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411 results for “Tropical rainforests”
Fig. 5 in Comb-footed spiders (Araneae: Theridiidae) in the tropical rainforest of Xishuangbanna, Southwest China
Fig. 5. Allothymoites sculptilis sp. nov., holotype male. A. Pedipalpus, ventral view; B. MA and conductor, ventral view; C. Embolus, ventral view. Scale bars = 0.10 mm.
Fig. 1 in Comb-footed spiders (Araneae: Theridiidae) in the tropical rainforest of Xishuangbanna, Southwest China
Fig. 1. Allothymoites repandus sp. nov., holotype male. A. Pedipalpus, prolateral view; B. Pedipalpus, retrolateral view; Scale bar = 0.05 mm.
Fig. 13 in Comb-footed spiders (Araneae: Theridiidae) in the tropical rainforest of Xishuangbanna, Southwest China
Fig. 13. Carniella foliosa sp. nov., holotype male. A. Pedipalpus, prolateral view; B. Pedipalpus, retrolateral view. Scale bar = 0.10 mm.
Fig. 9 in Comb-footed spiders (Araneae: Theridiidae) in the tropical rainforest of Xishuangbanna, Southwest China
Fig. 9. Ariamnes columnaceus sp. nov., holotype male. A. Pedipalpus (cymbium removed), ventral view; B. Pedipalpus, ventral view; C. Pedipalpus, prolateral view; D. Pedipalpus, retrolateral view. Scale bars = 0.10 mm.
Figure 1 A in Cicadas impact bird communication in a noisy tropical rainforest
Figure 1 A comparison of the "soundscape" recorded during two 30 s periods from the same location on 6 July 2012, within secondary wet forest at Las Cruces Biological Station, Costa Rica. (a) A spectrogram from approximately 08:14 AM, before the onset of Zammara cicada choruses and shows 7 unique vocalizations (Arremon aurantiirostris call, Picumnus olivaceus, Arremon torquatus, Catharus aurantiirostris, Arremon aurantiirostris song, Phaeothlypis fulvicauda, Formicarius analis). (b) A spectrogram from approximately 08:50 AM, just after onset of Zammara cicada choruses, which can be seen by the dark, pulsing signal with a base frequency occupying much of the bandwidth between approximately 2.7 and 6.5 kHz. No birds are vocalizing during this period.
Figure 2 in Cicadas impact bird communication in a noisy tropical rainforest
Figure 2 Rate of overlap, excluding "complete" overlap, between bird and cicada signals before versus after the onset of cicada signaling for 7 recording days during June and July 2012 in secondary wet forest at Las Cruces Biological Station, Costa Rica. The "overlap before" bar represents the number of unique bird vocalizations produced prior to the onset of Zammara chorusing, with spectra that overlap to any degree with the normal base frequency range of Zammara signals. The "overlap after" bar represents the number of unique bird vocalizations with spectra that overlapped to any degree with the actual Zammara signals.
Data from: Cavities and the demographic performance of tropical rainforest trees
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Data from: Impact of human foraging on tree diversity, composition and abundance in a tropical rainforest
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Data from: Tropical biome switching: Ant communities transition from savanna to rainforest following cessation of burning
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Active restoration fosters better recovery of tropical rainforest birds than natural regeneration in degraded forest fragments
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Small mammals reduce distance-dependence and increase seed predation risk in tropical rainforest fragments
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Data from: Effects of Habitat Structure and Adjacent Habitats on Birds in Tropical Rainforest Fragments and Shaded Plantations in the Western Ghats, India
<p>This dataset includes bird community, habitat structure, and vegetation data from the following publication:</p> <p>Raman, T.R.S. 2006. Effects of Habitat Structure and Adjacent Habitats on Birds in Tropical Rainforest Fragments and Shaded Plantations in the Western Ghats, India. <em>Biodiversity and Conservation</em> 15: 1577–1607. https://doi.org/10.1007/s10531-005-2352-5</p> <p><strong>Abstract: </strong>As large nature reserves occupy only a fraction of the earth's land surface, conservation biologists are critically examining the role of private lands, habitat fragments, and plantations for conservation. This study in a biodiversity hotspot and endemic bird area, the Western Ghats mountains of India, examined the effects of habitat structure, floristics, and adjacent habitats on bird communities in shade-coffee and cardamom plantations and tropical rainforest fragments. Habitat and birds were sampled in 13 sites: six fragments (three relatively isolated and three with canopy connectivity with adjoining shade-coffee plantations and forests), six plantations differing in canopy tree species composition (five coffee and one cardamom), and one undisturbed primary rainforest control site in the Anamalai hills. Around 3300 detections of 6000 individual birds belonging to 106 species were obtained. The coffee plantations were poorer than rainforest in rainforest bird species, particularly endemic species, but the rustic cardamom plantation with diverse, native rainforest shade trees, had bird species richness and abundance comparable to primary rainforest. Plantations and fragments that adjoined habitats providing greater tree canopy connectivity supported more rainforest and fewer open-forest bird species and individuals than sites that lacked such connectivity. These effects were mediated by strong positive effects of vegetation structure, particularly woody plant variables, cane, and bamboo, on bird community structure. Bird community composition was however positively correlated only to floristic (tree species) composition of sites. The maintenance or restoration of habitat structure and (shade) tree species composition in shade-coffee and cardamom plantations and rainforest fragments can aid in rainforest bird conservation in the regional landscape.</p>
