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7,883 results for “Tropic”
Data from: Multi-population seedling and soil transplants show possible responses of a common tropical montane tree species (Weinmannia bangii) to climate change
<p>A possible response of many plant species to global warming is migration to higher elevations. However, these migrations may not be required if species can tolerate higher temperatures, or may be prevented if there are other factors such as changes in soil conditions that make upslope areas unsuitable.</p> <p>We used a set of 3-year field transplant experiments in the remote Peruvian Andes to simulate two possible responses of an abundant tropical montane cloudforest tree species (Weinmania bangii) to global warming: (1) "upward migration", in which case seedlings of W. bangii's were grown at their current elevation/temperature but in soils transplanted from higher elevations; and (2) "migration failure", in which case seedlings were transplanted downslope along with their home soils into areas that are 1°C or 2°C warmer. We conducted separate experiments with populations from the upper/leading edge, middle and lower/trailing edges of W. bangii's elevational/thermal range to assess the influence of local adaptation on responses to changes in temperature or soil.</p> <p>We found that seedling survival and growth were not affected by changes in soil conditions, regardless of the origin population. However, seedling survival decreased with temperature. A simulated warming of 1°C caused a significant reduction in the survival of seedlings transplanted from the mid-range population, and 2°C warming caused a severe decrease in the survival of seedlings transplanted from both the mid-range and bottom-edge populations.</p> <p>Synthesis. Our findings reveal that rising temperatures are a serious threat to plants, especially in populations growing in the hotter portion of their species' range. At least in the case of W. bangii, novel soil conditions will not limit the establishment or growth of seedlings at higher elevations. As such, decreases in the survivorship at lower elevations may be offset through upward migrations as temperatures continue to increase.</p>
Characterizing the nectar microbiome of the non-native tropical milkweed, Asclepias curassavica, in an urban environment
<p>In increasingly urban landscapes, the loss of native pollen and nectar floral resources is impacting ecologically important pollinators. Increased urbanization has also brought about the rise of urban gardens which introduce new floral resources that may help replace those the pollinators have lost. Recently, studies have shown that the microbial communities of nectar may play an important role in plant-pollinator interactions, but these microbial communities and the floral visitors in urban environments are poorly studied. In this study we characterized the floral visitors and nectar microbial communities of <i>Ascelpias curassavica</i>, a non-native tropical milkweed commonly, in an urban environment. We found that the majority of the floral visitors to <i>A. curassavica</i> were honey bees followed closely by monarch butterflies. We also found that there were several unique visitors to each site, such as ants, wasps, solitary bees, several species of butterflies and moths, Anna's hummingbird, and the tarantula hawk wasp. Significant differences in the nectar bacterial alpha and beta diversity were found across the urban sites, although we found no significant differences among the fungal communities. We found that the differences in the bacterial communities were more likely due to the environment and floral visitors rather than physiological differences in the plants growing at the gardens. Greater understanding of the impact of urbanization on the nectar microbiome of urban floral resources and consequently their effect on plant-pollinator relationships will help to predict how these relationships will change with urbanization, and how negative impacts can be mitigated through better management of the floral composition in urban gardens.<br> </p>
Species Abundance Distributions (SADs) for local tree communities in 1-ha forest plots on 20 tropical islands in the Indo-Pacific region
<p>Species abundance distributions (SADs) characterise the distribution of individuals among species. This dataset was used to investigate the relative importance of disturbance regime (tropical cyclone regime) and island geography (the area and isolation of islands) on the shape of SADs.</p>
Datasets - Evolutionary history, not ecogeographic rules, explains size variation of tropical insects along elevational gradients
<p>One of the best-known biogeographic rules for ectotherms is the temperature-size rule, which asserts that ectotherms produce smaller adults at warmer temperatures. Although this is often true, it has become clear that there is no single process behind the pattern and many exceptions to the rule. To disentangle such complex temperature-size relationships, individual clades must be examined at ecological and evolutionary scales.</p> <p>We examined temperature-size relationships for 2106 individuals from 64 populations and 40 species of <i>Cephaloleia</i> rolled-leaf beetles (Chrysomelidae; Cassidinae)<b> </b>occurring along two tropical elevational gradientss: Barva and the Talamanca Cordillera in Costa Rica, Central America. We tested whether the temperature-size rule applied to interspecific elevational assemblages, intraspecific elevational populations, or different rearing temperatures for individual populations.</p> <p>At the interspecific scale, evolutionary history, rather than elevation, explains body size. At the intraspecific scale, only one of seven species followed the temperature-size rule across elevations. When larvae were reared at different temperatures, only one of five populations followed the temperature-size rule. Most populations grew to a fixed size regardless of temperature.</p> <p>Size in <i>Cephaloleia</i> beetles is constrained by their evolutionary history and responds to factors that rarely correlate with temperature. As temperature increases, ectotherms will not universally shrink, but determining if and why their size will change will require further investigation.</p> <p>Here we provide the following datasets used to determine effects of temperature on insect body size at population and community levels: <i>Supplement S1.</i> Body length for 2106 individuals representing 64 populations from 40 species of <i>Cephaloleia </i>rolled-leaf beetle along the Barva and Talamanca elevational gradients, Costa Rica<i>. Supplement S2.</i> Intraspecific differences in length for 798 individuals from seven <i>Cephaloleia </i>species present at multiple life zone<i>.</i><i> Supplement S3.</i> Effects of developmental temperatures on <i>Cephaloleia </i>adult size in 968 individuals from four species and five populations reared in the laboratory at temperatures between 10 and 35 °C.</p>
