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5,828 results for “Traits”
A trait-based framework for predicting foodborne pathogen risk from wild birds
<p>Recent foodborne illness outbreaks have heightened pressures on growers to deter wildlife from farms, jeopardizing conservation efforts. However, it remains unclear which species, particularly birds, pose the greatest risk to food safety. Using >11,000 pathogen tests and 1,565 bird surveys covering 139 bird species from across the western U.S.A., we examined the importance of 11 traits in mediating wild bird risk to food safety. We tested whether traits associated with pathogen exposure (<i>e.g</i>., habitat associations, movement, and foraging strategy) and pace-of-life (clutch size and generation length) mediated foodborne pathogen prevalence and proclivities to enter farm fields and defecate on crops. <i>Campylobacter </i>spp. were the most prevalent enteric pathogen (8.0%), while <i>Salmonella</i> and Shiga-toxin producing <i>E. coli </i>(STEC) were rare (0.46% and 0.22% prevalence, respectively). We found that several traits related to pathogen exposure predicted pathogen prevalence. Specifically, <i>Campylobacter </i>and STEC-associated virulence genes were more often detected in species associated with cattle feedlots and bird feeders, respectively. <i>Campylobacter </i>was also more prevalent in species that consumed plants and had longer generation lengths. We found that species associated with feedlots were more likely to enter fields and defecate on crops. Our results indicated that canopy-foraging insectivores were less likely to deposit foodborne pathogens on crops, suggesting growers may be able to promote pest-eating birds and birds of conservation concern (<i>e.g.</i>, via nest boxes) without necessarily compromising food safety. As such, promoting insectivorous birds may represent a win-win-win for bird conservation, crop production, and food safety. Collectively, our results suggest that separating crop production from livestock farming may be the best way to lower food safety risks from birds. More broadly, our trait-based framework suggests a path forward for co-managing wildlife conservation and food safety risks in farmland by providing a strategy for holistically evaluating the food safety risks of wild animals, including under-studied species.</p>
Rapid adaptive evolution to drought in a subset of plant traits in a large-scale climate change experiment
<p>Rapid evolution of traits and of plasticity may enable adaptation to climate change, yet solid experimental evidence under natural conditions is scarce. Here, we imposed rainfall manipulations (+30%, control, -30%) for ten years on entire natural plant communities in two Eastern Mediterranean sites. Additional sites along a natural rainfall gradient and selection analyses in a greenhouse assessed whether potential responses were adaptive. In both sites, our annual target species <i>Biscutella didyma</i> consistently evolved earlier phenology and higher reproductive allocation under drought. Multiple arguments suggest that this response was adaptive: it aligned with theory, corresponding trait shifts along the natural rainfall gradient, and selection analyses under differential watering in the greenhouse. However, another seven candidate traits did not evolve, and there was little support for evolution of plasticity. Our results provide compelling evidence for rapid adaptive evolution under climate change. Yet, several non-evolving traits may indicate potential constraints to full adaptation.</p>
Traits data of exotic species in four tropical botanic gardens and adjacent natural forests
<p>The establishment of new botanic gardens in tropical regions highlights a need for weed risk assessment tools suitable for tropical ecosystems. The relevance of plant traits for invasion into tropical rainforests has not been well studied. </p> <p>Working in and around four botanic gardens in Indonesia where 600 exotic species have been planted, we estimated the effect of four plant traits and time since species were introduced on: a) naturalization probability of exotic species; b) the abundance (density) of naturalized species in adjacent native tropical rainforests; and c) the distance that naturalized exotics have spread from the botanic gardens. </p> <p>We found that specific leaf area (SLA) strongly differentiated 23 naturalized from 78 non-naturalized exotic species (randomly selected from 577 non-naturalized species) in our study. These trends may indicate that exotics with high SLA benefit from at least two factors when establishing in tropical forests: high growth rates and occupation of forest gaps. Exotic species that were present in the gardens for over 30 years and those with small seeds also had higher probabilities of becoming naturalized, indicating that plants can invade the understorey of closed canopy tropical rainforests, especially when invading species are shade-tolerant and have sufficient time to establish. On average, exotic species that were not animal dispersed spread 78 m further into the forests than animal-dispersed species. We did not detect relationships between the measured traits and estimated density of naturalized exotics in the adjacent forests.</p> <p><i><span>Synthesis</span></i>: Traits were able to differentiate exotic species that naturalized from botanic gardens from those that did not; this is promising for developing trait-based risk assessment in the tropics. We suggest tropical botanic gardens avoid planting exotic species with fast carbon capture strategies and those that are shade tolerant, to limit the risk of invasion and spread into adjacent native forests.</p>
Bud traits and post-fire responses of Cerrado woody species, Southeastern Brazil