Effects of habitat modification on a tritrophic cascade in a lowland tropical rainforest
<b>Description: </b><p>The impact of anthropogenic disturbance of tropical rainforests on ecosystem processes is poorly understood. In this study I investigate how habitat modification in tropical rainforests may mediate a tritrophic cascade with resultant effects on herbivory, a key ecosystem process. I adopt a stepwise approach through the trophic levels, assessing the relationships between forest quality and the bird community assemblage, and corresponding impacts on predation rates and herbivory. I measured the bird community across a forest quality gradient, surveying 24 sites within a modified lowland tropical rainforest in Borneo. At each sampling location I established two treatments, one using a large (2 x 2 x 1.5m) cage designed to exclude vertebrates, and the second a control where no vertebrate exclusion was in place. I measured predation rates using dummy caterpillars, and herbivory rates on selected leaves in each treatment at all sampling locations. I used piecewise structural equation modelling to develop a path model between predictor and response variables. I established a significant pathway between increasing forest quality, increased richness of the bird community and higher vertebrate predation rates. Conversely, invertebrate predation rates declined with increasing forest quality. The effect of increasing forest quality did not mediate a trophic cascade bringing about an increase in herbivory. However, the effect of vertebrate exclusion mediated a trophic cascade and an increase in herbivory in higher forest quality, where invertebrate predation levels are lower. The results of the study therefore reflect the dampening of the tritrophic cascade across a forest quality gradient, and high functional redundancy in predatory function in forests of low quality. The study also highlights the importance of avian predatory function in forests of higher quality. A reduction in large vertebrate predators in undisturbed tropical rainforests may therefore result in cascading effects on herbivory, which may in turn have implications for primary productivity and nutrient cycling. These findings have significant implications for tropical forest conservation and management. Further research should place emphasis on addressing the effects of the loss of apex predators on key ecosystem processes.</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/201"><b>The effects of habitat modification on a tritrophic cascade in a lowland tropical rainforest</b></a></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (SABC) (Research licence JKN/MBS.1000-2/2 JLD.8 (66))</li><li>Sabah Biodiversity Centre (SABC) (Research licence JKM/MBS.1000-2/2 JLD.8 (61) )</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=3981222">here</a></p><p><b>Files: </b>This dataset consists of 2 files: FraserExclusionPlots_AFedit_150820.xlsx, FraserAdam_TFE_2019_SAFE_AudioFiles.zip</p><p><b>FraserExclusionPlots_AFedit_150820.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>Bird point counts</b> (described in worksheet PointCounts)</p><p>Description: Repeated bird point counts at all sites</p><p>Number of fields: 89</p><p>Number of data rows: 72</p><p>Fields: </p><ul><li><b>Visit_Code</b>: Unique site x replicate code (Field type: id)</li><li><b>Plot</b>: SAFE Project plot ID (Field type: location)</li><li><b>Visit</b>: Visit number (Field type: replicate)</li><li><b>Date</b>: Date of point count (Field type: date)</li><li><b>Time_Start</b>: Time at start of point count (Field type: time)</li><li><b>Time_Finish</b>: Time at end of point count (Field type: time)</li><li><b>Weather</b>: Observations on weather conditions (Field type: comments)</li><li><b>Ashy.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.fairy.bluebird</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.paradise.flycatcher</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.red.eyed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Banded.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Banded.bay.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>Black.and.red.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Black.and.yellow.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Black.capped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Black.headed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Black.headed.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Black.naped.monarch</b>: Count of individuals (Field type: abundance)</li><li><b>Blue.eared.