Effects of habitat modification on a tritrophic cascade in a lowland tropical rainforest
<b>Description: </b><p>The impact of anthropogenic disturbance of tropical rainforests on ecosystem processes is poorly understood. In this study I investigate how habitat modification in tropical rainforests may mediate a tritrophic cascade with resultant effects on herbivory, a key ecosystem process. I adopt a stepwise approach through the trophic levels, assessing the relationships between forest quality and the bird community assemblage, and corresponding impacts on predation rates and herbivory. I measured the bird community across a forest quality gradient, surveying 24 sites within a modified lowland tropical rainforest in Borneo. At each sampling location I established two treatments, one using a large (2 x 2 x 1.5m) cage designed to exclude vertebrates, and the second a control where no vertebrate exclusion was in place. I measured predation rates using dummy caterpillars, and herbivory rates on selected leaves in each treatment at all sampling locations. I used piecewise structural equation modelling to develop a path model between predictor and response variables. I established a significant pathway between increasing forest quality, increased richness of the bird community and higher vertebrate predation rates. Conversely, invertebrate predation rates declined with increasing forest quality. The effect of increasing forest quality did not mediate a trophic cascade bringing about an increase in herbivory. However, the effect of vertebrate exclusion mediated a trophic cascade and an increase in herbivory in higher forest quality, where invertebrate predation levels are lower. The results of the study therefore reflect the dampening of the tritrophic cascade across a forest quality gradient, and high functional redundancy in predatory function in forests of low quality. The study also highlights the importance of avian predatory function in forests of higher quality. A reduction in large vertebrate predators in undisturbed tropical rainforests may therefore result in cascading effects on herbivory, which may in turn have implications for primary productivity and nutrient cycling. These findings have significant implications for tropical forest conservation and management. Further research should place emphasis on addressing the effects of the loss of apex predators on key ecosystem processes.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/201"><b>The effects of habitat modification on a tritrophic cascade in a lowland tropical rainforest</b></a></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (SABC) (Research licence JKN/MBS.1000-2/2 JLD.8 (66))</li><li>Sabah Biodiversity Centre (SABC) (Research licence JKM/MBS.1000-2/2 JLD.8 (61) )</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3981222">here</a></p><p><b>Files: </b>This dataset consists of 2 files: FraserExclusionPlots_AFedit_150820.xlsx, FraserAdam_TFE_2019_SAFE_AudioFiles.zip</p><p><b>FraserExclusionPlots_AFedit_150820.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>Bird point counts</b> (described in worksheet PointCounts)</p><p>Description: Repeated bird point counts at all sites</p><p>Number of fields: 89</p><p>Number of data rows: 72</p><p>Fields: </p><ul><li><b>Visit_Code</b>: Unique site x replicate code (Field type: id)</li><li><b>Plot</b>: SAFE Project plot ID (Field type: location)</li><li><b>Visit</b>: Visit number (Field type: replicate)</li><li><b>Date</b>: Date of point count (Field type: date)</li><li><b>Time_Start</b>: Time at start of point count (Field type: time)</li><li><b>Time_Finish</b>: Time at end of point count (Field type: time)</li><li><b>Weather</b>: Observations on weather conditions (Field type: comments)</li><li><b>Ashy.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.fairy.bluebird</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.paradise.flycatcher</b>: Count of individuals (Field type: abundance)</li><li><b>Asian.red.eyed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Banded.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Banded.bay.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>Black.and.red.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Black.and.yellow.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Black.capped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Black.headed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Black.headed.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Black.naped.monarch</b>: Count of individuals (Field type: abundance)</li><li><b>Blue.eared.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Blue.headed.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Bold.striped.tit.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Bornean.banded.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Bornean.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Bronzed.drongo</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.fulvetta</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.backed.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Brown.throated.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Bushy.crested.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.backed.scimitar.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.munia</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.rumped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Chestnut.winged.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Collared.kingfisher</b>: Count of individuals (Field type: abundance)</li><li><b>Common.emerald.dove</b>: Count of individuals (Field type: abundance)</li><li><b>Cream.vented.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Crested.fireback</b>: Count of individuals (Field type: abundance)</li><li><b>Crimson.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Dark.necked.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Diards.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Dusky.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Fiery.minivet</b>: Count of individuals (Field type: abundance)</li><li><b>Fluffy.backed.tit.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Gold.whiskered.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Great.argus</b>: Count of individuals (Field type: abundance)</li><li><b>Greater.green.leafbird</b>: Count of individuals (Field type: abundance)</li><li><b>Greater.racket.tailed.drongo</b>: Count of individuals (Field type: abundance)</li><li><b>Green.broadbill</b>: Count of individuals (Field type: abundance)</li><li><b>Grey.headed.