<p>1) Species growing in fire-prone savannas usually persist by resprouting from their buds. In this study, we evaluated how various persistence traits allow bud protection for improved survival in fire-prone ecosystems.</p> <p>2) Using an integrative morphological and macroanatomical approach, we analyzed how woody plants protect their buds. We tested bud protection at the community level and evaluated: a) how bud protection changes along a fire frequency gradient, b) if it differs between shrubs and trees and c) whether the level of bud protection is related to post-fire responses of 28 woody savanna species.</p> <p>3) A mix of traits involving bud protection may enable woody species persistence in fire-prone ecosystems. Savanna species better protected their buds than forest species by developing bark and trichomes that allowed resprouting after fire. Regarding growth forms, shrub species capable of resprouting aboveground had their buds better protected than trees.</p> <p>4) Bud protection is not only linked with their position to the bark, but also with the presence of trichomes. Profuse trichomes covering buds were related to savanna species. Some species with no bud protection by bark but with trichomes covering their buds were able to resprout after fire. The presence of accessory buds is also a trait more related to savannas, possibly influencing the resprouting after fire as they are better protected and increase the bud bank. Finally, different persistence traits interact with one another to better protect the buds, requiring a detailed screening of the traits to assess species responses to fire.</p> <p>5) Synthesis. During fire, species have their aerial biomass consumed by the flames. To be able to resprout new branches and persist in the environment, they must have well-protected buds. In this study, we evaluated different ways that woody species protect their buds and related them with their resprouting strategy after fire. We investigated the protection by the bark, presence of trichomes and accessory buds. By studying the woody community in a gradient of savannas and forests we found that buds can be protected by bark, trichomes, or soil. Species can present a mix of these traits and strategies, which enhances their resprouting after fire.</p>
Colorful traits in female birds relate to individual condition, reproductive performance, and male mate preferences: A meta-analytic approach dataset
<p>Colorful traits in females are suggested to have evolved and be maintained by sexual selection. Although several studies have evaluated this idea, support is still equivocal. <span><span>Evidence has been compiled in reviews, and a handful of quantitative synthesis have explored evidence of the link between condition and specific color traits in males and females. However, understanding the potential function of females' colorful traits in sexual communication has not been the primary focus of any of those previous studies</span></span><span>. </span>Here, using a meta-analytic approach, we find that evidence from empirical studies in birds supports the idea that colorful female ornaments are positively associated with residual mass and immune response, clutch size, and male-mate preferences. Hence, colorful traits in female birds likely evolved and are maintained by sexual selection.</p>
Data from: Match and mismatch: integrating consumptive effects of predators, prey traits, and habitat selection in colonizing aquatic insects
<p>Predators are a particularly critical component of habitat quality, as they affect survival, morphology, behavior, population size, and community structure through both consumptive and non-consumptive effects. Non-consumptive effects can often exceed consumptive effects, but their relative importance is undetermined in many systems. Our objective was to determine the consumptive and non-consumptive effects of a predaceous aquatic insect, <em>Notonecta irrorata</em>, on colonizing aquatic beetles. We tested how <em>N. irrorata </em>affected survival and habitat selection of colonizing aquatic beetles, how beetle traits contributed to their vulnerability to predation by <em>N. irrorata,</em> and how combined consumptive and non-consumptive effects affected populations and community structure. Predation vulnerabilities ranged from 0–95% mortality, with size, swimming, and exoskeleton traits generating species-specific vulnerabilities. Habitat selection ranged from predator avoidance to preferentially colonizing predator patches. Attraction of Dytiscidae to <em>N. irrorata</em> may be a natural ecological trap given similar cues produced by these taxa. Hence, species-specific habitat selection by prey can be either predator-avoidance responses that reduce consumptive effects, or responses that magnify predator effects. <em>Notonecta irrorata</em> had both strong consumptive and non-consumptive effects on populations and communities, while combined effects predicted even more distinct communities and populations across patches with or without predators. Our results illustrate that an aquatic invertebrate predator can have functionally-unique consumptive effects on prey, attracting and repelling prey, while prey have functionally-unique responses to predators. Determining species-specific consumptive and non-consumptive effects is important to understand patterns of species diversity across landscapes.</p>
FIGURE 1 in The Impact Of Cucumber Nitrogen Nutrition On Life History Traits Of Tetranychus Urticae (Koch) (Acari: Tetranychidae)
FIGURE 1: Age specific survival rate (lx) and fecundity (mx) of Tetranychus urticae on four nitrogen treatments
FIGURE 4 in Habitat Use, Feeding And Reproductive Traits Of Rocky-Shore Intertidal Mites From Bermuda (Oribatida: Fortuyniidae And Selenoribatidae)
FIGURE 4: Chronological development of egg stage of Carinozetes bermudensis. Egg attached to a grain of sand. Arrow points to egg.