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Blue.headed.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Bold.striped.tit.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Bornean.banded.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Bornean.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Bronzed.drongo</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.fulvetta</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.backed.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.throated.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Bushy.crested.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.backed.scimitar.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.munia</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.rumped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.winged.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Collared.kingfisher</b>: Count of individuals (Field type: abundance)</li><li><b>Common.emerald.dove</b>: Count of individuals (Field type: abundance)</li><li><b>Cream.vented.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Crested.fireback</b>: Count of individuals (Field type: abundance)</li><li><b>Crimson.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Dark.necked.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Diards.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Dusky.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Fiery.minivet</b>: Count of individuals (Field type: abundance)</li><li><b>Fluffy.backed.tit.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Gold.whiskered.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Great.argus</b>: Count of individuals (Field type: abundance)</li><li><b>Greater.green.leafbird</b>: Count of individuals (Field type: abundance)</li><li><b>Greater.racket.tailed.drongo</b>: Count of individuals (Field type: abundance)</li><li><b>Green.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Grey.headed.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Helmeted.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Hooded.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Lesser.green.leafbird</b>: Count of individuals (Field type: abundance)</li><li><b>Little.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Long.billed.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Malaysian.blue.flycatcher</b>: Count of individuals (Field type: abundance)</li><li><b>Moustached.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Orange.bellied.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Pied.fantail</b>: Count of individuals (Field type: abundance)</li><li><b>Plain.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Plaintive.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>Puff.backed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Purple.naped.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Raffless.malkoha</b>: Count of individuals (Field type: abundance)</li><li><b>Red.bearded.bee.eater</b>: Count of individuals (Field type: abundance)</li><li><b>Red.naped.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Red.throated.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Rhinoceros.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.collared.kingfisher</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.crowned.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.fronted.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.tailed.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.tailed.shama</b>: Count of individuals (Field type: abundance)</li><li><b>Scarlet.rumped.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Short.tailed.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Short.toed.coucal</b>: Count of individuals (Field type: abundance)</li><li><b>Slender.billed.crow</b>: Count of individuals (Field type: abundance)</li><li><b>Sooty.capped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Spectacled.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Spectacled.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Violet.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>White.crowned.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>White.crowned.shama</b>: Count of individuals (Field type: abundance)</li><li><b>Woodpecker.sp.</b>: Count of individuals (Field type: abundance)</li><li><b>Wreathed.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.breasted.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.crowned.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.rumped.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.vented.bulbul</b>: Count of individuals (Field type: abundance)</li></ul></li><li><p><b>Leaf herbivory</b> (described in worksheet LeafHerbivory)</p><p>Description: Within each treatment, I tagged and numbered seven leaves. I chose a variation of leaf ages within each treatment, as recommended by Coley and Barone (1996). I measured leaf area on all tagged leaves at monthly intervals, as recommended by Coley and Barone (1996) and detailed in Harrison and Banks-Leite (2019), between March and May 2019. I calculated arthropod herbivory rate using ImageJ software (Schindelin et al. 2012) to determine the percentage leaf area lost (LAL) over time.