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Helmeted.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Hooded.pitta</b>: Count of individuals (Field type: abundance)</li><li><b>Lesser.green.leafbird</b>: Count of individuals (Field type: abundance)</li><li><b>Little.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Long.billed.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Malaysian.blue.flycatcher</b>: Count of individuals (Field type: abundance)</li><li><b>Moustached.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Orange.bellied.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Pied.fantail</b>: Count of individuals (Field type: abundance)</li><li><b>Plain.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Plaintive.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>Puff.backed.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Purple.naped.sunbird</b>: Count of individuals (Field type: abundance)</li><li><b>Raffless.malkoha</b>: Count of individuals (Field type: abundance)</li><li><b>Red.bearded.bee.eater</b>: Count of individuals (Field type: abundance)</li><li><b>Red.naped.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Red.throated.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Rhinoceros.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.collared.kingfisher</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.crowned.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.fronted.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.tailed.tailorbird</b>: Count of individuals (Field type: abundance)</li><li><b>Rufous.tailed.shama</b>: Count of individuals (Field type: abundance)</li><li><b>Scarlet.rumped.trogon</b>: Count of individuals (Field type: abundance)</li><li><b>Short.tailed.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Short.toed.coucal</b>: Count of individuals (Field type: abundance)</li><li><b>Slender.billed.crow</b>: Count of individuals (Field type: abundance)</li><li><b>Sooty.capped.babbler</b>: Count of individuals (Field type: abundance)</li><li><b>Spectacled.bulbul</b>: Count of individuals (Field type: abundance)</li><li><b>Spectacled.spiderhunter</b>: Count of individuals (Field type: abundance)</li><li><b>Violet.cuckoo</b>: Count of individuals (Field type: abundance)</li><li><b>White.crowned.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>White.crowned.shama</b>: Count of individuals (Field type: abundance)</li><li><b>Woodpecker.sp.</b>: Count of individuals (Field type: abundance)</li><li><b>Wreathed.hornbill</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.breasted.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.crowned.barbet</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.rumped.flowerpecker</b>: Count of individuals (Field type: abundance)</li><li><b>Yellow.vented.bulbul</b>: Count of individuals (Field type: abundance)</li></ul></li><li><p><b>Leaf herbivory</b> (described in worksheet LeafHerbivory)</p><p>Description: Within each treatment, I tagged and numbered seven leaves. I chose a variation of leaf ages within each treatment, as recommended by Coley and Barone (1996). I measured leaf area on all tagged leaves at monthly intervals, as recommended by Coley and Barone (1996) and detailed in Harrison and Banks-Leite (2019), between March and May 2019. I calculated arthropod herbivory rate using ImageJ software (Schindelin et al. 2012) to determine the percentage leaf area lost (LAL) over time.</p><p>Number of fields: 9</p><p>Number of data rows: 336</p><p>Fields: </p><ul><li><b>Site</b>: SAFE Project plot ID (Field type: location)</li><li><b>Treatment</b>: Experimental treatment: inside or outside exclusion cage? (Field type: categorical)</li><li><b>Leaf</b>: ID number for each leaf (Field type: replicate)</li><li><b>DateFirstObs</b>: Date of first leaf observation (Field type: date)</li><li><b>LeafArea</b>: Leaf area at first observation (Field type: numeric)</li><li><b>DateFinalObs</b>: Date of final leaf observation (Field type: date)</li><li><b>FinalLeafArea</b>: Leaf area at last observation (Field type: numeric)</li><li><b>LostArea</b>: Area of leaf lost to herbivory (Field type: numeric)</li><li><b>PercentLostArea</b>: Percent of leaf area lost to herbivory (Field type: numeric)</li></ul></li><li><p><b>Insect predation data</b> (described in worksheet PredationData)</p><p>Description: I assessed predation rates on invertebrates by placing five plasticine dummy caterpillars within each treatment, at each sampling location. The methods were based on those described in Howe, Lövei and Nachman (2009) Roslin et al. (2017) and Roels, Porter and Lindell (2018). I placed five fresh plasticine caterpillars at least one metre apart from each other within the treatment and recovered the caterpillars after 14 days. I quantified predation attempts on each set of caterpillars within each treatment, following guidance on visual predator identification as per Low et al. (2014).</p><p>Number of fields: 9</p><p>Number of data rows: 144</p><p>Fields: </p><ul><li><b>Visit_Code</b>: Unique site x replicate code (Field type: id)</li><li><b>Plot</b>: SAFE Project plot ID (Field type: location)</li><li><b>Visit</b>: Visit number (Field type: replicate)</li><li><b>Date</b>: Date of point count (Field type: date)</li><li><b>Treatment</b>: Experimental treatment: inside or outside exclusion cage? (Field type: categorical)</li><li><b>Invertebrate</b>: Number of plasticine invertebrate mimics attacked by invertebrate predator (Field type: numeric)</li><li><b>Mammal</b>: Number of plasticine invertebrate mimics attacked by mammalian predator (Field type: numeric)</li><li><b>Bird</b>: Number of plasticine invertebrate mimics attacked by avian predator (Field type: numeric)</li><li><b>Other</b>: Number of plasticine invertebrate mimics attacked by predator that couldn't be identified (Field type: numeric)</li></ul></li></ol><p><b>FraserAdam_TFE_2019_SAFE_AudioFiles.zip</b></p><p>Description: Audio files recorded during points counts</p><p><b>Date range: </b>2019-03-04 to 2019-05-10</p><p><b>Latitudinal extent: </b>4.6815 to 4.7435</p><p><b>Longitudinal extent: </b>117.5396 to 117.5971</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Chordata <br> -  -  -  Aves <br> -  -  -  -  Piciformes <br> -  -  -  -  -  Picidae <br> -  -  -  -  -  Ramphastidae <br> -  -  -  -  -  -  <i>Psilopogon</i> <br> -  -  -  -  -  -  -  <i>Psilopogon duvaucelii</i> <br> -  -  -  -  -  -  -  <i>Psilopogon chrysopogon</i> <br> -  -  -  -  -  -  -  <i>Psilopogon mystacophanos</i> <br> -  -  -  -  -  -  -  <i>Psilopogon henricii</i> <br> -  -  -  -  -  -  <i>Caloramphus</i> <br> -  -  -  -  -  -  -  <i>Caloramphus fuliginosus</i> <br> -  -  -  -  Coraciiformes <br> -  -  -  -  -  Alcedinidae <br> -  -  -  -  -  -  <i>Todiramphus</i> <br> -  -  -  -  -  -  -  <i>Todiramphus chloris</i> <br> -  -  -  -  -  -  <i>Actenoides</i> <br> -  -  -  -  -  -  -  <i>Actenoides concretus</i> <br> -  -  -  -  -  Meropidae <br> -  -  -  -  -  -  <i>Nyctyornis</i> <br> -  -  -  -  -  -  -  <i>Nyctyornis amictus</i> <br> -  -  -  -  Galliformes <br> -  -  -  -  -  Phasianidae <br> -  -  -  -  -  -  <i>Argusianus</i> <br> -  -  -  -  -  -  -  <i>Argusianus argus</i> <br> -  -  -  -  -  -  <i>Lophura</i> <br> -  -  -  -  -  -  -  <i>Lophura ignita</i> <br> -  -  -  -  Columbiformes <br> -  -  -  -  -  Columbidae <br> -  -  -  -  -  -  <i>Chalcophaps</i> <br> -  -  -  -  -  -  -  <i>Chalcophaps indica</i> <br> -  -  -  -  Passeriformes <br> -  -  -  -  -  Corvidae <br> -  -  -  -  -  -  <i>Corvus</i> <br> -  -  -  -  -  -  -  <i>Corvus enca</i> <br> -  -  -  -  -  Pellorneidae <br> -  -  -  -  -  -  <i>Pellorneum</i> <br> -  -  -  -  -  -  -  <i>Pellorneum capistratum</i> <br> -  -  -  -  -  -  <i>Alcippe</i> <br> -  -  -  -  -  -  -  <i>Alcippe brunneicauda</i> <br> -  -  -  -  -  -  <i>Trichastoma</i> <br> -  -  -  -  -  -  -  <i>Trichastoma malaccense</i> <br> -  -  -  -  -  -  <i>Malacopteron</i> <br> -  -  -  -  -  -  -  <i>Malacopteron magnirostre</i> <br> -  -  -  -  -  -  -  <i>Malacopteron magnum</i> <br> -  -  -  -  -  -  -  <i>Malacopteron affine</i> <br> -  -  -  -  -  Cisticolidae <br> -  -  -  -  -  -  <i>Orthotomus</i> <br> -  -  -  -  -  -  -  <i>Orthotomus ruficeps</i> <br> -  -  -  -  -  -  -  <i>Orthotomus atrogularis</i> <br> -  -  -  -  -  -  -  <i>Orthotomus sericeus</i> <br> -  -  -  -  -  Rhipiduridae <br> -  -  -  -  -  -  <i>Rhipidura</i> <br> -  -  -  -  -  -  -  <i>Rhipidura javanica</i> <br> -  -  -  -  -  Muscicapidae <br> -  -  -  -  -  -  <i>Trichixos</i> <br> -  -  -  -  -  -  -  <i>Trichixos pyrropygus</i> <br> -  -  -  -  -  -  <i>Cyornis</i> <br> -  -  -  -  -  -  -  <i>Cyornis turcosus</i> <br> -  -  -  -  -  -  <i>Copsychus</i> <br> -  -  -  -  -  -  -  <i>Copsychus stricklandii</i> <br> -  -  -  -  -  Dicaeidae <br> -  -  -  -  -  -  <i>Dicaeum</i> <br> -  -  -  -  -  -  -  <i>Dicaeum everetti</i> <br> -  -  -  -  -  -  -  <i>Dicaeum trigonostigma</i> <br> -  -  -  -  -  -  <i>Prionochilus</i> <br> -  -  -  -  -  -  -  <i>Prionochilus maculatus</i> <br> -  -  -  -  -  -  -  <i>Prionochilus xanthopygius</i> <br> -  -  -  -  -  Campephagidae <br> -  -  -  -  -  -  <i>Pericrocotus</i> <br> -  -  -  -  -  -  -  <i>Pericrocotus igneus</i> <br> -  -  -  -  -  Timaliidae <br> -  -  -  -  -  -  <i>Pomatorhinus</i> <br> -  -  -  -  -  -  -  <i>Pomatorhinus montanus</i> <br> -  -  -  -  -  -  <i>Cyanoderma</i> <br> -  -  -  -  -  -  -  <i>Cyanoderma erythropterum</i> <br> -  -  -  -  -  -  -  <i>Cyanoderma rufifrons</i> <br> -  -  -  -  -  -  <i>Stachyris</i> <br> -  -  -  -  -  -  -  <i>Stachyris maculata</i> <br> -  -  -  -  -  -  -  <i>Stachyris poliocephala</i> <br> -  -  -  -  -  -  <i>Macronus</i> <br> -  -  -  -  -  -  -  <i>Macronus ptilosus</i> <br> -  -  -  -  -  -  <i>Mixornis</i> <br> -  -  -  -  -  -  -  <i>Mixornis bornensis</i> <br> -  -  -  -  -  Eurylaimidae <br> -  -  -  -  -  -  <i>Eurylaimus</i> <br> -  -  -  -  -  -  -  <i>Eurylaimus javanicus</i> <br> -  -  -  -  -  -  -  <i>Eurylaimus ochromalus</i> <br> -  -  -  -  -  -  <i>Calyptomena</i> <br> -  -  -  -  -  -  -  <i>Calyptomena viridis</i> <br> -  -  -  -  -  -  <i>Cymbirhynchus</i> <br> -  -  -  -  -  -  -  <i>Cymbirhynchus macrorhynchos</i> <br> -  -  -  -  -  -  <i>Corydon</i> <br> -  -  -  -  -  -  -  <i>Corydon sumatranus</i> <br> -  -  -  -  -  Dicruridae <br> -  -  -  -  -  -  <i>Dicrurus</i> <br> -  -  -  -  -  -  -  <i>Dicrurus aeneus</i> <br> -  -  -  -  -  -  -  <i>Dicrurus paradiseus</i> <br> -  -  -  -  -  Estrildidae <br> -  -  -  -  -  -  <i>Lonchura</i> <br> -  -  -  -  -  -  -  <i>Lonchura atricapilla</i> <br> -  -  -  -  -  Pycnonotidae <br> -  -  -  -  -  -  <i>Pycnonotus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus brunneus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus atriceps</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus simplex</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus eutilotus</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus erythropthalmos</i> <br> -  -  -  -  -  -  -  <i>Pycnonotus goiavier</i> <br> -  -  -  -  -  Chloropseidae <br> -  -  -  -  -  -  <i>Chloropsis</i> <br> -  -  -  -  -  -  -  <i>Chloropsis sonnerati</i> <br> -  -  -  -  -  -  -  <i>Chloropsis cyanopogon</i> <br> -  -  -  -  -  Nectariniidae <br> -  -  -  -  -  -  <i>Aethopyga</i> <br> -  -  -  -  -  -  -  <i>Aethopyga siparaja</i> <br> -  -  -  -  -  -  <i>Anthreptes</i> <br> -  -  -  -  -  -  -  <i>Anthreptes malacensis</i> <br> -  -  -  -  -  -  -  <i>Anthreptes simplex</i> <br> -  -  -  -  -  -  <i>Arachnothera</i> <br> -  -  -  -  -  -  -  <i>Arachnothera everetti</i> <br> -  -  -  -  -  -  -  <i>Arachnothera longirostra</i> <br> -  -  -  -  -  -  -  <i>Arachnothera robusta</i> <br> -  -  -  -  -  -  -  <i>Arachnothera flavigaster</i> <br> -  -  -  -  -  -  <i>Kurochkinegramma</i> <br> -  -  -  -  -  -  -  <i>Kurochkinegramma hypogrammicum</i> <br> -  -  -  -  -  Irenidae <br> -  -  -  -  -  -  <i>Irena</i> <br> -  -  -  -  -  -  -  <i>Irena puella</i> <br> -  -  -  -  -  Pittidae <br> -  -  -  -  -  -  <i>Erythropitta</i> <br> -  -  -  -  -  -  -  <i>Erythropitta ussheri</i> <br> -  -  -  -  -  -  <i>Pitta</i> <br> -  -  -  -  -  -  -  <i>Pitta sordida</i> <br> -  -  -  -  -  Monarchidae <br> -  -  -  -  -  -  <i>Hypothymis</i> <br> -  -  -  -  -  -  -  <i>Hypothymis azurea</i> <br> -  -  -  -  -  -  <i>Terpsiphone</i> <br> -  -  -  -  -  -  -  <i>Terpsiphone paradisi</i> <br> -  -  -  -  Trogoniformes <br> -  -  -  -  -  Trogonidae <br> -  -  -  -  -  -  <i>Harpactes</i> <br> -  -  -  -  -  -  -  <i>Harpactes diardii</i> <br> -  -  -  -  -  -  -  <i>Harpactes kasumba</i> <br> -  -  -  -  -  -  -  <i>Harpactes duvaucelii</i> <br> -  -  -  -  Cuculiformes <br> -  -  -  -  -  Cuculidae <br> -  -  -  -  -  -  <i>Chrysococcyx</i> <br> -  -  -  -  -  -  -  <i>Chrysococcyx xanthorhynchus</i> <br> -  -  -  -  -  -  <i>Centropus</i> <br> -  -  -  -  -  -  -  <i>Centropus rectunguis</i> <br> -  -  -  -  -  -  <i>Cacomantis</i> <br> -  -  -  -  -  -  -  <i>Cacomantis sonneratii</i> <br> -  -  -  -  -  -  -  <i>Cacomantis merulinus</i> <br> -  -  -  -  -  -  <i>Rhinortha</i> <br> -  -  -  -  -  -  -  <i>Rhinortha chlorophaea</i> <br> -  -  -  -  Bucerotiformes <br> -  -  -  -  -  Bucerotidae <br> -  -  -  -  -  -  <i>Berenicornis</i> <br> -  -  -  -  -  -  -  <i>Berenicornis comatus</i> <br> -  -  -  -  -  -  <i>Anorrhinus</i> <br> -  -  -  -  -  -  -  <i>Anorrhinus galeritus</i> <br> -  -  -  -  -  -  <i>Rhyticeros</i> <br> -  -  -  -  -  -  -  <i>Rhyticeros undulatus</i> <br> -  -  -  -  -  -  <i>Buceros</i> <br> -  -  -  -  -  -  -  <i>Buceros rhinoceros</i> <br> -  -  -  -  -  -  <i>Rhinoplax</i> <br> -  -  -  -  -  -  -  <i>Rhinoplax vigil</i> <br> -  -  -  -  <i>Hydrornis</i> <br> -  -  -  -  -  <i>Hydrornis baudii</i> <br> -  -  -  -  -  <i>Hydrornis schwaneri</i> <br></div><p></p>
