitment are altered in tropical forests degraded by selective logging
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Data from: Impacts of logging roads on tropical forests
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Data from: Logging, exotic plant invasions, and native plant reassembly in a lowland tropical rain forest
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Data from: Carbon recovery dynamics following disturbance by selective logging in Amazonian forests
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Increased importance of terrestrial vertebrate seed dispersal in tropical logged forests
<b>Description: </b><p>A large seed dispersal experiement combining seed tracking and camera trapping at ten forest sites along a wide gradient of historical logging disturbance with AGB ranging between 4.7 and 614.0 Mg ha-1, all part of the established SAFE mammal survey network. Each experiment was run for a consecutive five days using experimental seeds with different hardness (fleshy vs hard) and size (large vs small). Each seed was tracked with a spool.</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/177"><b>Resilience of Tropical Forest Ecosystem Processes to the Interactive Effects of El Nino and Forest Disturbance</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Natural Environment Research Council (Directed grant, NE/P00363X/1, <a href="https://gtr.ukri.org/projects?ref=NE%2FP00363X%2F1">https://gtr.ukri.org/projects?ref=NE%2FP00363X%2F1</a>)</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>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3901735">here</a></p><p><b>Files: </b>This consists of 1 file: template_seed_experiment_LanQieJan9_v2.xlsx</p><p><b>template_seed_experiment_LanQieJan9_v2.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Seed fate</b> (described in worksheet Seed fate)</p><p>Description: seed fate and removal distance of 12000 experimental seeds of different treatments at all sites</p><p>Number of fields: 14</p><p>Number of data rows: 12000</p><p>Fields: </p><ul><li><b>seed.id</b>: Seed ID (Field type: id)</li><li><b>Grid</b>: Experimental site ID, with the same Grid identifier used in the core SAFE project small mammal trapping work -- see SAFE dataset 256 "CORE SAFE PROJECT SMALL MAMMAL TRAPPING DATA" (Field type: id)</li><li><b>Point</b>: experimental points, selected from the camera trap points in SAFE gazetteer (Field type: location)</li><li><b>Day</b>: The day of the seed outcome. Each experimental point was set up on Day 1 and checked on Day 2-6. This numeric variable is used for temporal analysis. For treating Day as a random effect, an additional "date" label can be created by pasting Grid and Day. (Field type: numeric)</li><li><b>type</b>: Experiment seed type. OP = oil palm fruit, PK1 = single pumpkin seed, PK10 = pumpkin seed cluster of 10, PK20 = pumpkin seed cluster of 20, PT = pistachio nut. For analysis, these were classified as fleshy (OP) vs hard (other seeds), and large (> 10 g; OP, PK10, PK20) vs small (< 10 g; PT, PK1). (Field type: categorical)</li><li><b>trmt</b>: Experiment treatment. Control = seeds accessible by all animals, Cage = exclosure cage treatment with 10x10cm entrances where large vertebrates were excluded (Field type: categorical)</li><li><b>Distance</b>: Seed removal distance (Field type: numeric)</li><li><b>Bearing</b>: Compass bearing of the removed seed from experimental point (Field type: numeric)</li><li><b>Location</b>: Location of removed seed. Free text can be grouped into categories for analysis. (Field type: comments)</li><li><b>fate</b>: Seed fate. Untouched = intact and not moved. Uneaten = removed but uneaten (dispersed). Eaten = eaten or partially eaten. Unknown = seed dragged into burrows, nests or up trees with seed fate unknown, presumed eaten in analsysis to be conservative about seed dispersal (Field type: categorical)</li><li><b>Day.3</b>: Fate of dispersed seeds on subsequent days, Day.3 - Day.6, where applicable, e.g. a seed dispersed on Day 4 would only be monitored on Day 5 and Day 6. Also, not all dispersed seeds could be practically monitored. (Field type: categorical)</li><li><b>Day.4</b>: Fate of dispersed seeds on subsequent days, Day.3 - Day.6, where applicable, e.g. a seed dispersed on Day 4 would only be monitored on Day 5 and Day 6. Also, not all dispersed seeds could be practically monitored. (Field type: categorical)</li><li><b>Day.5</b>: Fate of dispersed seeds on subsequent days, Day.3 - Day.6, where applicable, e.g. a seed dispersed on Day 4 would only be monitored on Day 5 and Day 6. Also, not all dispersed seeds could be practically monitored. (Field type: categorical)</li><li><b>Day.6</b>: Fate of dispersed seeds on subsequent days, Day.3 - Day.6, where applicable, e.g. a seed dispersed on Day 4 would only be monitored on Day 5 and Day 6. Also, not all dispersed seeds could be practically monitored. (Field type: categorical)</li></ul></li><li><p><b>Camera trap records</b> (described in worksheet Camera trap records)</p><p>Description: For each visit to seed experiment by animals recorded by camera traps, we recorded the functional group (large vertebrate or small vertebrate) and seed activity (eating or moving)</p><p>Number of fields: 12</p><p>Number of data rows: 2594</p><p>Fields: </p><ul><li><b>Grid</b>: Experimental site ID, with the same Grid identifier used in the core SAFE project small mammal trapping work -- see SAFE dataset 256 "CORE SAFE PROJECT SMALL MAMMAL TRAPPING DATA" (Field type: id)</li><li><b>Point</b>: experimental points, selected from the camera trap points in SAFE gazetteer (Field type: location)</li><li><b>Day</b>: The day of the camera trap record. Each experimental point was set up on Day 1 and checked on Day 2-6. This numeric variable is used for temporal analysis. For treating Day as a random effect, an additional "date" label can be created by pasting Grid and Day. (Field type: numeric)</li><li><b>trmt</b>: Experiment treatment. Control = seeds accessible by all animals, Cage = exclosure cage treatment with 10x10cm entrances where large vertebrates were excluded (Field type: categorical)</li><li><b>func.group</b>: functional group of the seed visitor (Field type: categorical)</li><li><b>animal.comment</b>: animal species if possible to identify on photos, with some level of uncertainty (Field type: taxa)</li><li><b>visit.number</b>: visit number of the apparent repeated visits by the same animal, with some level of uncertainty (Field type: numeric)</li><li><b>PIT.tag</b>: the PIT tag number of tagged animals entering cage, detected by the antenna and recorded by the data logger (Field type: id)</li><li><b>estimated.body.size</b>: body size estimate from photos, in mm, with some level of uncertainty (Field type: comments)</li><li><b>activity</b>: observed interaction with seeds, with details in the next column. For analysis, "investigate" was not considered an active interaction. (Field type: categorical)</li><li><b>activity.comment</b>: detailed comments on the activity (Field type: comments)</li><li><b>seed.type</b>: the seed type(s) interacted with, if possible to determine, with some level of uncertainty (Field