</p><p>Number of fields: 9</p><p>Number of data rows: 336</p><p>Fields: </p><ul><li><b>Site</b>: SAFE Project plot ID (Field type: location)</li><li><b>Treatment</b>: Experimental treatment: inside or outside exclusion cage? (Field type: categorical)</li><li><b>Leaf</b>: ID number for each leaf (Field type: replicate)</li><li><b>DateFirstObs</b>: Date of first leaf observation (Field type: date)</li><li><b>LeafArea</b>: Leaf area at first observation (Field type: numeric)</li><li><b>DateFinalObs</b>: Date of final leaf observation (Field type: date)</li><li><b>FinalLeafArea</b>: Leaf area at last observation (Field type: numeric)</li><li><b>LostArea</b>: Area of leaf lost to herbivory (Field type: numeric)</li><li><b>PercentLostArea</b>: Percent of leaf area lost to herbivory (Field type: numeric)</li></ul></li><li><p><b>Insect predation data</b> (described in worksheet PredationData)</p><p>Description: I assessed predation rates on invertebrates by placing five plasticine dummy caterpillars within each treatment, at each sampling location. The methods were based on those described in Howe, Lövei and Nachman (2009) Roslin et al. (2017) and Roels, Porter and Lindell (2018). I placed five fresh plasticine caterpillars at least one metre apart from each other within the treatment and recovered the caterpillars after 14 days. I quantified predation attempts on each set of caterpillars within each treatment, following guidance on visual predator identification as per Low et al. (2014).</p><p>Number of fields: 9</p><p>Number of data rows: 144</p><p>Fields: </p><ul><li><b>Visit_Code</b>: Unique site x replicate code (Field type: id)</li><li><b>Plot</b>: SAFE Project plot ID (Field type: location)</li><li><b>Visit</b>: Visit number (Field type: replicate)</li><li><b>Date</b>: Date of point count (Field type: date)</li><li><b>Treatment</b>: Experimental treatment: inside or outside exclusion cage? (Field type: categorical)</li><li><b>Invertebrate</b>: Number of plasticine invertebrate mimics attacked by invertebrate predator (Field type: numeric)</li><li><b>Mammal</b>: Number of plasticine invertebrate mimics attacked by mammalian predator (Field type: numeric)</li><li><b>Bird</b>: Number of plasticine invertebrate mimics attacked by avian predator (Field type: numeric)</li><li><b>Other</b>: Number of plasticine invertebrate mimics attacked by predator that couldn't be identified (Field type: numeric)</li></ul></li></ol><p><b>FraserAdam_TFE_2019_SAFE_AudioFiles.zip</b></p><p>Description: Audio files recorded during points counts</p><p><b>Date range: </b>2019-03-04 to 2019-05-10</p><p><b>Latitudinal extent: </b>4.6815 to 4.7435</p><p><b>Longitudinal extent: </b>117.5396 to 117.5971</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> -  -  -  Aves <br> -  -  -  -  Piciformes <br> -  -  -  -  -  Picidae <br> -  -  -  -  -  Ramphastidae <br> -  -  -  -  -  -  <i>Psilopogon</i> <br> -  -  -  -  -  -  -  <i>Psilopogon duvaucelii</i> <br> -  -  -  -  -  -  -  <i>Psilopogon chrysopogon</i> <br> -  -  -  -  -  -  -  <i>Psilopogon mystacophanos</i> <br> -  -  -  -  -  -  -  <i>Psilopogon henricii</i> <br> -  -  -  -  -  -  <i>Caloramphus</i> <br> -  -  -  -  -  -  -  <i>Caloramphus fuliginosus</i> <br> -  -  -  -  Coraciiformes <br> -  -  -  -  -  Alcedinidae <br> -  -  -  -  -  -  <i>Todiramphus</i> <br> -  -  -  -  -  -  -  <i>Todiramphus chloris</i> <br> -  -  -  -  -  -  <i>Actenoides</i> <br> -  -  -  -  -  -  -  <i>Actenoides concretus</i> <br> -  -  -  -  -  Meropidae <br> -  -  -  -  -  -  <i>Nyctyornis</i> <br> -  -  -  -  -  -  -  <i>Nyctyornis amictus</i> <br> -  -  -  -  Galliformes <br> -  -  -  -  -  Phasianidae <br> -  -  -  -  -  -  <i>Argusianus</i> <br> -  -  -  -  -  -  -  <i>Argusianus argus</i> <br> -  -  -  -  -  -  <i>Lophura</i> <br> -  -  -  -  -  -  -  <i>Lophura ignita</i> <br> -  -  -  -  Columbiformes <br> -  -  -  -  -  Columbidae <br> -  -  -  -  -  -  <i>Chalcophaps</i> <br> -  -  -  -  -  -  -  <i>Chalcophaps indica</i> <br> -  -  -  -  Passeriformes <br> -  -  -  -  -  Corvidae <br> -  -  -  -  -  -  <i>Corvus</i> <br> -  -  -  -  -  -  -  <i>Corvus enca</i> <br> -  -  -  -  -  Pellorneidae <br> -  -  -  -  -  -  <i>Pellorneum</i> <br> -  -  -  -  -  -  -  <i>Pellorneum capistratum</i> <br> -  -  -  -  -  -  <i>Alcippe</i> <br> -  -  -  -  -  -  -  <i>Alcippe brunneicauda</i> <br> -  -  -  -  -  -  <i>Trichastoma</i> <br> -  -  -  -  -  -  -  <i>Trichastoma malaccense</i> <br> -  -  -  -  -  -  <i>Malacopteron</i> <br> -  -  -  -  -  -  -  <i>Malacopteron magnirostre</i> <br> -  -  -  -  -  -  -  <i>Malacopteron magnum</i> <br> -  -  -  -  -  -  -  <i>Malacopteron affine</i> <br> -  -  -  -  -  Cisticolidae <br> -  -  -  -  -  -  <i>Orthotomus</i> <br> -  -  -  -  -  -  -  <i>Orthotomus ruficeps</i> <br> -  -  -  -  -  -  -  <i>Orthotomus atrogularis</i> <br> -  -  -  -  -  -  -  <i>Orthotomus sericeus</i> <br> -  -  -  -  -  Rhipiduridae <br> -  -  -  -  -  -  <i>Rhipidura</i> <br> -  -  -  -  -  -  -  <i>Rhipidura javanica</i> <br> -  -  -  -  -  Muscicapidae <br> -  -  -  -  -  -  <i>Trichixos</i> <br> -  -  -  -  -  -  -  <i>Trichixos pyrropygus</i> <br> -  -  -  -  -  -  <i>Cyornis</i> <br> -  -  -  -  -  -  -  <i>Cyornis turcosus</i> <br> -  -  -  -  -  -  <i>Copsychus</i> <br> -  -  -  -  -  -  -  <i>Copsychus stricklandii</i> <br> -  -  -  -  -  Dicaeidae <br> -  -  -  -  -  -  <i>Dicaeum</i> <br> -  -  -  -  -  -  -  <i>Dicaeum everetti</i> <br> -  -  -  -  -  -  -  <i>Dicaeum trigonostigma</i> <br> -  -  -  -  -  -  <i>Prionochilus</i> <br> -  -  -  -  -  -  -  <i>Prionochilus maculatus</i> <br> -  -  -  -  -  -  -  <i>Prionochilus xanthopygius</i> <br> -  -  -  -  -  Campephagidae <br> -  -  -  -  -  -  <i>Pericrocotus</i> <br> -  -  -  -  -  -  -  <i>Pericrocotus igneus</i> <br> -  -  -  -  -  Timaliidae <br> -  -  -  -  -  -  <i>Pomatorhinus</i> <br> -  -  -  -  -  -  -  <i>Pomatorhinus montanus</i> <br> -  -  -  -  -  -  <i>Cyanoderma</i> <br> -  -  -  -  -  -  -  <i>Cyanoderma erythropterum</i> <br> -  -  -  -  -  -  -  <i>Cyanoderma rufifrons</i> <br> -  -  -  -  -  -  <i>Stachyris</i> <br> -  -  -  -  -  -  -  <i>Stachyris maculata</i> <br> -  -  -  -  -  -  -  <i>Stachyris poliocephala</i> <br> -  -  -  -  -  -  <i>Macronus</i> <br> -  -  -  -  -  -  -  <i>Macronus ptilosus</i> <br> -  -  -  -  -  -  <i>Mixornis</i> <br> -  -  -  -  -  -  -  <i>Mixornis bornensis</i> <br> -  -  -  -  -  Eurylaimidae <br> -  -  -  -  -  -  <i>Eurylaimus</i> <br> -  -  -  -  -  -  -  <i>Eurylaimus javanicus</i> <br> -  -  -  -  -  -  -  <i>Eurylaimus ochromalus</i> <br> -  -  -  -  -  -  <i>Calyptomena</i> <br> -  -  -  -  -  -  -  <i>Calyptomena viridis</i> <br> -  -  -  -  -  -  <i>Cymbirhynchus</i> <br> -  -  -  -  -  -  -  <i>Cymbirhynchus macrorhynchos</i> <br> -  -  -  -  -  -  <i>Corydon</i> <br> -  -  -  -  -  -  -  <i>Corydon sumatranus</i> <br> -  -  -  -  -  Dicruridae <br> -  -  -  -  -  -  <i>Dicrurus</i> <br> -  -  -  -  -  -  -  <i>Dicrurus aeneus</i> <br> -  -  -  -  -  -  -  <i>Dicrurus paradiseus</i> <br> -  -  -  -  -  Estrildidae <br> -  -  -  -  -  -  <i>Lonchura</i> <br> -  -  -  -  -  -  -  <i>Lonchura atricapilla</i> <br> -  -  -  -  -  Pycnonotidae <br> -  -  -  -  -  -  <i>Pycnonotus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus brunneus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus atriceps</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus simplex</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus eutilotus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus erythropthalmos</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus goiavier</i> <br> -  -  -  -  -  Chloropseidae <br> -  -  -  -  -  -  <i>Chloropsis</i> <br> -  -  -  -  -  -  -  <i>Chloropsis sonnerati</i> <br> -  -  -  -  -  -  -  <i>Chloropsis cyanopogon</i> <br> -  -  -  -  -  Nectariniidae <br> -  -  -  -  -  -  <i>Aethopyga</i> <br> -  -  -  -  -  -  -  <i>Aethopyga siparaja</i> <br> -  -  -  -  -  -  <i>Anthreptes</i> <br> -  -  -  -  -  -  -  <i>Anthreptes malacensis</i> <br> -  -  -  -  -  -  -  <i>Anthreptes simplex</i> <br> -  -  -  -  -  -  <i>Arachnothera</i> <br> -  -  -  -  -  -  -  <i>Arachnothera everetti</i> <br> -  -  -  -  -  -  -  <i>Arachnothera longirostra</i> <br> -  -  -  -  -  -  -  <i>Arachnothera robusta</i> <br> -  -  -  -  -  -  -  <i>Arachnothera flavigaster</i> <br> -  -  -  -  -  -  <i>Kurochkinegramma</i> <br> -  -  -  -  -  -  -  <i>Kurochkinegramma hypogrammicum</i> <br> -  -  -  -  -  Irenidae <br> -  -  -  -  -  -  <i>Irena</i> <br> -  -  -  -  -  -  -  <i>Irena puella</i> <br> -  -  -  -  -  Pittidae <br> -  -  -  -  -  -  <i>Erythropitta</i> <br> -  -  -  -  -  -  -  <i>Erythropitta ussheri</i> <br> -  -  -  -  -  -  <i>Pitta</i> <br> -  -  -  -  -  -  -  <i>Pitta sordida</i> <br> -  -  -  -  -  Monarchidae <br> -  -  -  -  -  -  <i>Hypothymis</i> <br> -  -  -  -  -  -  -  <i>Hypothymis azurea</i> <br> -  -  -  -  -  -  <i>Terpsiphone</i> <br> -  -  -  -  -  -  -  <i>Terpsiphone paradisi</i> <br> -  -  -  -  Trogoniformes <br> -  -  -  -  -  Trogonidae <br> -  -  -  -  -  -  <i>Harpactes</i> <br> -  -  -  -  -  -  -  <i>Harpactes diardii</i> <br> -  -  -  -  -  -  -  <i>Harpactes kasumba</i> <br> -  -  -  -  -  -  -  <i>Harpactes duvaucelii</i> <br> -  -  -  -  Cuculiformes <br> -  -  -  -  -  Cuculidae <br> -  -  -  -  -  -  <i>Chrysococcyx</i> <br> -  -  -  -  -  -  -  <i>Chrysococcyx xanthorhynchus</i> <br> -  -  -  -  -  -  <i>Centropus</i> <br> -  -  -  -  -  -  -  <i>Centropus rectunguis</i> <br> -  -  -  -  -  -  <i>Cacomantis</i> <br> -  -  -  -  -  -  -  <i>Cacomantis sonneratii</i> <br> -  -  -  -  -  -  -  <i>Cacomantis merulinus</i> <br> -  -  -  -  -  -  <i>Rhinortha</i> <br> -  -  -  -  -  -  -  <i>Rhinortha chlorophaea</i> <br> -  -  -  -  Bucerotiformes <br> -  -  -  -  -  Bucerotidae <br> -  -  -  -  -  -  <i>Berenicornis</i> <br> -  -  -  -  -  -  -  <i>Berenicornis comatus</i> <br> -  -  -  -  -  -  <i>Anorrhinus</i> <br> -  -  -  -  -  -  -  <i>Anorrhinus galeritus</i> <br> -  -  -  -  -  -  <i>Rhyticeros</i> <br> -  -  -  -  -  -  -  <i>Rhyticeros undulatus</i> <br> -  -  -  -  -  -  <i>Buceros</i> <br> -  -  -  -  -  -  -  <i>Buceros rhinoceros</i> <br> -  -  -  -  -  -  <i>Rhinoplax</i> <br> -  -  -  -  -  -  -  <i>Rhinoplax vigil</i> <br> -  -  -  -  <i>Hydrornis</i> <br> -  -  -  -  -  <i>Hydrornis baudii</i> <br> -  -  -  -  -  <i>Hydrornis schwaneri</i> <br></div><p></p>
Destructive harvest data collected from four large tropical rainforest trees in Floresta Nacional de Caxiuanã