Range-extending tropical herbivores increase diversity, intensity and extent of herbivory functions in temperate marine ecosystems
1. Climate change is modifying species distributions around the world, forcing some species poleward, where they can alter trophic interactions. Many tropical herbivorous fishes have successfully expanded their ranges into temperate ecosystems, and while it is clear they drive increases in herbivory rates in specific localities, little is known about how they might affect the diversity of herbivory functions across large spatial scales, considering their interaction with assemblages of native herbivores in temperate habitats. 2. We assessed the spatial overlap and habitat associations of native temperate and range-expanding tropical herbivorous fishes in six sub-regions of south-western Australia to determine how incursions of tropical species may have affected the diversity, redundancy (index of uniqueness) and the 'spatial extent' (addition of functions in new areas) and 'intensity' (increasing density of functional groups) of specific herbivory functions in recipient ecosystems. 3. Tropical herbivores were more abundant in temperate ecosystems, forming schools from 40 (parrotfish) to 200 (rabbitfish) individuals strongly associated with seagrass meadows and reefs with high cover of turf algae. Overlap with temperate herbivores was highest in the northern sub-regions, forming unique assemblages, with no apparent species displacements. The addition of tropical species increased functional diversity and uniqueness (the complement of redundancy), introducing novel herbivory functions to many locations. Seagrass browsing increased in spatial extent (27%) and intensity (15 x), while seaweed browsing and grazing increased in intensity by up to 2.5 x in regions with high abundances of tropical herbivores. 4. Our results suggest that the diversity, intensity and spatial extent of different herbivory functions can change as tropical species with different habitat affinities, behaviors and diets shift their distributions poleward. Changes in functional redundancy are likely to be heterogeneous in space and might not increase initially because the diversity of herbivory functions is relatively low in some temperate marine ecosystems. However, there is the potential for greater redundancy as further tropical species arrive, their abundances increase and the spatial and functional overlap of communities rises.
Data from: Nitrogen enrichment accelerates mangrove range expansion in the temperate-tropical ecotone
Climate change and nutrient enrichment are two phenomena impacting coastal ecosystems. In coastal wetlands, mangroves in temperate-tropical ecotones are encroaching on adjacent saltmarshes, a pattern that is primarily attributed to warmer winter temperatures. Climate change is also expected to increase the vulnerability of coastal wetlands to eutrophication, and increases in nutrient availability may further mediate the rate of mangrove expansion. We investigated the consequences of nutrient enrichment on coastal wetlands in the mangrove-saltmarsh ecotone near the temperate edge of mangrove distribution along the northeast coast of Florida. We tested the hypothesis that nutrient enrichment enhances the ongoing, climate-driven expansion of mangroves into areas historically dominated by saltmarshes by increasing mangrove growth and cover, allowing them to outcompete and overgrow adjacent saltmarsh plants. We manipulated nitrogen (N) and phosphorus (P) availability and measured the effects on growth, cover, diversity, leaf traits and nutrient dynamics of Avicennia germinans. We found that A. germinans shrubs growing in the saltmarsh-mangrove ecotone in northern Florida grew taller, increased their canopies, and had higher reproductive output when enriched with N compared to control plants and P-enriched plants. Nutrient enrichment did not alter Sarcocornia perennis growth, and increased Batis maritima height but did not alter density or biomass. Nitrogen addition caused an increase in A. germinans cover and decreases in B. maritima cover and Simpson's index of diversity, suggesting that N enrichment, an ongoing phenomenon, can hasten the invasion of mangroves into saltmarshes by favoring mangrove growth and reproduction without significantly enhancing saltmarsh plant growth.
Climate and plant structure determine the spatiotemporal butterfly distribution in a tropical mountain
Mountains are among the most powerful natural gradients for testing ecological and evolutionary responses of biota to environmental influences because differences in climate and plant structure occur over short spatial scales. We describe the spatiotemporal distribution patterns and drives of fruit-feeding butterfly diversity on the mountaineous region of Serra do Cipó, Minas Gerais, Brazil. Seven elevations from 822 to 1388 m were selected for evaluating the effects of abiotic factors and vegetation characteristics on butterfly diversity. A total of 44 fruit-feeding butterfly species were recorded in a two-years study. Species richness (local and regional) of fruit-feeding butterflies decreased with increasing elevation. The interaction between temperature or humidity and precipitation influenced the abundance and β-diversity of butterflies in the altitudinal gradient, while β-diversity decreased with increasing plant richness. Butterfly richness (local and regional) and β-diversity varied with the sampling period, with fewer species in July (2012 and 2013), dry period, as expected for Neotropical insects. β-diversity in space and time was due to species replacement (turnover), indicating that butterfly composition differs throughout the mountain and over time. In summary, climate and plant richness largely influenced butterfly diversity in the altitudinal gradient. Climatic changes in conjunction with increasing anthropic impacts in mountainous regions of southeast Brazil will likely influence the community of mountaintop butterflies in Espinhaço Mountain Range.
