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2,390 results for “rainforests”
Data from: Tropical biome switching: Ant communities transition from savanna to rainforest following cessation of burning
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Cold waves in the Amazon rainforest and their ecological impact
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Changes in trait covariance along an orographic moisture gradient reveal the relative importance of light- and moisture-driven trade-offs in subtropical rainforest communities
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Active restoration fosters better recovery of tropical rainforest birds than natural regeneration in degraded forest fragments
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Canopy height and epiphytic bryophytes shape fungal communities in a temperate rainforest
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Small mammals reduce distance-dependence and increase seed predation risk in tropical rainforest fragments
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Secondary Amazon rainforest partially recovers tree cavities suitable for nesting birds in 18–34 years
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Water and soil chemistry and molecular composition data of dissolved organic matter from soils in the central Amazon rainforest, 2019-2021
This dataset was created based on sampling campaigns in the central Amazon rainforest. It covers four field sites in vicinity of the Amazon Tall Tower Oberservatory project (ATTO). The field sites are comprised of pristine, old-growth rainforest with distinct forest types: terra firme forest (Plateau and Terrace sites) and white-sand forest (Campina and Campinarana sites). Freely percolating soil porewater was sampled repeatedly in soil profiles from 0 to 30 cm in the wet seasons (October to May) of 2019, 2020 and 2021. Solid soil samples were taken in vicinity to the plots in October 2017. The datasets include chemical and texture (particle size fractions) and chemical (metals, cation exchange capacities and pH) data from soil samples. Soil porewater samples were measured for pH, electrical conductivity and dissolved organic carbon (DOC) concentrations. There are some missing values for these data, particularly for DOC concentrations. Soil porewater samples were used for solid-phase extraction of dissolved organic matter (DOM). The molecular composition was measured by ultra-high resolution mass spectrometry (Orbitrap Elite MS). The detected masses were used to assign molecular formulas. The data include the assigned molecular formulas and sum-normalized intensites of all samples. This data is associated with a Ph.D. dissertation chapter (Lange, 2025) and a journal article (Lange et al., accepted).
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.
Data from: Prey abundance and leopard diet in a plantation and rainforest landscape, Anamalai Hills, Western Ghats
<p>Leopards use a wide range of habitats from natural forests to plantations in human-dominated landscapes. Within interface areas, understanding leopard ecology and diet can help in conservation management and conflict avoidance. In a fragmented rainforest and plantation landscape in southern India, we examined diet of large carnivores (with a focus on leopards) using scat analysis with DNA-based identification of predator species, and estimated relative abundance of prey species in different land uses through transect surveys. Large carnivores predominantly consumed wild prey species (98.1%) and domestic prey species contributed <2% to overall prey biomass. For leopards, four wild prey species (Indian muntjac, Indian spotted chevrotain, sambar and Indian porcupine) contributed 95.1% of prey biomass, with the rest being minor wild prey species (no livestock in identified scats). Wild prey species occurred across the landscape but varied in relative abundance by land-use type, with forest fragments supporting higher abundance of many species relative to tea and coffee plantations. As large carnivores mainly depend on wild prey and rainforest fragments act as refuges for these mammals within the tea and coffee plantations, it is important to continue to retain or restore these forest fragments.</p> <p>This dataset contains abundance data on mammals (large carnivores and their prey species), using direct and indirect sign surveys along line and belt transects, respectively, as well as data on remains of prey species in large carnivore scats. This dataset is part of a study (published paper under Related works) on leopard ecology in a landscape containing commercial plantations of tea and coffee, and rainforest fragments and protected area. These data were collected between 2008 and 2010 in Valparai plateau and Anamalai Tiger Reserve in the Western Ghats, India. The dataset contains following files:</p> <p>1) Transect_details.csv<br> 2) Transect_repeats.csv<br> 3) Mammals_Direct_signs.csv<br> 4) Mammals_Indirect_signs.csv<br> 5) Large_carnivores_Indirect_signs.csv<br> 6) Large_carnivore_Diet.csv</p> <p>More details regarding the above files can be found in ReadMe_Data_ColumnNames.txt.</p> <p><strong>Update, version 2</strong>: Data were updated on 4 May 2020. There was an error in the following file: Large_carnivore_Diet.csv. This file has been corrected and replaced in this update. All other files are correct and therefore not replaced.</p>
Forest cover and fruit crop size differentially influence frugivory of select rainforest tree species in Western Ghats, India (Part II)