<p>Title<br> -----</p> <p>Destructive harvest data collected from four large tropical rainforest trees in Floresta Nacional de Caxiuanã</p> <p>Authors<br> ------- </p> <p>A. Burt<br> M. Boni Vicari<br> A. C. L. da Costa<br> I. Coughlin<br> P. Meir<br> L. Rowland<br> M. Disney</p> <p>Contact<br> -------</p> <p>a.burt@ucl.ac.uk</p> <p>License<br> -------</p> <p>These data are distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC BY 4.0) - see the LICENSE file for details.</p> <p>Overview<br> --------</p> <p>We harvested four large tropical rainforest trees (diameter range: 0.6-1.2m, height range: 30-46m) in a natural closed forest stand in Floresta Nacional de Caxiuanã, Pará, Brazil (approx. coordinates in the WGS-84 datum: -1.798, -51.435 degrees), during August/October 2018.<br> The objective was to measure the green mass of each tree in its entirety, and to measure woody tissue green-to-dry mass and volume ratios, and basic/green/dry woody tissue density. <br> A complete description of the four trees, these data, and the companion terrestrial lidar data (collected pre-harvest) can be found in our paper entitled: ‘New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar’.</p> <p>Acquisition<br> -----------</p> <p>Field measurements:</p> <p>Neighbouring vegetation surrounding each tree was removed, including complete clearing of the felling area.<br> Stem diameter was measured using a circumference/diameter tape at either 1.3m above-ground, or 0.5m above-buttress.<br> Each tree was felled onto tarpaulin using a STIHL MS 650 chainsaw with a 20” bar length and 13/64” chain loop.<br> Tree height (incl. stump) was measured with a surveyor's tape measure, and GPS data were acquired from the centre of the stump using a Garmin GPSMAP 64st.<br> The stem (incl. stump) and crown were cut into manageable sections, and the mass of each section was measured via weighing using two Adam LHS 500 crane scales.<br> Mass measurements commenced immediately post-felling, requiring two, four, four and two days to complete measurement of CAX-H_T1 to CAX-H_T4 respectively.<br> Multiple discs (approx. 50mm thick) were also collected from each tree: at 1.3m and 25%, 50% and 75% the length of the stem, and up to 3x discs were taken from the mid-points of 1st, 2nd and 3rd order branches (totalling a minimum of 11 discs per tree).<br> Foliage/fruit samples were retained to confirm taxonomic identity at the Museu Paraense Emílio Goeldi, Belem, Pará, Brazil.</p> <p>Laboratory measurements:</p> <p>All discs were reduced to a set of subsamples using a consistent approach: for any particular disc, they were cut as guided by parallel chords straddling above and below the major axis, each with approximate dimensions of 150mm x 50mm x 50mm (i.e., each set included periderm, phloem, cambium, xylem and pith tissues).<br> Mass and volume measurements were made on each subsample in a green and dry state.<br> Subsamples were considered in a green state after soaking for 48 hours, and a dry state once a constant mass had been attained whilst drying in an oven at 105 degree Celsius.<br> Mass was measured using an Adam NBL4602i Nimbus Precision balance, and volume measurements were made on the same balance via Archimedes’ principle.</p> <p>Processing<br> ----------</p> <p>Dry mass was estimated from measured green mass and an estimate of whole-tree woody tissue green-to-dry mass ratio. <br> Whole-tree woody tissue green-to-dry mass ratio was estimated by weighting the mean value from subsamples in each pool (stem and crown), by the green mass in each pool.<br> This mass-weighted approach was also used for estimating whole-tree woody tissue green-to-dry volume ratio and whole-tree basic/green/dry woody tissue density. </p> <p>File and directory naming convention<br> ------------------------------------</p> <p>The four trees are identified: CAX-H_T1, CAX-H_T2, CAX-H_T3 and CAX-H_T4.<br> The various files and directories are described as follows: </p> <p>./CAXH-H/<br> ├───overview/<br> │ ├───cal_cert/ (Directory: contains balance calibration certificates)<br> │ ├───images/ (Directory: various photographs illustrating the field and laboratory measurements)<br> │ ├───sentinel-2 (Directory: contains RGB and NDVI images from Sentinel-2 data over the harvest site during the campaign dates)<br> │ ├───CAX-H.results.xlsx (File: top-level results)<br> ├───CAX-H_T1/ (Directory: tree-level directories)<br> ├───CAX-H_T2/<br> ├───CAX-H_T3/<br> ├───CAX-H_T4/<br> │ ├───fieldsheets/<br> │ │ ├───CAX-H_T4.fieldsheets.pdf (File: fieldsheets from the original campaign)<br> │ │ ├───CAX-H_T4.remeasurement.fieldsheets.pdf (File: fieldsheets from the remeasurement campaign)<br> │ ├───gps/<br> │ │ ├───CAX-H_T4.gps.txt<br> │ ├───media/ (Directory: contains various photographs and videos of the field measurements, and the discs and subsamples)<br> │ ├───CAX-H_T4.results.xlsx (File: tree-level results)</p>
Data from: Three decades of annual growth, mortality, physical condition, and microsite for ten tropical rainforest tree species
