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Figure 44 in Seven new species of Rhynchobombyx Aurivillius, 1909 from Congolian lowland forests (Lepidoptera: Lasiocampidae)
Figure 44. Genitalia of Rh. arijakefriend, male holotype, DRC, Haut-Uele Prov., genitalia slide GU 2011-152 (RMCA).
Comparative physiology of canopy tree leaves in evergreen and deciduous forests in lowland Thailand
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High-performing plastic clones best explain the spread of yellow monkeyflower from lowland to higher elevation areas in New Zealand
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Comparative physiology of canopy tree leaves in evergreen and deciduous forests in lowland Thailand
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Data from: Occupancy patterns and upper range limits of lowland Bornean birds along an elevational gradient
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Open Lowland Environmental Monitoring Station, Black Rock Forest, NY, raw hourly data
Black Rock Forest maintains the Open Lowland real-time weather station at 129 Continental Rd, Cornwall, NY. The system was designed to measure air temperature (average, maximum, minimum), relative humidity (average, maximum, minimum), average vapor pressure, dew point temperature, photosynthetically active solar radiation, net global solar radiation, mean horizontal wind speed, mean wind direction, standard deviation of wind direction, maximum wind speed, precipitation amount, barometric pressure (average, maximum, minimum), and average soil temperature at two depths. Other sensors are used to measure snow depth, CO2 concentration, and albedo. Data are collected from the Open Lowland Station using a CR1000. Most instruments have a sample interval of 1 minute. The program records averages, minimum or maximum of those 1-minute readings every hour. Rainfall is totals for the 1 hour period.
Growth and survival of seedlings of 14 species of lowland rainforest trees planted in the La Guaria Annex (Canada Plot) of La Selva Biological Station, Costa Rica, in 1986 and measured every six months or every year until 1992 (Part 1 of 2)
During the 1960s, 1970s, and 1980s, Costa Rica’s old growth forests were being cut to clear land for cattle pastures and large-scale agriculture. Timber concessions were also growing pine, gmelina, and other non-native trees for harvesting. The Costa Rican government was developing plans for a reforestation program and for a Payment for Environmental Services program to combat forest loss. At this time there were no data available on the growth of native trees species. The TRIALS project (starting with the CANADA Plot) was designed by OTS (Organization for Tropical Studies) and the DGF (Dirección General Forestal) to measure the growth and survival of native tree seedlings planted on abandoned pasture lands at the La Selva Biological Station. Data from these seedlings formed the basis of the reforestation law and the Payments of Ecosystem Services (PES) plan and this model was replicated in many other areas of Costa Rica.
Growth and survival of seedlings of 14 species of lowland rainforest trees planted in the La Guaria Annex (Canada Plot) of La Selva Biological Station, Costa Rica, in 1986 and measured every six months or every year until 1992 (Part 2 of 2)
During the 1960s, 1970s, and 1980s, Costa Rica’s old growth forests were being cut to clear land for cattle pastures and large-scale agriculture. Timber concessions were also growing pine, gmelina, and other non-native trees for harvesting. The Costa Rican government was developing plans for a reforestation program and for a Payment for Environmental Services program to combat forest loss. At this time there were no data available on the growth of native trees species. The TRIALS project (starting with the CANADA Plot) was designed by OTS (Organization for Tropical Studies) and the DGF (Dirección General Forestal) to measure the growth and survival of native tree seedlings planted on abandoned pasture lands at the La Selva Biological Station. Data from these seedlings formed the basis of the reforestation law and the Payments of Ecosystem Services (PES) plan and this model was replicated in many other areas of Costa Rica.
Alaskan Peatland Experiment (APEX): Ammonium Uptake Experiment I - Uptake Data Collected in 2016 at Lowland Bog Sites in the Bonanza Creek Experimental Forest near Fairbanks, Alaska
This dataset contains data from an ammonium uptake experiment conducted at the APEX Beta site in the BCEF. Data includes ammonium uptake of Carex aquatilis roots from porewater spiked with (NH4)2SO4 for 4 and 8 hours after excavation from thermokarst bogs. Comparisons involve deep vs shallow roots and roots excavated from the edge and centre of thermokarst bogs.
Data from: Can light-saturated photosynthesis in lowland tropical forests be estimated by one light level?