<p><span><span><span><span><span><span><span><span><span><span><span>Forest fragmentation and habitat loss are major disruptors of plant–frugivore interactions, affecting seed dispersal and altering recruitment patterns of tree species dependent on vertebrate dispersers. In a heterogeneous production landscape (primarily tea and coffee plantations) in the southern Western Ghats, India, we <span><span>examined effects of surrounding forest cover and fruit crop size on frugivory of four rainforest bird-dispersed tree species</span></span> (<i>N</i> = 131 trees, ≥ 30 trees per species, observed for 623 h). Frugivore composition differed among the four tree species with the large-seeded <i>Canarium strictum </i>and<i> Myristica dactyloides</i> exclusively dependent on large-bodied avian frugivores, whereas, medium-seeded <i>Persea macrantha</i> and <i>Heynea trijuga </i>were predominantlyvisited by small-bodied and large-bodied avian frugivores, respectively. Using the seed-dispersal-effectiveness framework, we identified effective frugivores and examined their response to forest cover and fruit crop size. Results were idiosyncratic and governed by plant and frugivore traits. Visitations to medium-seeded <i>Persea </i>had a positive relationship with forest cover but the relationship was negative for the large-seeded <i>Myristica</i>. In addition, two of the three effective frugivores for <i>Persea </i>responded to the interactive effect of forest cover and fruit crop size<i>. </i>Frugivore visitations to <i>Hyenea</i> were not related to forest cover or fruit crop and<i> </i>there were too few visitations to <i>Canarium </i>to discern any trends<i>. </i>These results highlight the context-specific response of plant-frugivore interactions to forest cover and fruit crop size influenced by the plant and frugivore traits.</span></span></span></span></span></span></span></span></span></span></span></p>
Forest cover and fruit crop size differentially influence frugivory of select rainforest tree species in Western Ghats, India (Part I)
<p>Forest fragmentation and habitat loss are major disruptors of plant–frugivore interactions, affecting seed dispersal and altering recruitment patterns of tree species dependent on vertebrate dispersers. In a heterogeneous production landscape (primarily tea and coffee plantations) in the southern Western Ghats, India, we <span>examined effects of surrounding forest cover and fruit crop size on frugivory of four rainforest bird-dispersed tree species</span> (<i>N</i> = 131 trees, ≥ 30 trees per species, observed for 623 h). Frugivore composition differed among the four tree species with the large-seeded <i>Canarium strictum </i>and<i> Myristica dactyloides</i> exclusively dependent on large-bodied avian frugivores, whereas, medium-seeded <i>Persea macrantha</i> and <i>Heynea trijuga </i>were predominantly visited by small-bodied and large-bodied avian frugivores, respectively. Using the seed-dispersal-effectiveness framework, we identified effective frugivores and examined their response to forest cover and fruit crop size. Results were idiosyncratic and governed by plant and frugivore traits. Visitations to medium-seeded <i>Persea </i>had a positive relationship with forest cover but the relationship was negativefor the large-seeded <i>Myristica</i>. In addition, two of the three effective frugivores for <i>Persea </i>responded to the interactive effect of forest cover and fruit crop size<i>. </i>Frugivore visitations to <i>Hyenea</i> were not related to forest cover or fruit crop and<i> </i>there were too few visitations to <i>Canarium </i>to discern any trends<i>. </i>These results highlight the context-specific response of plant-frugivore interactions to forest cover and fruit crop size influenced by the plant and frugivore traits.</p>
Data from: Habitat use and seed removal by invasive rats (Rattus rattus) in disturbed and undisturbed rainforest, Puerto Rico
Despite frequent occurrences of invasive rats (Rattus spp.) on islands, their known effects on forests are limited. Where invasive rats have been studied, they generally have significant negative impacts on native plants, birds, and other animals. This study aimed to determine invasive rat distribution and effects on native plant populations via short-term seed removal trials in tropical rain forest habitats in the Luquillo Experimental Forest, Puerto Rico. To address the first objective, we used tracking tunnels (inked and baited cards inside tunnels enabling animal visitors' foot prints to be identified) placed on the ground and in the lower canopy within disturbed (treefall gaps, hurricane plots, stream edges) and undisturbed (continuous forest) habitats. We found that rats are present in all habitats tested. Secondly, we compared seed removal of four native tree species (Guarea guidonia, Buchenavia capitata, Tetragastris balsamifera, and Prestoea acuminata) between vertebrate-excluded and free-access treatments in the same disturbed and undisturbed habitats. Trail cameras were used to identify animals responsible for seed contact and removal. Black rats (R. rattus) were responsible for 65.1% of the interactions with seeds, of which 28.6% were confirmed seed removals. Two plant species had significantly more seeds removed in disturbed (gaps) than undisturbed forest. Prestoea acuminata had the lowest seed removal (9% in 10 d), whereas all other species had >30% removal. Black rats are likely influencing fates of seeds on the forest floor, and possibly forest community composition, through dispersal or predation. Further understanding of rat-plant interactions may be useful for formulating conservation strategies.