Data from: Nest attendance by tropical and temperate passerine birds: same constancy, different strategy
1. Parental care in birds varies among species and geographic regions. Incubation behavior influences embryonic development rate and varies substantially among species. 2. We studied attendance at the nest by videoing nests or collecting data from the literature for 112 species in north temperate and lowland tropical sites, then associated patterns of incubation on- and off-bouts with species and environmental traits. 3. Songbirds nesting at low elevations incubate their eggs for an average of 74.1% (12.9 s.d., n = 60 species) of the time in temperate regions and 71.0% (12.2 s.d., n = 52 species) in tropical regions during daylight hours, and 84.3% (8.2 s.d.) and 85.3% (6.2 s.d.), respectively, of each 24-hour cycle. 4. While these attendance percentages do not differ significantly between latitudes, our data also show that lowland tropical songbirds make fewer visits to the nest and, consequently, have longer on-bouts and off-bouts during incubation. This pattern in attendance reflects a latitudinal contrast in parental care strategy, where lowland tropical birds reduce visits to the nest by increasing on- and off-bout lengths while maintaining the same proportion of time spent incubating their eggs (constancy). 5. Similar constancy across latitude suggests that tropical and temperate birds may be similarly constrained to maintain elevated egg temperatures for normal embryo growth. 6. The different attendance strategies adopted in each region may reflect differences in ambient temperature, adult foraging time, and nest predation rate. Consistently warm ambient temperatures likely allow tropical birds to take longer off-bouts, and thereby to reduce activity around the nest, compared to temperate birds.
Destructive harvest data collected from four large tropical rainforest trees in Floresta Nacional de Caxiuanã
<p>Title<br> -----</p> <p>Destructive harvest data collected from four large tropical rainforest trees in Floresta Nacional de Caxiuanã</p> <p>Authors<br> ------- </p> <p>A. Burt<br> M. Boni Vicari<br> A. C. L. da Costa<br> I. Coughlin<br> P. Meir<br> L. Rowland<br> M. Disney</p> <p>Contact<br> -------</p> <p>a.burt@ucl.ac.uk</p> <p>License<br> -------</p> <p>These data are distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC BY 4.0) - see the LICENSE file for details.</p> <p>Overview<br> --------</p> <p>We harvested four large tropical rainforest trees (diameter range: 0.6-1.2m, height range: 30-46m) in a natural closed forest stand in Floresta Nacional de Caxiuanã, Pará, Brazil (approx. coordinates in the WGS-84 datum: -1.798, -51.435 degrees), during August/October 2018.<br> The objective was to measure the green mass of each tree in its entirety, and to measure woody tissue green-to-dry mass and volume ratios, and basic/green/dry woody tissue density. <br> A complete description of the four trees, these data, and the companion terrestrial lidar data (collected pre-harvest) can be found in our paper entitled: ‘New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar’.</p> <p>Acquisition<br> -----------</p> <p>Field measurements:</p> <p>Neighbouring vegetation surrounding each tree was removed, including complete clearing of the felling area.<br> Stem diameter was measured using a circumference/diameter tape at either 1.3m above-ground, or 0.5m above-buttress.<br> Each tree was felled onto tarpaulin using a STIHL MS 650 chainsaw with a 20” bar length and 13/64” chain loop.<br> Tree height (incl. stump) was measured with a surveyor's tape measure, and GPS data were acquired from the centre of the stump using a Garmin GPSMAP 64st.<br> The stem (incl. stump) and crown were cut into manageable sections, and the mass of each section was measured via weighing using two Adam LHS 500 crane scales.<br> Mass measurements commenced immediately post-felling, requiring two, four, four and two days to complete measurement of CAX-H_T1 to CAX-H_T4 respectively.<br> Multiple discs (approx. 50mm thick) were also collected from each tree: at 1.3m and 25%, 50% and 75% the length of the stem, and up to 3x discs were taken from the mid-points of 1st, 2nd and 3rd order branches (totalling a minimum of 11 discs per tree).<br> Foliage/fruit samples were retained to confirm taxonomic identity at the Museu Paraense Emílio Goeldi, Belem, Pará, Brazil.</p> <p>Laboratory measurements:</p> <p>All discs were reduced to a set of subsamples using a consistent approach: for any particular disc, they were cut as guided by parallel chords straddling above and below the major axis, each with approximate dimensions of 150mm x 50mm x 50mm (i.e., each set included periderm, phloem, cambium, xylem and pith tissues).<br> Mass and volume measurements were made on each subsample in a green and dry state.<br> Subsamples were considered in a green state after soaking for 48 hours, and a dry state once a constant mass had been attained whilst drying in an oven at 105 degree Celsius.<br> Mass was measured using an Adam NBL4602i Nimbus Precision balance, and volume measurements were made on the same balance via Archimedes’ principle.</p> <p>Processing<br> ----------</p> <p>Dry mass was estimated from measured green mass and an estimate of whole-tree woody tissue green-to-dry mass ratio. <br> Whole-tree woody tissue green-to-dry mass ratio was estimated by weighting the mean value from subsamples in each pool (stem and crown), by the green mass in each pool.<br> This mass-weighted approach was also used for estimating whole-tree woody tissue green-to-dry volume ratio and whole-tree basic/green/dry woody tissue density. </p> <p>File and directory naming convention<br> ------------------------------------</p> <p>The four trees are identified: CAX-H_T1, CAX-H_T2, CAX-H_T3 and CAX-H_T4.<br> The various files and directories are described as follows: </p> <p>./CAXH-H/<br> ├───overview/<br> │ ├───cal_cert/ (Directory: contains balance calibration certificates)<br> │ ├───images/ (Directory: various photographs illustrating the field and laboratory measurements)<br> │ ├───sentinel-2 (Directory: contains RGB and NDVI images from Sentinel-2 data over the harvest site during the campaign dates)<br> │ ├───CAX-H.results.xlsx (File: top-level results)<br> ├───CAX-H_T1/ (Directory: tree-level directories)<br> ├───CAX-H_T2/<br> ├───CAX-H_T3/<br> ├───CAX-H_T4/<br> │ ├───fieldsheets/<br> │ │ ├───CAX-H_T4.fieldsheets.pdf (File: fieldsheets from the original campaign)<br> │ │ ├───CAX-H_T4.remeasurement.fieldsheets.pdf (File: fieldsheets from the remeasurement campaign)<br> │ ├───gps/<br> │ │ ├───CAX-H_T4.gps.txt<br> │ ├───media/ (Directory: contains various photographs and videos of the field measurements, and the discs and subsamples)<br> │ ├───CAX-H_T4.results.xlsx (File: tree-level results)</p>
Data from: Low fitness at low latitudes: wintering in the tropics increases migratory delays and mortality rates in an arctic-breeding shorebird