FIGURE 6 in Habitat Use, Feeding And Reproductive Traits Of Rocky-Shore Intertidal Mites From Bermuda (Oribatida: Fortuyniidae And Selenoribatidae)
FIGURE 6: Photographs illustrating "floating behaviour" shown by Fortuynia atlantica; specimens floating with splayed legs on the water surface.
FIGURE 5 in Habitat Use, Feeding And Reproductive Traits Of Rocky-Shore Intertidal Mites From Bermuda (Oribatida: Fortuyniidae And Selenoribatidae)
FIGURE 5: SEM-micrographs of exochorion structures; scale bar of left column 40 µm, scale bar of right column 1 µm. A – Alismobates inexpectatus egg; B – detailed surface view of egg shown in A; C – Fortuynia atlantica egg; D – detailed surface view of egg shown in C; E – Carinozetes bermudensis egg; F – surface details of egg shown in E.
FIGURE 3 in Habitat Use, Feeding And Reproductive Traits Of Rocky-Shore Intertidal Mites From Bermuda (Oribatida: Fortuyniidae And Selenoribatidae)
FIGURE 3: Egg of Fortuynia atlantica, vertical row of pictures illustrating chronological development of egg stage. Arrow points to egg.
FIGURE 2 in Habitat Use, Feeding And Reproductive Traits Of Rocky-Shore Intertidal Mites From Bermuda (Oribatida: Fortuyniidae And Selenoribatidae)
FIGURE 2: Eggs of Alismobates inexpectatus deposited into an algal mass, arrows pointing to eggs. A – left egg shortly before eclosion showing dark colour, right egg freshly deposited with lighter colour; B – algal mass removed from egg; C – larva hatching from egg.
FIGURE 1 in Habitat Use, Feeding And Reproductive Traits Of Rocky-Shore Intertidal Mites From Bermuda (Oribatida: Fortuyniidae And Selenoribatidae)
FIGURE 1: A-C – Spermatophores of Alismobates inexpectatus; A – deposited on lateral wall of plastic box; B – deposited on alga; C – bare stalk of spermatophore shown in B; D-F – spermatophores of Carinozetes bermudensis, D-E – deposited on lateral wall of box; F – bare stalk. Arrows pointing to spermatophores and bare stalks, respectively.
Measuring the contribution of evolution to community trait structure in freshwater zooplankton
<p>There are currently few predictions about when evolutionary processes are likely to play an important role in structuring community features.Determining predictors that indicate when evolution is expected to impact ecological processes in natural landscapes can help researchers identify eco-evolutionary 'hotspots', where eco-evolutionary interactions are more likely to occur. Using data collected from a survey in freshwater cladoceran communities, landscape population genetic data, and phenotypic trait data measured in a common garden, we applied a Bayesian linear model to assess whether the impact of local trait evolution in the keystone species <i>Daphnia magna</i> on cladoceran community trait values could be predicted by population genetic properties (within-population genetic diversity, genetic distance among populations), ecological properties (Simpson's diversity, phenotypic divergence), or environmental divergence. We found that the impact of local trait evolution varied among communities. Moreover, community diversity and phenotypic divergence were found to be better predictors of the contribution of evolution to community trait values than environmental features or genetic properties of the evolving species. Our results thus indicate the importance of ecological context for the impact of evolution on community features. Our study also demonstrates one way to detect signatures of eco-evolutionary interactions in communities inhabiting heterogeneous landscapes using survey data of contemporary ecological and evolutionary structure.</p>
Variation in plant leaf traits affects transmission and detectability of herbivore vibrational cues