Leaf-level net photosynthesis (An) estimates and associated photosynthetic parameters are crucial for accurately parameterizing photosynthesis models. For tropical forests such data are poorly available and collected at variable light conditions. To avoid over- or underestimation of modelled photosynthesis, it is critical to know at which photosynthetic photon flux density (PPFD) photosynthesis becomes light saturated. We studied the dependence of An on PPFD in two tropical forests in French Guiana. We estimated the light saturation range, including the lowest PPFD level at which Asat (An at light saturation) is reached, as well as the PPFD range at which Asat remained unaltered. The light saturation range was derived from photosynthetic light-response curves, and within-canopy and interspecific differences were studied. We observed wide light saturation ranges of An. Light saturation ranges differed among canopy heights, but a PPFD level of 1000 µmol/m²/s was common across all heights, except for pioneer trees species that did not reach light saturation below 2000 µmol/m²/s. A light intensity of 1000 µmol/m²/s sufficed for measuring Asat of climax species at our study sites, independent of the species or the canopy height. Because of the wide light saturation ranges, results from studies measuring Asat at higher PPFD levels (for upper canopy leaves up to 1600 µmol/m²/s) are comparable with studies measuring at 1000 µmol/m²/s.
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>
Data from: Resource acquisition strategies facilitate Gilbertiodendron dewevrei monodominance in African lowland forests
1. Tropical forests are hyperdiverse, yet extensive areas of monodominant forest occur in the tropics worldwide. Most long-lived and persistent monodominant tree species form ectomycorrhizal fungi symbioses, allowing them to obtain nutrients directly from soil organic matter. This might promote monodominance by reducing nutrient availability to co-occurring species, the majority of which form associations with arbuscular mycorrhizal fungi. 2. Gilbertiodendron dewevrei forest is the most widespread monodominant forest in tropical Africa. Its distribution appears determined in part by moisture availability, but its monodominance is not thought to be driven by its fungal partner or soil fertility. 3. Here we compare soil fertility of twenty G. dewevrei stands to mixed forest from three sites across an 8,400 km2 region of the Central African Republic and the Republic of Congo. In contrast to previous studies, we find monodominant G. dewevrei stands associated with infertile soils, as base cations (calcium, magnesium, total exchangeable bases) and extractable manganese are extremely low, and significantly lower in soils under G. dewevrei forest compared to mixed forest. Further, and consistent with ectomycorrhizal forests globally, soil carbon to nitrogen and carbon to phosphorus ratios are significantly higher in G. dewevrei stands than in mixed forest stands, providing evidence in support of direct acquisition of nitrogen and phosphorus from soil organic matter by ectomycorrhizal fungi. 4. Gilbertiodendron dewevrei recruits from the seedling bank, with its large seedlings surviving in high densities for over a decade. We tested whether light plasticity could facilitate monodominance by growing seedlings of G. dewevrei under controlled light conditions. We found that its seedlings grow well under a wide range of irradiance levels and conclude that this plasticity affords a competitive advantage. 5. Synthesis: We reframe the discussion of factors contributing to monodominance of G. dewevrei into one of resource acquisition and use efficiency. In particular, G. dewevrei is associated with moist and infertile soils and competes well under a variety of light conditions. Our data is consistent with a model where root associations with ectomycorrhizal fungi drive monodominance through the direct acquisition of nutrients from soil organic matter, promoting nutrient limitation of co-occurring species.
The biotic interactions hypothesis partially explains bird species turnover along a lowland Neotropical precipitation gradient
<p><span><span><span><span><span><span><span><span><span><span><span><b>Aim</b></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>We evaluated the influence of climate in determining bird communities along precipitation gradients. We argue that mechanisms responsible for community turnover along precipitation gradients are similar to mechanisms operating along temperature and latitudinal gradients. We test the hypothesis that environmental conditions affect community composition in dry forests, whereas biotic interactions affect community composition in wet forests.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Location</b></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Low-elevation forests along a precipitation gradient in Colombia where precipitation ranges from 700 – 4000 mm annually but neither temperature or elevation change.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Time period</b></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Present day</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Major Taxa Studied</b></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Tropical Forest Birds.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Methods</b></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>We performed 291 bird counts in nine study areas across the ~3000 mm range of variation in precipitation. In each locality we obtained climatic characteristics, and a phylogenetic, morphological and physiological proxy data set to test predictions about the evolutionary relationships and distribution of traits in each community. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Results</b></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>Bird communities changed abruptly along the precipitation gradient and could be divided into dry and wet forest communities. Analyses of phylogenetic relationships, trait space, and observations at nests suggested that environmental filtering is more important in dry forest, especially for breeding. In contrast, we found little evidence that competition was more important in wet forest. Nest predation or competition for nest space, however, may be more critical in wetter forests.</span></span></span></span></span></span></span></span></span></span></span></p> <p class="author"><span><span><span><span><span><span><span><span><span><span><span><b>Conclusions</b></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>The two distinct bird communities we documented suggest that lowland precipitation gradients, where temperature is constant can be as important as temperature gradients in generating high beta diversity. We conclude that the breeding process in bird communities might be crucial for determining community assembly along environmental gradients. Given that recent population declines in tropical birds have been attributed to changes in precipitation, by understanding the mechanisms underlying community assembly along precipitation gradients our study may improve our ability to understand those declines and predict the effects of climate change on neotropical avifauna.</span></span></span></span></span></span></span></span></span></span></span></p>
Supplementary Information for "Resolution and the Detection of Cultural Dispersals: development and application of spatiotemporal methods in Lowland South America"
<p>Data and code to reproduce the analyses in "Resolution and the Detection of Cultural Dispersals: development and application of spatiotemporal methods in Lowland South America"</p> <p> </p> <p><strong>Abstract</strong></p> <p>Inferring episodes of expansion, admixture, diffusion, and/or migration in prehistory is at present undergoing a resurgence in macro-scale archaeological interpretation. In parallel to this renewed popularity, expanding access to computational tools and datasets has seen the use of aggregated radiocarbon datasets for the study of dispersals also increasing. This paper advocates for developing reflexive practice in the application of radiocarbon dates to prehistoric dispersals, by reflecting on the quality and qualities of the underlying data, particularly chronometric uncertainty, and framing dispersals explicitly in terms of hypothesis testing. This paper draws on cultural expansions within South America and employs two emblematic examples, the Arauquinoid and Tupiguarani traditions, to develop an analytical solution that not only incorporates chronometric uncertainty in bivariate regression but, importantly, tests whether the datasets provide statistically significant evidence for a dispersal process. The analysis, which the paper provides the means to replicate, identifies fundamental issues with resolution and data quality that impede identification of pre-Columbian cultural dispersals through simple spatial gradients of radiocarbon data. The results suggest that reflexivity must be fed back into theoretical frameworks of prehistoric mobility for the study of dispersals, in turn informing the construction of more critical statistical null models. As a first step, alternative models of cultural expansion should be formally considered alongside demographic models.Inferring episodes of expansion, admixture, diffusion, and/or migration in prehistory is at present undergoing a resurgence in macro-scale archaeological interpretation. In parallel to this renewed popularity, expanding access to computational tools and datasets has seen the use of aggregated radiocarbon datasets for the study of dispersals also increasing. This paper advocates for developing reflexive practice in the application of radiocarbon dates to prehistoric dispersals, by reflecting on the quality and qualities of the underlying data, particularly chronometric uncertainty, and framing dispersals explicitly in terms of hypothesis testing. This paper draws on cultural expansions within South America and employs two emblematic examples, the Arauquinoid and Tupiguarani traditions, to develop an analytical solution that not only incorporates chronometric uncertainty in bivariate regression but, importantly, tests whether the datasets provide statistically significant evidence for a dispersal process. The analysis, which the paper provides the means to replicate, identifies fundamental issues with resolution and data quality that impede identification of pre-Columbian cultural dispersals through simple spatial gradients of radiocarbon data. The results suggest that reflexivity must be fed back into theoretical frameworks of prehistoric mobility for the study of dispersals, in turn informing the construction of more critical statistical null models. As a first step, alternative models of cultural expansion should be formally considered alongside demographic models.</p>
Closely related tree species support distinct communities of seed-associated fungi in a lowland tropical forest
<p>Previous theoretical work has highlighted the potential for natural enemies to mediate the coexistence of species with similar life-histories via density-dependent effects on survivorship. For plant pathogens to play this role, they must differ in their ability to infect or induce disease in different host plant species. In tropical forests characterized by high diversity, these effects must extend to phylogenetically closely related species pairs. Mortality at the seed and seedling stage strongly influences the abundance and distribution of tropical tree species, but the host preferences and spatial distributions of fungi are rarely determined.</p> <p>We examined how host species identity, relatedness, and seed viability influence the composition of fungal communities associated with seeds of four co-occurring pioneer trees (<em>Cecropia insignis</em>, <em>C. longipes</em>, <em>C. peltata</em>, and <em>Jacaranda copaia</em>). Seeds were buried in mesh bags in five common gardens in the understory of a lowland tropical forest in Panama and retrieved at intervals from 1-30 months. A subset of the seeds in each bag was used to determine germination success. One half of each remaining seed was tested for viability; the other half was used to culture and identify seed-infecting fungi.