In lowland tropical rainforest, hundreds of tree species typically occur within mesoscale landscapes (50-500 ha). There is no consensus ecological theory that accounts for the coexistence of so many species with similar morphologies and the same fundamental requirements of light, nutrients, water, and physical space. In part this is due to the limited understanding of post-establishment ecology for the vast majority of tropical tree species. Of even more concern is the lack of understanding of how these trees are responding to on-going atmospheric and climatic changes. Here we present long-term data on the post-establishment ecology of ten species of tropical rainforest trees that span a broad life-history spectrum. The study site was upland (non-swamp) old-growth tropical wet forest at the La Selva Biological Station (N.E. Costa Rica). Focal individuals from established seedlings to mature trees were assessed annually, with an emphasis on accuracy and long-term consistency of the observations. The annual time-step, rare for longterm studies in tropical rainforest, captures the typically abrupt changes in forest structure and light environments, the frequent instances of major physical damage, and the trees' responses to these events and to interannual and long-term climatic variation. With the completion of the study in 2016, the data for survivorship, growth, and microsite conditions span 4499 individuals and 34 years. The first ten years of these data were published as an Ecology/Ecological Archives data paper in 2000 (Clark and Clark 2000), with two subsequent update publications (Clark and Clark 2006, 2012). This final update adds the final six years of observations, digitized field comments, and histories of points of measurement on the trees. The metadata now include the scanned original field data-sheets for the entire study and a narrative detailing the annual qa/qc of the data. The data set is unique for its scope (years of continuous annual measurements, number of monitored individuals), the in-depth documentation, and the unrestricted data access. The data have been used to study life history patterns, tree ecology through ontogeny, and effects on tree performance from interannual and long-term climatic and atmospheric change. They have also contributed to numerous remote-sensing studies.
Data from: Leaf drought tolerance cannot be inferred from classic leaf traits in a tropical rainforest
<ol> <li>Plants are enormously diverse in their traits and ecological adaptation, even within given ecosystems, such as tropical rainforests. Accounting for this diversity in vegetation models poses serious challenges. Global plant functional trait databases have highlighted general trait correlations across species that have considerably advanced this research program. However, it remains unclear whether trait correlations found globally hold within communities, and whether they extend to drought tolerance traits.</li> <li>For 134 individual plants spanning a range of sizes and life forms (tree, liana, understory species) within an Amazonian forest, we measured leaf drought tolerance (leaf water potential at turgor loss point, π<sub>tlp</sub>), together with 17 leaf traits related to various functions, including leaf economics traits and nutrient composition (leaf mass per area, LMA; and concentrations of C, N, P, K, Ca, and Mg per leaf mass and area), leaf area, water use efficiency (carbon isotope ratio), and time-integrated stomatal conductance and carbon assimilation rate per leaf mass and area. We tested trait coordination and the ability to estimate π<sub>tlp</sub> from the other traits through model selection. Performance and transferability of the best predictive model were assessed through cross-validation.</li> <li>π<sub>tlp</sub> was positively correlated with leaf area, and with N, P and K concentrations per leaf mass, but not with LMA or any other studied trait. Five axes were needed to account for >80% of trait variation, but only three of them explained more variance than expected at random. The best model explained only 30% of the variation in π<sub>tlp</sub>, and out-sample predictive performance was variable across life forms or canopy strata, suggesting a limited transferability of the model.</li> <li> <i>Synthesis</i>. We found a weak correlation among leaf drought tolerance and other leaf traits within a forest community. We conclude that higher trait dimensionality than assumed under the leaf economics spectrum may operate among leaves within plant communities, with important implications for species coexistence and responses to changing environmental conditions, and also for the representation of community diversity in vegetation models.</li> </ol>
CO and CO2 mixing ratios and flux measurements from the Amazon tropical rainforest
<p>CO and CO2 mixing ratio and flux measurements from the Amazon tropical rainforest</p><p>This dataset belongs to the manuscript 'The emission of CO from tropical rain forest soils', submitted to the journal Biogeosciences in December 2023.</p><p>More details on this dataset can be found in this manuscript:</p><p>https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2746/egusphere-2023-2746.pdf</p><p> For questions, please reach out to Hella van Asperen: hasperen@bgc.mpg-jena.de</p><p>########################################</p><p>Plateau tower CO and CO2 mixing ratio measurements</p><p>Plateau tower CO and CO2 mixing ratio measurements took place in a dry season campaign (28 Sep- 7 Oct 2020) and a wet season campaign (11-18 May 2021) at the K34 tower at field site ZF2 in the Amazon rain forest (-2.60898, -60.209106). Due to a problem in the beginning of the dry season campaign, the measurements at the tower were continued until outside the campaign period, until 18 October 2020. Measurements were performed by a Spectronus FTIR analyzer. Concentrations were measured at 3 heights (5,15 and 36m) every half hour. Canopy height is ~28m.