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>
Phylogenetic and ecological correlates of pollen morphological diversity in a neotropical rainforest
Morphology varies enormously across clades, and the morphology of a trait may reflect ecological function or the retention of ancestral features. We examine the tension between ecological and phylogenetic correlates of morphological diversity through a case study of pollen grains produced by angiosperms in Barro Colorado Island, Panama (BCI). Using a molecular phylogeny of 730 taxa we demonstrate a statistically significant association between morphological and genetic distance for these plants. However, the relationship is non-linear, and while close relatives share more morphological features than distant relatives, above a genetic distance of ~0.7 increasingly distant relatives are not more divergent in phenotype. The pollen grains of biotically pollinated and abiotically pollinated plants overlap in morphological space, but certain pollen morphotypes and individual morphological traits are unique to these pollination ecologies. Our data show that the pollen grains of biotically pollinated plants are significantly more morphologically diverse than those of abiotically pollinated plants.
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: Effects of restoration on tree communities and carbon storage in rainforest fragments of the Western Ghats, India
Ecological restoration is a leading strategy for reversing biodiversity losses and enhancing terrestrial carbon sequestration in degraded tropical forests. There have been few comprehensive assessments of recovery following restoration in fragmented forest landscapes, and the efficacy of active versus passive (i.e., natural regeneration) restoration remains unclear. We examined 11 indicators of forest structure, tree diversity and composition (adult and sapling), and aboveground carbon storage in 25 pairs of actively restored (AR; 7–15 yr after weed removal and mixed-native tree species planting) and naturally regenerating (NR) plots within degraded rainforest fragments, and in 17 less-disturbed benchmark (BM) rainforest plots in the Western Ghats, India. We assessed the effects of active restoration on the 11 indicators and tested the hypothesis that active restoration effects increase with isolation from contiguous and relatively intact rainforests. Active restoration significantly increased canopy cover, adult tree and sapling density, adult and sapling species density (overall and late successional), compositional similarity to benchmarks, and aboveground carbon storage, which recovered 14–82% toward BM targets relative to NR baselines. By contrast, tree height–diameter ratios and the proportion of native saplings did not recover consistently in actively restored forests. The effects of active restoration on canopy cover, species density (adult), late successional species density (adult and sapling), and species composition, but not carbon storage, increased with isolation across the fragmented landscape. Our findings show that active restoration can promote recovery of forest structure, composition, and carbon storage within 7–15 yr of restoration in degraded tropical rainforest fragments, although the benefits of active over passive restoration across fragmented landscapes would depend on indicator type and may increase with site isolation. These findings on early stages of recovery suggest that active restoration in ubiquitous fragmented landscapes of the tropics could complement passive restoration of degraded forests in less fragmented landscapes, and protection of intact forests, as a key strategy for conserving biodiversity and mitigating climate change.
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 and code for: Time of night and moonlight structure vertical space use by insectivorous bats in a Neotropical rainforest: an acoustic monitoring study
<p>Abstract</p> <p>Previous research has shown diverse vertical space use by various taxa, highlighting the importance of forest canopy. Yet, we often fail to explore how this three-dimensional space use changes over time. Here we use canopy tower systems in French Guiana to monitor neotropical bat activity above and below the forest canopy throughout nine nights in the wet season. We show that different bats use both canopy and understory space differently, and that this can change throughout the night. We find that bats are overall more active in the canopy, but multiple species/acoustic complexes are more active in the understory. We also find that species that do not seem to prefer understory or canopy, when data are aggregated by night, do show temporally changing preferences in hourly activity. This work highlights the need to consider temporal axes in studies of space use, both throughout daily cycles and across seasons.</p>
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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.