</p> <p>Seeds were infected by fungi after burial. Although fungal communities differed in viable vs. dead seeds, and across burial locations, community composition primarily varied as a function of plant species identity (30.7% of variation in community composition vs. 4.5% for viability and location together), even for congeneric <em>Cecropia</em> species. Phylogenetic reconstruction showed that relatedness of fungi mostly reflected differences between <em>Jacaranda</em> (Bignoniaceae) and <em>Cecropia</em> (Urticaceae).</p> <p>Although the proportion of germinable seeds decreased gradually over time for all species, intraspecific variation in survival was high at the same location (e.g., ranging from 0-100% for <em>C. peltata</em>) suggesting variable exposure or susceptibility to seed pathogens.</p> <p>Synthesis: Our study provides evidence under field conditions that congeneric tree species with similar life-history differ markedly in seed-associated fungal communities when exposed to the same soilborne fungi. This is a critical first step supporting pathogen mediated coexistence of closely related tree species.</p>
Data from: Environmental controls on canopy foliar N distributions in a neotropical lowland forest
Distributions of foliar nutrients across forest canopies can give insight into their plant functional diversity and improve our understanding of biogeochemical cycling. We used airborne remote sensing and Partial Least Squares Regression (PLSR) to quantify canopy foliar nitrogen (N) across ~164 km2 of wet lowland tropical forest in the Osa Peninsula, Costa Rica. We determined the relative influence of climate and topography on the observed patterns of canopy foliar N using a gradient boosting model (GBM) technique. At a local scale, where climate and substrate where constant, we explored the influence of slope position on canopy N by quantifying canopy N on remnant terraces, their adjacent slopes and knife edged ridges. In addition, we climbed and sampled 540 trees and analyzed foliar N in order to quantify the role of species identity (phylogeny) and environmental factors in predicting canopy N. Observed canopy N heterogeneity reflected environmental factors working at multiple spatial scales. Across the larger landscape, elevation and precipitation had the highest relative influence on predicting canopy foliar N (30 and 24%), followed by soils (15%), site exposure (9%), compound topographic index (8%), substrate (6%), and landscape dissection (6%). Phylogeny explained ~75% of the variation in the filed collected foliar N data, suggesting that phylogeny largely underpins the response to the environmental factors. Taken together, these data suggest that a large fraction of the variance in canopy N across the landscape is proximately driven by species composition, though ultimately this is likely a response to abiotic factors such as climate and topography. Future work should focus on the mechanisms and feedbacks involved, and how shifts in climate may translate to changes in forest function.
Data from: Defaunation increases the spatial clustering of lowland Western Amazonian tree communities
1.Declines of large vertebrates in tropical forests may reduce dispersal of tree species that rely on them, and the resulting undispersed seedlings might suffer increased distance- and density- dependent mortality. Consequently, extirpation of large vertebrates may alter the composition and spatial structure of plant communities and impair ecosystem functions like carbon storage. 2.We analysed spatial patterns of tree recruitment within six forest plots along a defaunation gradient in western Amazonia. We divided recruits into two size cohorts ("saplings", ≥1 m tall and <1 cm diameter at breast height [dbh], and juveniles, 1 – 2 cm dbh) and examined the spatial organization of conspecific recruits within each cohort (within-cohort) and around conspecific reproductive-sized trees (between-cohort). We used replicated spatial point pattern analysis to quantify relationships between recruit clustering and cohort, defaunation intensity, each tree species' reliance on hunted dispersers and the interactions among these three covariates. 3.Within-cohort clustering of conspecific saplings increased with reliance of tree species on hunted dispersers and this trend strengthened significantly as defaunation increased, probably because of reduced dispersal. 4.Within-cohort clustering of conspecifics declined from saplings to juveniles, suggesting density-dependent mortality of saplings. However, the positive relationship between sapling clustering and defaunation did not lead to greater reductions in within-cohort clustering during the sapling-juvenile transition, suggesting that higher conspecific densities did not translate into increased mortality. Instead, the increased spatial clustering associated with defaunation was retained for juvenile recruits. 5.Between-cohort clustering was unrelated to defaunation and did not change during the sapling – juvenile transition. 6.Synthesis: Defaunation increased spatial aggregation of saplings of tree species reliant on hunted dispersers. The increase in sapling clustering did not increase density-dependent thinning, and persisted into older recruit cohorts, suggesting that hunting may initiate long-term spatial reorganisation of Amazonian tree communities. The lack of increased density-dependent thinning indicates that reduced dispersal did not increase mortality of large-vertebrate dispersed tree species that contribute disproportionately to forest biomass. We therefore caution against the fait accompli acceptance of the prediction by recent modelling studies that overhunting will precipitate a collapse in carbon sequestration by tropical forests.