<p>1. Evolutionary theories of seasonal migration generally assume that the costs of longer migrations are balanced by benefits at the non-breeding destinations. 2. We tested, and rejected, the null hypothesis of equal survival and timing of spring migration for High Arctic breeding sanderling Calidris alba using six and eight winter destinations between 55° N and 25° S, respectively. 3. Annual apparent survival was considerably lower for adult birds wintering in tropical West-Africa (Mauritania: 0.74 and Ghana: 0.75) than in three European sites (0.84, 0.84 and 0.87) and in subtropical Namibia (0.85). Moreover, compared with adults, second calendar-year sanderlings in the tropics, but not in Europe, often refrained from migrating north during the first possible breeding season. During northward migration, tropical-wintering sanderlings occurred at their final staging site in Iceland 5-15 days later than birds wintering further north or south. Namibia-wintering sanderlings tracked with solar geolocators only staged in West-Africa during southward migration. 4. The low annual survival, the later age of first northward migration and the later passage through Iceland during northward migration of tropical-wintering sanderlings, in addition to the skipping of this area during northward but not southward migration by Namibia-wintering sanderlings, all suggest they face issues during the late non-breeding season in West-Africa. 5. Migrating sanderlings defy long distances but may end up in winter areas with poor fitness prospects. We suggest that ecological conditions in tropical West-Africa make the fuelling prior to northward departure problematic. </p>
Data from: Tropical forest type influences community assembly processes in arbuscular mycorrhizal fungi
Aim: Plant community assembly in tropical rainforest has been shown to be largely governed by stochastic processes, but as arbuscular mycorrhizal (AM) fungi display limited host preference, they may not follow the same stochastic assembly pattern. Here, we determined the relative importance of environmental and spatial drivers responsible for the community assembly process of AM fungi in two types of tropical rainforest (semideciduous rainforest and dense ombrophilous forests). Location: Atlantic rainforest in northeastern Brazil, South America. Taxon: Arbuscular mycorrhizal fungi (Glomeromycota). Methods: We collected root samples from eight protected areas of Atlantic forest along a 700 km transect in northeastern Brazil. We measured the relative importance of deterministic and stochastic processes by redundancy analysis (RDA) and variation partitioning in comparison with null expectations using ad hoc generated neutral communities. Furthermore, we accessed species associations from co-occurrence data, at different scales using a Bayesian approach of Hierarchical Modelling of Species Communities (HMSC). Results: Overall, the extent to which stochastic and deterministic processes affected community assembly depended on the forest type and the spatial scale. Specifically, we found that abiotic and biotic predictors of AM fungal community assemblages are related to environmental homogeneity in tropical rainforests. Main conclusions: The results of the study show that dynamics in community assembly was clearly different between the two forest types, and that the difference most likely is due to differences in responses to environmental variables.
Data From: Contrasting physiological traits of shade tolerance in Pinus and Podocarpaceae native to a tropical Vietnamese forest: Insight from an aberrant flat-leaved pine
<p>The absence of pines from tropical forests is a puzzling biogeographical oddity potentially explained by traits of shade intolerance. <i>Pinus krempfii</i>, a flat-leaved pine endemic to the Central Highlands of Vietnam, provides a notable exception as it seems to successfully compete with shade-tolerant tropical species. Here, we test the hypothesis that successful conifer performance at the juvenile stage depends on physiological traits of shade tolerance by comparing the physiological characteristics of <i>P. krempfii </i>to coexisting species from the genus <i>Pinus</i> and from the Podocarpaceae, a relatively abundant and shade tolerant conifer family found in pantropical forests. We examined leaf photosynthetic, respiratory and biochemical traits. Additionally, we compiled attainable maximum photosynthesis, maximum RuBP carboxylation (<i>Vc</i><sub>max</sub>) and maximum electron transport (<i>J</i><sub>max</sub>) values for <i>Pinus</i> and Podocarpaceae species from the literature. In our literature compilation, <i>P. krempfii </i>was intermediate between <i>Pinus</i> and Podocarpaceae in its maximum photosynthesis and its <i>Vc</i><sub>max</sub>. <i>Pinus</i> exhibited a higher <i>Vc</i><sub>max</sub> than Podocarpaceae, resulting in a less steep slope in the linear relationship between <i>J</i><sub>max</sub> and <i>Vc</i><sub>max</sub>. These results suggest that <i>Pinus </i>may be more shade intolerant than Podocarpaceae with <i>P. krempfii </i>falling between the two groups. However, in contrast, Vietnamese conifers' leaf mass per areas and biochemical traits did not highlight the same intermediate nature of <i>P. krempfii</i>. Furthermore, regardless of leaf shape or family assignation, all species demonstrated a common carbon gain efficiency. Overall, our findings highlight the importance of shade tolerance for conifer survival in tropical forests. However, they also demonstrate a diversity of shade tolerance strategies, all of which lead to the persistence of Vietnamese juvenile conifers in low-light tropical understories.</p>
Trade-offs in above and belowground biomass allocation influencing seedling growth in a tropical forest
<p>1. Plants allocate biomass to different organs in response to resource variation for maximizing performance, yet we lack a framework that adequately integrates plant responses to the simultaneous variation in above and belowground resources. Although traditionally, the optimal partition theory (OPT) has explained patterns of biomass allocation in response to a single limiting resource, it is well known that in natural communities multiple resources limit growth. We study trade-offs involved in plant biomass allocation patterns and their effects on plant growth under variable below and aboveground resources –light, soil N, and P– for seedling communities.</p> <p>2. We collected information on leaf, stem, and root mass fractions for more than 1,900 seedlings of 97 species paired with growth data and local-scale variation in abiotic resources from a tropical forest in China.</p> <p>3. We identified two trade-off axes that define the mass allocation strategies for seedlings – allocation to photosynthetic vs. non-photosynthetic tissues and allocation to roots over stems – that responded to the variation in soil P and N and light. Yet, the allocation patterns did not always follow predictions of OPT in which plants should allocate biomass to the organ that acquires the most limiting resource. Limited soil N resulted in high allocation to leaves at expense of non-photosynthetic tissues, while the opposite trend was found in response to limited soil P. Also, co-limitation in above and belowground resources (light and soil P) led to mass allocation to stems at expense of roots. Finally, we found that growth increased under high light availability and soil P for seedlings that either invested more in photosynthetic over non-photosynthetic tissues or/and that allocated mass to roots at expense of stem.</p> <p>4. Synthesis: Biomass allocation patterns to above and belowground tissues are described by two independent trade-offs that allow plants to have divergent allocation strategies (e.g., high root allocation at expense of stem or high leaf allocation at expense of allocation to non-photosynthetic tissues) and enhance growth under variable resources. Identifying the trade-offs driving biomass allocation is important to disentangle plant responses to the simultaneous variation in resources in diverse forest communities.</p>