</p><p>########################################</p><p>Valley CO and CO2 mixing ratio measurements</p><p>Valley CO and CO2 mixing ratio measurements took place in a dry season campaign (28 Sep- 7 Oct 2020) and a wet season campaign (11-18 May 2021) at a valley close to the K34 tower at field site ZF2 (-2.600026, -60.217079). Since no electricity was available, automatic battery-driven bag sampling was performed during the night at 3h time intervals, with 4 measurements per night from a 1m height inlet (~18:00, ~21:00, ~0:00, ~3:00). Bag samples were measured the following morning by a Spectronus FTIR-analyzer. </p><p>########################################</p><p>Plateau and valley chamber CO and CO2 fluxes</p><p>Flux chamber measurements were performed over soil and litter together on the plateau and in the valley at field site ZF2, in a dry season campaign (28 Sep- 7 Oct 2020) and a wet season campaign (11-18 May 2021). Five soil collars were installed in the valley, and five on the plateau. Each collar was measured 3 times during each campaign week (on different days). Measurements from the same collar are indicated as (for example) V1A, V1B, V1C. After each flux chamber measurement, soil moisture and soil temperature was measured.</p>
Woody debris removal modifies carbon stocks and soil properties in a fragmented tropical rainforest
<p>We examined whether and how woody debris removal for domestic fuel affects carbon storage and soil properties in an Indian rainforest. Fuelwood removal reduced aboveground carbon stocks, increased soil bulk density, and possibly reduced soil phosphorus stocks. Equitably balancing this subtle trade-off between climate-regulating and vital, widely-utilized provisioning functions, is a challenge for tropical forest research and management.</p>
Data from: Preference for mammalian urine is higher in the canopy than on the ground in a tropical rainforest ant community in Yunnan, China
<p>Ants are among the most abundant groups of arthropods, and approximately half of all ant species are associated with forest canopies. The forest canopy environment is distinct from the understory and forest floor, and vertical stratification in environmental conditions shapes species assembly and organismal traits and behaviors across taxa in forest communities. Canopy ants are faced with a more nitrogen-limited environment compared with ground ants because of their reliance on nitrogen-poor plant and insect exudates. Despite prior work suggesting that some ant species consume mammalian urine and use symbiotic bacteria to extract nitrogen, we have little knowledge about the consumption of urine in canopy ants or the relative preference for urine between ground and canopy ants. We conducted an observational field experiment in a lowland tropical rainforest in southern China to test for vertical stratification in ant preference for sugar and urine, setting ground and canopy baited pitfall traps with the use of a canopy crane. We found distinct vertical stratification in the use of urine, with higher richness and abundance in sugar baits on the ground, and a higher abundance in urine baits in the canopy. Furthermore, the composition of captured ants differentiated according to both vertical stratum and bait type. This distinct vertical stratification of niche preference may represent an important case of niche partitioning that contributes to high ant species diversity in tropical rainforests as well as high species turnover between ground and canopy strata. The preference of canopy ants for mammalian urine also highlights the importance of interspecific interactions across highly unrelated animal taxa and emphasizes the need for a holistic understanding of biological networks to effectively conserve threatened tropical forest communities.</p>
Vertical profiles of leaf photosynthesis and leaf traits, and soil nutrients in two tropical rainforests in French Guiana before and after a three-year nitrogen and phosphorus addition experiment
<p>We provide a comprehensive dataset of vertical profiles of photosynthetic capacity and important leaf traits, including leaf N and P concentrations, from two three-year, large-scale fertilisation experiments conducted in two tropical rainforests in French Guiana. These data present a unique source of information to further improve model representations of the roles of N, P, and other leaf nutrients, in photosynthesis in tropical forests. To further facilitate the use of our data in syntheses and model studies, we provide an elaborate list of ancillary data, including important soil properties and nutrients, along with the leaf data. As environmental drivers are key to improve our understanding of carbon (C)-nutrient cycle interactions, this comprehensive dataset will aid to further enhance our understanding of how nutrient availability interacts with C uptake in tropical forests.</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.