<p>Many insects use plant-borne vibrations to obtain important information about their environment, such as where to find a mate or a prey, or when to avoid a predator. Plant species can differ in the way they vibrate, possibly affecting the reliability of information, and ultimately the decisions that are made by animals based on this information. We examined whether the production, transmission and possible perception of plant-borne vibrational cues is affected by variation in leaf traits. We recorded vibrations of 69 <i>Spodoptera exigua</i> caterpillars foraging on four plant species that differed widely in their leaf-traits (cabbage, beetroot, sunflower and corn). We carried out a transmission and an airborne noise absorption experiment to assess whether leaf traits influence amplitude and frequency characteristics, and background noise levels of vibrational-chewing cues. Our results reveal that species-specific leaf traits can influence transmission and potentially perception of herbivore-induced chewing vibrations. Experimentally-induced vibrations attenuated stronger on plants with thicker leaves. Amplitude and frequency characteristics of chewing vibrations measured near a chewing caterpillar were, however, not affected by leaf traits. Furthermore, we found a significant effect of leaf area, water content and leaf thickness - important plant traits against herbivory, on the vibrations induced by airborne noise. On larger leaves higher amplitude vibrations were induced, whereas on thicker leaves containing more water airborne noise induced higher peak frequencies. Our findings indicate that variation in leaf traits can be important for the transmission and possibly detection of vibrational cues.</p>
Associations between metabolic traits and growth rate in brown trout (Salmo trutta) depend on thermal regime
<p class="academicstyle"><span><span><span><span><span><span><span><span><span><span><span>Metabolism defines the energetic cost of life, yet we still know relatively little about why intraspecific variation in metabolic rate arises and persists. Spatiotemporal variation in selection potentially maintains differences, but relationships between metabolic traits (standard metabolic rate (SMR), maximum metabolic rate (MMR), and aerobic scope) and fitness across contexts are unresolved. We show that associations between SMR, MMR, and growth rate (a key fitness-related trait) vary depending on thermal regime (a potential selective agent) in offspring of wild-sampled brown trout from two populations reared for ~15 months in either a cool or warm (+ 1.8°C) regime.<i> </i>SMR was positively related to growth in the cool, but negatively related in the warm regime. The opposite patterns were found for MMR and growth associations (positive in warm, negative in cool regime). Mean SMR, but not MMR, was lower in warm regimes within both populations (i.e., basal metabolic costs were reduced at higher temperatures), consistent with an adaptive acclimation response that optimises growth. Metabolic phenotypes thus exhibited a thermally sensitive metabolic 'floor' and a less flexible metabolic 'ceiling'. Our findings suggest a role for growth-related fluctuating selection in shaping patterns of metabolic variation that is likely important in adapting to climate change.</span></span></span></span></span></span></span></span></span></span></span></p>
Anatomical wood traits of tree species in old-growth and selectively logged forest