type: categorical)</li></ul></li></ol><p><b>Date range: </b>2017-03-01 to 2017-10-31</p><p><b>Latitudinal extent: </b>4.6881 to 4.7519</p><p><b>Longitudinal extent: </b>116.9633 to 117.5934</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> -  -  -  -  Rodentia <br> -  -  -  -  -  Muridae <br> -  -  -  -  -  -  <i>Maxomys</i> <br> -  -  -  -  -  -  -  <i>Maxomys surifer</i> <br> -  -  -  -  -  -  -  <i>Maxomys rajah</i> <br> -  -  -  -  -  -  <i>Sundamys</i> <br> -  -  -  -  -  -  -  <i>Sundamys muelleri</i> <br> -  -  -  -  -  -  <i>Rattus</i> <br> -  -  -  -  -  -  -  <i>Rattus exulans</i> <br> -  -  -  -  -  -  <i>Chrotomys</i> <br> -  -  -  -  -  -  -  <i>Chrotomys whiteheadi</i> (as homotypic_synonym: <i>Maxomys whiteheadi</i>)<br> -  -  -  -  -  -  <i>Leopoldamys</i> <br> -  -  -  -  -  -  -  <i>Leopoldamys sabanus</i> <br> -  -  -  -  -  Sciuridae <br> -  -  -  -  -  -  <i>Callosciurus</i> <br> -  -  -  -  -  -  -  <i>Callosciurus notatus</i> <br> -  -  -  -  -  -  -  <i>Callosciurus adamsi</i> <br> -  -  -  -  -  -  <i>Lariscus</i> <br> -  -  -  -  -  -  -  <i>Lariscus hosei</i> <br> -  -  -  -  -  -  <i>Sundasciurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus lowii</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus tenuis</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus hippurus</i> <br> -  -  -  -  -  -  <i>Rhinosciurus</i> <br> -  -  -  -  -  -  -  <i>Rhinosciurus laticaudatus</i> <br> -  -  -  -  -  Hystricidae <br> -  -  -  -  -  -  <i>Hystrix</i> <br> -  -  -  -  -  -  -  <i>Hystrix brachyura</i> <br> -  -  -  -  -  -  -  <i>Hystrix crassispinis</i> <br> -  -  -  -  Scandentia <br> -  -  -  -  -  Tupaiidae <br> -  -  -  -  -  -  <i>Tupaia</i> <br> -  -  -  -  -  -  -  <i>Tupaia tana</i> <br> -  -  -  -  -  -  -  <i>Tupaia gracilis</i> <br> -  -  -  -  -  -  -  <i>Tupaia glis</i> <br> -  -  -  -  -  -  -  <i>Tupaia minor</i> <br> -  -  -  -  -  -  -  <i>Tupaia dorsalis</i> <br> -  -  -  -  Artiodactyla <br> -  -  -  -  -  Suidae <br> -  -  -  -  -  -  <i>Sus</i> <br> -  -  -  -  -  -  -  <i>Sus barbatus</i> <br> -  -  -  -  -  Tragulidae <br> -  -  -  -  -  -  <i>Tragulus</i> <br> -  -  -  -  -  -  -  <i>Tragulus napu</i> <br> -  -  -  -  Erinaceomorpha <br> -  -  -  -  -  Erinaceidae <br> -  -  -  -  -  -  <i>Echinosorex</i> <br> -  -  -  -  -  -  -  <i>Echinosorex gymnura</i> <br> -  -  -  -  Carnivora <br> -  -  -  -  -  Viverridae <br> -  -  -  -  -  -  <i>Viverra</i> <br> -  -  -  -  -  -  -  <i>Viverra tangalunga</i> <br> -  -  -  -  -  -  <i>Paguma</i> <br> -  -  -  -  -  -  -  <i>Paguma larvata</i> <br> -  -  -  -  -  Ursidae <br> -  -  -  -  -  -  <i>Helarctos</i> <br> -  -  -  -  -  -  -  <i>Helarctos malayanus</i> <br> -  -  -  -  -  Mustelidae <br> -  -  -  -  -  -  <i>Martes</i> <br> -  -  -  -  -  -  -  <i>Martes flavigula</i> <br> -  -  -  Reptilia <br> -  -  -  -  Squamata <br> -  -  -  -  -  Gekkonidae <br> -  -  -  -  -  Scincidae <br> -  -  -  Aves <br> -  -  -  -  Columbiformes <br> -  -  -  -  -  Columbidae <br> -  -  -  -  -  -  <i>Chalcophaps</i> <br> -  -  -  -  Galliformes <br> -  -  -  -  -  Phasianidae <br> -  -  -  -  -  -  <i>Lophura</i> <br> -  -  -  -  -  -  -  <i>Lophura ignita</i> <br> -  -  -  -  -  -  <i>Argusianus</i> <br> -  -  -  -  -  -  -  <i>Argusianus argus</i> <br> -  -  -  -  Passeriformes <br> -  -  -  -  -  Pellorneidae <br> -  -  -  -  -  -  <i>Malacocincla</i> <br> -  -  -  -  -  -  -  <i>Malacocincla malaccensis</i> <br> -  -  -  -  -  -  <i>Malacopteron</i> <br> -  -  -  -  -  -  -  <i>Malacopteron affine</i> <br> -  -  -  -  -  -  <i>Pellorneum</i> <br> -  -  -  -  -  -  -  <i>Pellorneum capistratum</i> <br> -  -  -  -  -  Muscicapidae <br> -  -  -  -  -  -  <i>Trichixos</i> <br> -  -  -  -  -  -  -  <i>Trichixos pyrropygus</i> (as homotypic_synonym: <i>Copsychus pyrropygus</i>)<br> -  -  -  -  -  -  <i>Enicurus</i> <br> -  -  -  -  -  -  -  <i>Enicurus leschenaulti</i> <br> -  -  -  -  -  -  -  <i>Enicurus borneensis</i> <br> -  -  -  -  -  -  <i>Copsychus</i> <br> -  -  -  -  -  -  -  <i>Copsychus stricklandii</i> <br> -  -  -  -  -  -  -  <i>Copsychus stricklandii</i> <br> -  -  -  -  -  -  -  <i>Copsychus malabaricus</i> <br> -  -  -  Amphibia <br> -  -  -  -  Anura <br> -  -  Arthropoda <br> -  -  -  Arachnida <br> -  -  -  -  Araneae <br> -  -  -  Malacostraca <br> -  -  -  -  Decapoda <br> -  -  -  Insecta <br> -  -  -  -  Lepidoptera <br> -  -  -  -  -  Nymphalidae <br> -  -  -  -  -  -  <i>Danaus</i> <br> -  -  -  -  -  -  -  <i>Danaus plexippus</i> <br> -  -  -  -  Lepidoptera <br> -  -  -  -  -  Nymphalidae <br> -  -  -  -  -  -  <i>Danaus</i> <br> -  -  -  -  -  -  -  <i>Danaus plexippus</i> <br> -  -  -  -  Coleoptera <br> -  -  -  -  Phasmida <br> -  -  -  -  Orthoptera <br> -  -  -  -  -  Grasshooper <br> -  -  -  -  -  Gryllidae <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Formicidae <br> -  -  Annelida <br> -  -  -  Clitellata <br> -  -  -  -  Arhynchobdellida <br> -  -  -  -  -  Haemadipsidae <br> -  -  -  -  -  -  <i>Haemadipsa</i> <br> -  -  Mollusca <br> -  -  -  Gastropoda <br></div><p></p>
Long-term logging residue loadings affect tree growth but not soil nutrients in lodgepole pine forests
<p>Both above- and below-ground characteristics are affected by logging residue loadings. Long-term monitoring of tree growth and soil nutrients was conducted. We found that tree growth but not soil nutrients were affected. There were dynamic relationships between tree growth and logging residue loadings.</p>
Data from: The impact of tropical forest logging and oil palm agriculture on the soil microbiome
Selective logging and forest conversion to oil palm agriculture are rapidly altering tropical forests. However, functional responses of the soil microbiome to these land-use changes are poorly understood. Using 16S rRNA gene and shotgun metagenomic sequencing, we compared composition and functional attributes of soil biota between unlogged, once-logged and twice-logged rainforest, and areas converted to oil palm plantations in Sabah, Borneo. Although there was no significant effect of logging history, we found a significant difference between the taxonomic and functional composition of both primary and logged forests and oil palm. Oil palm had greater abundances of genes associated with DNA, RNA, protein metabolism and other core metabolic functions, but conversely, lower abundance of genes associated with secondary metabolism and cell–cell interactions, indicating less importance of antagonism or mutualism in the more oligotrophic oil palm environment. Overall, these results show a striking difference in taxonomic composition and functional gene diversity of soil microorganisms between oil palm and forest, but no significant difference between primary forest and forest areas with differing logging history. This reinforces the view that logged forest retains most features and functions of the original soil community. However, networks based on strong correlations between taxonomy and functions showed that network complexity is unexpectedly increased due to both logging and oil palm agriculture, which suggests a pervasive effect of both land-use changes on the interaction of soil microbes.