Data from: Fire catalyzed rapid ecological change in lowland coniferous forests of the Pacific Northwest over the past 14,000 years
Disturbance can catalyze rapid ecological change by causing widespread mortality and initiating successional pathways, and during times of climate change, disturbance may contribute to ecosystem state changes by initiating a new successional pathway. In the Pacific Northwest of North America (PNW), disturbance by wildfires strongly shapes the composition and structure of lowland forests, but understanding the role of fire over periods of climate change is challenging, because fire-return intervals are long (e.g., millennia) and the coniferous trees dominating these forests can live for many centuries. We developed stand-scale paleorecords of vegetation and fire that span nearly the past 14,000 yr to study how fire was associated with state changes and rapid dynamics in forest vegetation at the stand scale (1–3 ha). We studied forest history with sediment cores from small hollow sites in the Marckworth State Forest, located ~1 km apart in the Tsuga heterophylla Zone in the Puget Lowland ecoregion of western Washington, USA. The median rate of change in pollen/spore assemblages was similar between sites (0.12 and 0.14% per year), but at both sites, rates of change increased significantly following fire events (ranging up to 1% per year, with a median of 0.28 and 0.38%, P < 0.003). During times of low climate velocity, forest composition was resilient to fires, which initiated successional pathways leading back to the dominant vegetation type. In contrast, during times of high climate variability and velocity (e.g., the early Holocene) forests were not resilient to fires, which triggered large-scale state changes. These records provide clear evidence that disturbance, in the form of an individual fire event, can be an important catalyst for rapid state changes, accelerating vegetation shifts in response to large-scale climate change.
Data from: Flooding and soil composition determine beta-diversity of lowland forests in Northern South America
Beta diversity may be determined by dispersal limitation, environment and phylogeographic history. Our objective was to advance the understanding of plant species turnover in rainforests in Northern South America and determine which factors are affecting species beta-diversity. We evaluated the relative effect of environmental variables (i.e. soil, climate, fragmentation and flooding frequency) and dispersal limitation (i.e. geographical distance and resistance distance due mountain barriers) on tree beta diversity in 32 1-ha lowland forest plots. We found that tree species turnover was better explained by environmental distance than by geographic distance. Although, soil conditions and flooding regime were good predictors of tree species composition, almost half of the variance remained unexplained. In our study system, the Eastern Andean ridge had no significant effect on plant beta diversity, probably because of its young age in relation to the phylogeny. Our results provide support for the importance of environmental factors and suggests a more restricted role of dispersal limitation. Therefore, we advise that conservation strategies of lowland trees should consider specific forest types (e.g. seasonally flooded vs. terra firme, as well as piedmont vs. central Amazonian forests).
Data from: Lowland tapirs facilitate seed dispersal in degraded Amazonian forests
The forests of southeastern Amazonia are highly threatened by disturbances such as fragmentation, understory fires and extreme climatic events. Large-bodied frugivores such as the lowland tapir (Tapirus terrestris) have the potential to offset this process, supporting natural forest regeneration by dispersing a variety of seeds over long distances to disturbed forests. However, we know little about their effectiveness as seed dispersers in degraded forest landscapes. Here, we investigate the seed dispersal function of lowland tapirs in Amazonian forests subject to a range of human (fire, fragmentation) and natural (extreme droughts, windstorms) disturbances, using a combination of field observations, camera traps, and Light Detection and Ranging (LiDAR) data. Tapirs travel and defecate more often in degraded forests, dispersing much more seeds in these areas [9,822 seeds per ha/yr (CI95% = 9,106; 11,838)] than in undisturbed forests [2,950 seeds per ha/yr (CI95% = 2,961; 3,771)]. By effectively dispersing seeds across disturbed forests, tapirs may contribute to natural forest regeneration – the cheapest and usually the most feasible way to achieve large-scale restoration of tropical forests. Through the dispersal of large-seeded species that eventually become large trees, such frugivores also contribute indirectly to maintaining forest carbon stocks. These functions may be critical in helping tropical countries to achieve their goals to maintain and restore biodiversity and its ecosystem services. Ultimately, preserving these animals along with their habitats may help in the process of natural recovery of degraded forests throughout the tropics.
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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.