<b>Description: </b><p>Traits matrix of wood anatomical characteristics for tree species in selectively logged forest at SAFE and in old-growth forest in Danum Valley and Maliau Basin. Sampled during the BALI project traits campaign</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/55"><b>Biodiversity and land-use impacts on tropical ecosystem function (BALI): Quantifying functional trait distributions across the disturbance gradient</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC (Standard grant, NE/K016253/1)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2.2(385))</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=5513918">here</a></p><p><b>Files: </b>This consists of 1 file: Both_wood_anatomical_traits_complete_dataset.xlsx</p><p><b>Both_wood_anatomical_traits_complete_dataset.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Wood_anatomical_traits</b> (described in worksheet Wood_anatomical_traits)</p><p>Description: Traits matrix of wood anatomical characteristics for tree species in selectively logged forest at SAFE and in old-growth forest in Danum Valley and Maliau Basin. Sampled during the BALI project traits campaign</p><p>Number of fields: 18</p><p>Number of data rows: 596</p><p>Fields: </p><ul><li><b>location</b>: Location (Field type: location)</li><li><b>forest_type</b>: Forest type: OG: old-growth plots, Maliau and Danum; SL: selectively logged plots at SAFE (Field type: categorical)</li><li><b>forestplots_name</b>: Plot name coherent with forestplots database (Field type: id)</li><li><b>plot_name_trait_campaign</b>: Plot name used during the BALI trait campaign (Field type: id)</li><li><b>sample_code</b>: Sample code referencing: plot-'T'(ree) ID-branch type (Field type: id)</li><li><b>branch_type</b>: Binary classification of branch sampled depending on their position in the tree crown. BS: sun branch; BSH: shade branch (Field type: id)</li><li><b>sampling_date</b>: Date of sampling (Field type: date)</li><li><b>tree_id</b>: Reference for tree tag label (Field type: id)</li><li><b>species</b>: Tree species (Field type: taxa)</li><li><b>Wedge.area.micron2</b>: Area of wedge from microtome slice used for analysis. (Field type: numeric trait)</li><li><b>No.vessel.wedge</b>: Count of vessels in the respective wedge area. (Field type: numeric trait)</li><li><b>Vessel.diameter.micron</b>: Mean vessel diameter. Vessel diameter is determined as the mean of the maximum and minimum (lumen) diameters. (Field type: numeric trait)</li><li><b>Median.vessel.diameter.micron</b>: The middle value of the vessel diameter data set. (Field type: numeric trait)</li><li><b>Hydraulically.weighted.diameter.micron</b>: Hydraulically weighted mean diameter. Calculated as (∑ diameter^5) / (∑ diameter^4). (Field type: numeric trait)</li><li><b>Vessel.area.micron2</b>: Mean vessel area. Vessel area is determined by the average cross-sectional area of all vessel lumens (excluding vessel walls) in the wedge-shaped transect of the branch wood cross-section. (Field type: numeric trait)</li><li><b>Median.vessel.area.micron2</b>: The middle value of the vessel area data set. (Field type: numeric trait)</li><li><b>Vessel.lumen.tot.area</b>: Total area of the vessel lumens in the wedge-shaped transect of the branch wood cross-section. (Field type: numeric trait)</li><li><b>vessel.lumen.f.wedge</b>: Vessel lumen fraction. From the vessel areas and transect areas, vessel lumen fraction is calculated as the fraction of transect area filled by vessel lumens. (Field type: numeric trait)</li></ul></li></ol><p><b>Date range: </b>2014-05-01 to 2018-09-01</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</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> -  Plantae <br> -  -  Tracheophyta <br> -  -  -  Magnoliopsida <br> -  -  -  -  Malpighiales <br> -  -  -  -  -  Chrysobalanaceae <br> -  -  -  -  -  -  <i>Licania</i> <br> -  -  -  -  -  -  -  <i>Licania splendens</i> <br> -  -  -  -  -  Hypericaceae <br> -  -  -  -  -  -  <i>Cratoxylum</i> <br> -  -  -  -  -  Irvingiaceae <br> -  -  -  -  -  -  <i>Irvingia</i> <br> -  -  -  -  -  -  -  <i>Irvingia malayana</i> <br> -  -  -  -  -  Centroplacaceae <br> -  -  -  -  -  -  <i>Bhesa</i> <br> -  -  -  -  -  -  -  <i>Bhesa indica</i> (as synonym: <i>Bhesa paniculata</i>)<br> -  -  -  -  -  Clusiaceae <br> -  -  -  -  -  -  <i>Garcinia</i> <br> -  -  -  -  -  -  -  <i>Garcinia benthamiana</i> <br> -  -  -  -  -  -  -  <i>Garcinia forbesii</i> <br> -  -  -  -  -  -  -  <i>Garcinia parvifolia</i> <br> -  -  -  -  -  Salicaceae <br> -  -  -  -  -  -  <i>Homalium</i> <br> -  -  -  -  -  -  -  <i>Homalium foetidum</i> <br> -  -  -  -  -  Putranjivaceae <br> -  -  -  -  -  -  <i>Drypetes</i> <br> -  -  -  -  -  -  -  <i>Drypetes longifolia</i> <br> -  -  -  -  -  Achariaceae <br> -  -  -  -  -  -  <i>Hydnocarpus</i> <br> -  -  -  -  -  -  <i>Ryparosa</i> <br> -  -  -  -  -  -  -  <i>Ryparosa acuminata</i> <br> -  -  -  -  -  Euphorbiaceae <br> -  -  -  -  -  -  <i>Spathiostemon</i> <br> -  -  -  -  -  -  <i>Hancea</i> <br> -  -  -  -  -  -  -  <i>Hancea penangensis</i> (as synonym: <i>Mallotus penangensis</i>)<br> -  -  -  -  -  -  <i>Neoscortechinia</i> <br> -  -  -  -  -  -  -  <i>Neoscortechinia kingii</i> <br> -  -  -  -  -  -  -  <i>Neoscortechinia philippinensis</i> <br> -  -  -  -  -  -  <i>Mallotus</i> <br> -  -  -  -  -  -  -  <i>Mallotus leucodermis</i> <br> -  -  -  -  -  -  -  <i>Mallotus miquelianus</i> <br> -  -  -  -  -  -  -  <i>Mallotus mollissimus</i> <br> -  -  -  -  -  -  -  <i>Mallotus wrayi</i> <br> -  -  -  -  -  -  <i>Ptychopyxis</i> <br> -  -  -  -  -  -  -  <i>Ptychopyxis arborea</i> <br> -  -  -  -  -  -  <i>Macaranga</i> <br> -  -  -  -  -  -  -  <i>Macaranga conifera</i> <br> -  -  -  -  -  -  -  <i>Macaranga gigantea</i> <br> -  -  -  -  -  -  -  <i>Macaranga hypoleuca</i> <br> -  -  -  -  -  -  -  <i>Macaranga pearsonii</i> <br> -  -  -  -  -  -  -  <i>Macaranga winkleri</i> <br> -  -  -  -  -  -  <i>Blumeodendron</i> <br> -  -  -  -  -  -  -  <i>Blumeodendron kurzii</i> <br> -  -  -  -  -  -  -  <i>Blumeodendron tokbrai</i> <br> -  -  -  -  -  Phyllanthaceae <br> -  -  -  -  -  -  <i>Aporosa</i> (as synonym: <i>Aporusa</i>)<br> -  -  -  -  -  -  <i>Cleistanthus</i> <br> -  -  -  -  -  -  -  <i>Cleistanthus hirsutulus</i> <br> -  -  -  -  -  -  -  <i>Cleistanthus hylandii</i> <br> -  -  -  -  -  -  -  <i>Cleistanthus oblongifolius</i> (as synonym: <i>Cleistanthus myrianthus</i>)<br> -  -  -  -  -  -  <i>Glochidion</i> <br> -  -  -  -  -  -  <i>Phyllanthus</i> <br> -  -  -  -  -  -  -  <i>Phyllanthus lutescens</i> (as synonym: <i>Glochidion lutescens</i>)<br> -  -  -  -  -  -  -  <i>Phyllanthus ruber</i> (as synonym: <i>Glochidion rubrum</i>)<br> -  -  -  -  -  -  <i>Baccaurea</i> <br> -  -  -  -  -  -  -  <i>Baccaurea lanceolata</i> <br> -  -  -  -  -  -  -  <i>Baccaurea macrocarpa</i> <br> -  -  -  -  -  -  -  <i>Baccaurea tetrandra</i> <br> -  -  -  -  -  Calophyllaceae <br> -  -  -  -  -  -  <i>Mesua</i> <br> -  -  -  -  -  -  -  <i>Mesua oblongifolia</i> (as synonym: <i>Kayea oblongifolia</i>)<br> -  -  -  -  -  -  -  <i>Mesua macrantha</i> <br> -  -  -  -  -  -  <i>Calophyllum</i> <br> -  -  -  -  -  -  -  <i>Calophyllum soulattri</i> <br> -  -  -  -  Malvales <br> -  -  -  -  -  Malvaceae <br> -  -  -  -  -  -  <i>Heritiera</i> <br> -  -  -  -  -  -  -  <i>Heritiera elata</i> <br> -  -  -  -  -  -  <i>Pterygota</i> <br> -  -  -  -  -  -  -  <i>Pterygota alata</i> <br> -  -  -  -  -  -  <i>Pentace</i> <br> -  -  -  -  -  -  -  <i>Pentace borneensis</i> (as synonym: <i>Pentace laxiflora</i>)<br> -  -  -  -  -  -  <i>Sterculia</i> <br> -  -  -  -  -  -  -  <i>Sterculia stipulata</i> <br> -  -  -  -  -  -  <i>Microcos</i> <br> -  -  -  -  -  -  -  <i>Microcos crassifolia</i> <br> -  -  -  -  -  -  <i>Scaphium</i> <br> -  -  -  -  -  -  -  <i>Scaphium macropodum</i> <br> -  -  -  -  -  -  <i>Boschia</i> <br> -  -  -  -  -  -  -  <i>Boschia grandiflora</i> (as synonym: <i>Durio grandiflorus</i>)<br> -  -  -  -  -  -  <i>Durio</i> <br> -  -  -  -  -  -  -  <i>Durio graveolens</i> <br> -  -  -  -  -  Dipterocarpaceae <br> -  -  -  -  -  -  <i>Shorea</i> <br> -  -  -  -  -  -  -  <i>Shorea