Time of activity is a better predictor of the distribution of a tropical lizard than pure environmental temperatures
<p>Environmental temperatures influence ectotherms' physiology and capacity to perform activities necessary for survival and reproduction. Time available to perform those activities is determined by thermal tolerances and environmental temperatures. Estimates of activity time might enhance our ability to predict suitable areas for species' persistence in face of climate warming, compared to the exclusive use of environmental temperatures, without considering thermal tolerances. We compare the ability of environmental temperatures and estimates of activity time to predict the geographic distribution of a tropical lizard, <i>Tropidurus torquatus</i>. We compared 105 estimates of activity time, resulting from the combination of four methodological decisions: (1) How to estimate daily environmental temperature variation (modeling a sinusoid wave ranging from monthly minimum to maximum temperature, extrapolating from operative temperatures measured in field or using biophysical projections of microclimate)? (2) In which temperature range are animals considered active? (3) Should these ranges be determined from body temperatures obtained in laboratory or in field? and (4) Should thermoregulation simulations be included in estimations? We show that models using estimates of activity time made with the sinusoid and biophysical methods had higher predictive accuracy than those using environmental temperatures alone. Estimates made using the central 90% of temperatures measured in a thermal gradient as the temperature range for activity also ranked higher than environmental temperatures. Thermoregulation simulations did not improve model accuracy. Precipitation ranked higher than thermally related predictors. Activity time adds important information to distribution modeling and should be considered as a predictor in studies of the distribution of ectotherms. The distribution of <i>T. torquatus</i> is restricted by precipitation and by the effect of lower temperatures on their time of activty and climate warming could lead to range expansion. We provide an R package "Mapinguari" with tools to generate spatial predictors based on the processes described herein.</p>
Autopolyploidy-driven range expansion of a temperate-originated plant to pan-tropic under global change
<p>Angiosperms are believed to have emerged initially in the tropics and expanded their distribution range polewards through diverse mechanisms, for example polyploidization-driven cold-tolerance evolution. Reversed expansion from temperate to pantropic climate through a polyploidization-driven shift in heat-tolerance remains largely unknown. Here, we found autopolyploidy in relation to the global expansion of <i>Solidago canadensis</i> from its temperate-climate native range in North American to hot-summer climate in an introduced range. Our cytogeographical study of 2062 accessions from 471 locations worldwide demonstrates that ploidy levels correlates negatively with latitude and positively with average temperature. An isotherm-dependent shift of the climate niches at the threshold of 20-24ºC between geo-cytotypes can be attributed mainly to autopolyploidy-driven differentiation of heat tolerance; only polyploids and not diploids are able to complete sexual reproduction, germinate and grow in the hot-summer climate of low latitudes. Ploidy-dependent fertility appears to play a key role in the hot-summer introduced range in the northern hemisphere through both pre-adaptation and rapid post-introduction adaptive evolution of delayed flowering and improved heat-tolerance during embryo development. MaxEnt model predicts continuous expansion of this weed under global change. These results provide new insights into the mechanisms governing autopolyploidy-driven backward range-expansion of plant species from temperate origins.</p>
Nits tropicals a la fase de maduració de la vinya a la D.O. Empordà (Alt Empordà) a llarg del segle XXI a l'escenari de canvi climàtic RCP8.5 (format TIFF)
<p>Distribució espacial del valor mitjà de nits tropicals a la fase de maduració de la vinya (indicador climàtic NT20III) a la D.O. Alt Empordà (Alt Empordà) per l’escenari de canvi climàtic intensiu RCP 8.5 projectat per a les dècades dels anys 2030, 2050, 2070 i 2090. A dalt a l’esquerra es mostra l’escenari control on es representa el valor mitjà del període 1972-2005.</p>
Nits tropicals a la fase de maduració de la vinya a la D.O. Empordà (Alt Empordà) a llarg del segle XXI a l'escenari de canvi climàtic RCP4.5 (format TIFF)
<p>Distribució espacial del valor mitjà de nits tropicals a la fase de maduració de la vinya (indicador climàtic NT20III) a la D.O. Alt Empordà (Alt Empordà) per l’escenari de canvi climàtic moderat RCP 4.5 projectat per a les dècades dels anys 2030, 2050, 2070 i 2090. A dalt a l’esquerra es mostra l’escenari control on es representa el valor mitjà del període 1972-2005.</p>
Nits tropicals a la fase de maduració de la vinya a la D.O. Empordà (Baix Empordà) a llarg del segle XXI a l'escenari de canvi climàtic RCP8.5 (format TIFF)
<p>Distribució espacial del valor mitjà de les nits tropicals durant la fase de maduració de la vinya (indicador climàtic NT20III) a la D.O. Empordà (Baix Empordà) per l’escenari de canvi climàtic intensiu RCP 8.5 projectat per a les dècades dels anys 2030, 2050, 2070 i 2090. A dalt a l’esquerra es mostra l’escenari control on es representa el valor mitjà del període 1972-2005.</p>
Nits tropicals a la fase de maduració de la vinya a la D.O. Empordà (Baix Empordà) a llarg del segle XXI a l'escenari de canvi climàtic RCP4.5 (format TIFF)
<p>Distribució espacial del valor mitjà de les nits tropicals durant la fase de maduració de la vinya (indicador climàtic NT20III) a la D.O. Empordà (Baix Empordà) per l’escenari de canvi climàtic moderat RCP 4.5 projectat per a les dècades dels anys 2030, 2050, 2070 i 2090. A dalt a l’esquerra es mostra l’escenari control on es representa el valor mitjà del període 1972-2005.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.