Agent‐based modeling of the effects of forest dynamics, selective logging, and fragment size on epiphyte communities
<p>Forest canopies play a crucial role in structuring communities of vascular epiphytes by providing substrate for colonization, by locally varying microclimate, and by causing epiphyte mortality due to branch or tree fall. However, as field studies in the three-dimensional habitat of epiphytes are generally challenging, our understanding of how forest structure and dynamics influence the structure and dynamics of epiphyte communities is scarce. Mechanistic models can improve our understanding of epiphyte community dynamics. We present such a model that couples dispersal, growth, and mortality of individual epiphytes with substrate dynamics, obtained from a three-dimensional functional-structural forest model, allowing the study of forest-epiphyte interactions. After validating the epiphyte model with independent field data, we performed several theoretical simulation experiments to assess how (1) differences in natural forest dynamics, (2) selective logging, and (3) forest fragmentation could influence the long-term dynamics of epiphyte communities. The proportion of arboreal substrate occupied by epiphytes (i.e. saturation level) was tightly linked with forest dynamics and increased with decreasing forest turnover rates. While species richness was, in general, negatively correlated with forest turnover rates, low species numbers in forests with very low turnover rates were due to competitive exclusion when epiphyte communities became saturated. Logging had a negative impact on epiphyte communities, potentially leading to a near-complete extirpation of epiphytes when the simulated target diameters fell below a threshold. Fragment size had no effect on epiphyte abundance and saturation level but correlated positively with species numbers. Synthesis: The presented model is a first step towards studying the dynamic forest-epiphyte interactions in an agent-based modelling framework. Our study suggests forest dynamics as key factor in controlling epiphyte communities. Thus, both natural and human-induced changes in forest dynamics, e.g. increased mortality rates or the loss of large trees, pose challenges for epiphyte conservation.</p>
Habitat fragmentation and logging affects the occurrence of the lesser mouse deer in tropical forest reserves
<p>Due to rapid urbanization, logging, and agricultural expansion, forest fragmentation is negatively affecting native wildlife populations throughout the tropics. <span>This study examined the effects of landscape and habitat characteristics on the lesser </span>mouse deer, <i>Tragulus kanchil,</i><span> populations in Peninsular Malaysia. A total of 315 camera traps were deployed in eight forest reserves. This study provides critical ecological information for managing and conserving understudied populations of <i>T. kanchil</i>. We found that the detection of <i>T. kanchil </i>was attributed to forest fragmentation.<i> </i>Forest patches had the detection of <i>T. kanchil</i> four times greater than continuous forests<i>. </i>The detection of <i>T. kanchil</i> was nearly three times higher in the peat swamp forest compared to the lowland dipterocarp forests. Surprisingly, the detection of <i>T. kanchil</i> was almost twice lower in the unlogged forests compared to logged forests. The detection of <i>T. kanchil</i> increased with the presence of trees, particularly those with DBH of 5 cm to 45 cm, canopy cover, number of saplings</span> <span>and palms, number of dead fallen trees, and distance from nearest roads. However, detection decreased with a greater number of trees with a DBH greater than 45 cm and higher elevation. We recommend that conservation stakeholders take the necessary steps to support the conservation of mouse deer species and its natural habitats regardless of whether these forests are fragmented or continuous. These steps include eradicating poaching, habitat degradation, and further deforestation.</span></p>
Figure 8 from: Klimaszewski J, Work T, Thiffault E, Bourdon C, Pare D, Bousquet Y, Venier L, Titus B (2013) Initial responses of rove and ground beetles (Coleoptera, Staphylinidae, Carabidae) to removal of logging residues following clearcut harvesting in the boreal forest of Quebec, Canada. ZooKeys 258: 31-52. https://doi.org/10.3897/zookeys.258.4174
Figure 8 - a–d Colour images of abundant species: a Quedius labradorensis Smetana b Gabrius brevipennis (Horn) c Pseudopsis subulata Herman d Pterostichus punctatissimus (Randall).
Figure 7 from: Klimaszewski J, Work T, Thiffault E, Bourdon C, Pare D, Bousquet Y, Venier L, Titus B (2013) Initial responses of rove and ground beetles (Coleoptera, Staphylinidae, Carabidae) to removal of logging residues following clearcut harvesting in the boreal forest of Quebec, Canada. ZooKeys 258: 31-52. https://doi.org/10.3897/zookeys.258.4174
Figure 7 - a–d Colour images of abundant species: a Atheta capsularis Klimaszewski b Atheta klagesi Bernhauer c Atheta strigosula Casey d Tachinus fumipennis (Say).
ScienceDex guides
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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.