almon</i> <br> -  -  -  -  -  -  -  <i>Shorea angustifolia</i> <br> -  -  -  -  -  -  -  <i>Shorea argentifolia</i> <br> -  -  -  -  -  -  -  <i>Shorea beccariana</i> <br> -  -  -  -  -  -  -  <i>Shorea faguetiana</i> <br> -  -  -  -  -  -  -  <i>Shorea falciferoides</i> <br> -  -  -  -  -  -  -  <i>Shorea fallax</i> <br> -  -  -  -  -  -  -  <i>Shorea gibbosa</i> <br> -  -  -  -  -  -  -  <i>Shorea guiso</i> <br> -  -  -  -  -  -  -  <i>Shorea johorensis</i> <br> -  -  -  -  -  -  -  <i>Shorea leprosula</i> <br> -  -  -  -  -  -  -  <i>Shorea leptoderma</i> <br> -  -  -  -  -  -  -  <i>Shorea macrophylla</i> <br> -  -  -  -  -  -  -  <i>Shorea macroptera</i> <br> -  -  -  -  -  -  -  <i>Shorea ovalis</i> <br> -  -  -  -  -  -  -  <i>Shorea ovata</i> <br> -  -  -  -  -  -  -  <i>Shorea parviflora</i> <br> -  -  -  -  -  -  -  <i>Shorea parvifolia</i> <br> -  -  -  -  -  -  -  <i>Shorea parvistipulata</i> <br> -  -  -  -  -  -  -  <i>Shorea pauciflora</i> <br> -  -  -  -  -  -  -  <i>Shorea pinanga</i> <br> -  -  -  -  -  -  -  <i>Shorea superba</i> <br> -  -  -  -  -  -  -  <i>Shorea symingtonii</i> <br> -  -  -  -  -  -  -  <i>Shorea xanthophylla</i> <br> -  -  -  -  -  -  <i>Shorea</i> <br> -  -  -  -  -  -  -  <i>Shorea almon</i> <br> -  -  -  -  -  -  -  <i>Shorea angustifolia</i> <br> -  -  -  -  -  -  -  <i>Shorea argentifolia</i> <br> -  -  -  -  -  -  -  <i>Shorea beccariana</i> <br> -  -  -  -  -  -  -  <i>Shorea faguetiana</i> <br> -  -  -  -  -  -  -  <i>Shorea falciferoides</i> <br> -  -  -  -  -  -  -  <i>Shorea fallax</i> <br> -  -  -  -  -  -  -  <i>Shorea gibbosa</i> <br> -  -  -  -  -  -  -  <i>Shorea guiso</i> <br> -  -  -  -  -  -  -  <i>Shorea johorensis</i> <br> -  -  -  -  -  -  -  <i>Shorea leprosula</i> <br> -  -  -  -  -  -  -  <i>Shorea leptoderma</i> <br> -  -  -  -  -  -  -  <i>Shorea macrophylla</i> <br> -  -  -  -  -  -  -  <i>Shorea macroptera</i> <br> -  -  -  -  -  -  -  <i>Shorea ovalis</i> <br> -  -  -  -  -  -  -  <i>Shorea ovata</i> <br> -  -  -  -  -  -  -  <i>Shorea parviflora</i> <br> -  -  -  -  -  -  -  <i>Shorea parvifolia</i> <br> -  -  -  -  -  -  -  <i>Shorea parvistipulata</i> <br> -  -  -  -  -  -  -  <i>Shorea pauciflora</i> <br> -  -  -  -  -  -  -  <i>Shorea pinanga</i> <br> -  -  -  -  -  -  -  <i>Shorea superba</i> <br> -  -  -  -  -  -  -  <i>Shorea symingtonii</i> <br> -  -  -  -  -  -  -  <i>Shorea xanthophylla</i> <br> -  -  -  -  -  -  <i>Vatica</i> <br> -  -  -  -  -  -  -  <i>Vatica dulitensis</i> <br> -  -  -  -  -  -  -  <i>Vatica odorata</i> <br> -  -  -  -  -  -  <i>Hopea</i> <br> -  -  -  -  -  -  -  <i>Hopea plagata</i> <br> -  -  -  -  -  -  -  <i>Hopea sangal</i> <br> -  -  -  -  -  -  <i>Dipterocarpus</i> <br> -  -  -  -  -  -  -  <i>Dipterocarpus caudiferus</i> <br> -  -  -  -  -  -  <i>Dryobalanops</i> <br> -  -  -  -  -  -  -  <i>Dryobalanops lanceolata</i> <br> -  -  -  -  -  -  <i>Parashorea</i> <br> -  -  -  -  -  -  -  <i>Parashorea malaanonan</i> <br> -  -  -  -  -  -  -  <i>Parashorea smythiesii</i> <br> -  -  -  -  -  -  -  <i>Parashorea warburgii</i> (as synonym: <i>Parashorea tomentella</i>)<br> -  -  -  -  -  Thymelaeaceae <br> -  -  -  -  -  -  <i>Aquilaria</i> <br> -  -  -  -  -  -  -  <i>Aquilaria beccariana</i> <br> -  -  -  -  Celastrales <br> -  -  -  -  -  Celastraceae <br> -  -  -  -  -  -  <i>Lophopetalum</i> <br> -  -  -  -  -  -  -  <i>Lophopetalum beccarianum</i> <br> -  -  -  -  -  -  -  <i>Lophopetalum javanicum</i> <br> -  -  -  -  Santalales <br> -  -  -  -  -  Coulaceae <br> -  -  -  -  -  -  <i>Ochanostachys</i> <br> -  -  -  -  -  -  -  <i>Ochanostachys amentacea</i> <br> -  -  -  -  Fagales <br> -  -  -  -  -  Fagaceae <br> -  -  -  -  -  -  <i>Lithocarpus</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus blumeanus</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus conocarpus</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus echinifer</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus gracilis</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus leptogyne</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus sundaicus</i> <br> -  -  -  -  -  -  <i>Lithocarpus</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus blumeanus</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus conocarpus</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus echinifer</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus gracilis</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus leptogyne</i> <br> -  -  -  -  -  -  -  <i>Lithocarpus sundaicus</i> <br> -  -  -  -  -  -  <i>Quercus</i> <br> -  -  -  -  -  -  -  <i>Quercus argentata</i> <br> -  -  -  -  -  -  -  <i>Quercus lowii</i> <br> -  -  -  -  -  -  -  <i>Quercus merrillii</i> <br> -  -  -  -  -  -  <i>Trigonobalanus</i> <br> -  -  -  -  -  -  -  <i>Trigonobalanus verticillata</i> <br> -  -  -  -  -  -  <i>Castanopsis</i> <br> -  -  -  -  -  -  -  <i>Castanopsis hypophoenicea</i> <br> -  -  -  -  Lamiales <br> -  -  -  -  -  Lamiaceae <br> -  -  -  -  -  -  <i>Callicarpa</i> <br> -  -  -  -  -  -  -  <i>Callicarpa pentandra</i> <br> -  -  -  -  -  Oleaceae <br> -  -  -  -  -  -  <i>Chionanthus</i> <br> -  -  -  -  -  -  -  <i>Chionanthus macrocarpus</i> <br> -  -  -  -  -  -  -  <i>Chionanthus pluriflorus</i> <br> -  -  -  -  Rosales <br> -  -  -  -  -  Urticaceae <br> -  -  -  -  -  -  <i>Dendrocnide</i> <br> -  -  -  -  -  -  -  <i>Dendrocnide elliptica</i> <br> -  -  -  -  -  Rosaceae <br> -  -  -  -  -  -  <i>Prunus</i> <br> -  -  -  -  -  -  -  <i>Prunus javanica</i> <br> -  -  -  -  -  -  <i>Pygeum</i> <br> -  -  -  -  -  -  -  <i>Pygeum beccarii</i> (as synonym: <i>Prunus beccarii</i>)<br> -  -  -  -  -  Moraceae <br> -  -  -  -  -  -  <i>Ficus</i> <br> -  -  -  -  -  -  -  <i>Ficus hispida</i> <br> -  -  -  -  -  -  -  <i>Ficus septica</i> <br> -  -  -  -  -  -  -  <i>Ficus uncinata</i> <br> -  -  -  -  -  -  -  <i>Ficus variegata</i> <br> -  -  -  -  -  -  <i>Antiaris</i> <br> -  -  -  -  -  -  -  <i>Antiaris toxicaria</i> <br> -  -  -  -  -  -  <i>Artocarpus</i> <br> -  -  -  -  -  -  -  <i>Artocarpus anisophyllus</i> <br> -  -  -  -  -  -  -  <i>Artocarpus glaucus</i> <br> -  -  -  -  -  -  -  <i>Artocarpus integer</i> <br> -  -  -  -  -  -  -  <i>Artocarpus odoratissimus</i> <br> -  -  -  -  -  -  -  <i>Artocarpus tamaran</i> <br> -  -  -  -  -  Cannabaceae <br> -  -  -  -  -  -  <i>Trema</i> <br> -  -  -  -  -  -  -  <i>Trema orientalis</i> <br> -  -  -  -  Cornales <br> -  -  -  -  -  Nyssaceae <br> -  -  -  -  -  -  <i>Mastixia</i> <br> -  -  -  -  -  -  -  <i>Mastixia trichotoma</i> <br> -  -  -  -  -  Cornaceae <br> -  -  -  -  -  -  <i>Alangium</i> <br> -  -  -  -  -  -  -  <i>Alangium javanicum</i> <br> -  -  -  -  Gentianales <br> -  -  -  -  -  Apocynaceae <br> -  -  -  -  -  -  <i>Alstonia</i> <br> -  -  -  -  -  -  -  <i>Alstonia angustiloba</i> <br> -  -  -  -  -  Rubiaceae <br> -  -  -  -  -  -  <i>Neonauclea</i> <br> -  -  -  -  -  -  -  <i>Neonauclea gigantea</i> <br> -  -  -  -  -  -  <i>Ludekia</i> <br> -  -  -  -  -  -  -  <i>Ludekia borneensis</i> <br> -  -  -  -  -  -  <i>Psydrax</i> <br> -  -  -  -  -  -  -  <i>Psydrax dicoccos</i> <br> -  -  -  -  -  -  <i>Urophyllum</i> <br> -  -  -  -  -  -  -  <i>Urophyllum polyneurum</i> (as synonym: <i>Pleiocarpidia polyneura</i>)<br> -  -  -  -  -  -  <i>Neolamarckia</i> <br> -  -  -  -  -  -  -  <i>Neolamarckia cadamba</i> <br> -  -  -  -  -  -  <i>Nauclea</i> <br> -  -  -  -  -  -  -  <i>Nauclea subdita</i> <br> -  -  -  -  Fabales <br> -  -  -  -  -  Fabaceae <br> -  -  -  -  -  -  <i>Sindora</i> <br> -  -  -  -  -  -  <i>Crudia</i> <br> -  -  -  -  -  -  -  <i>Crudia reticulata</i> <br> -  -  -  -  -  -  <i>Fordia</i> <br> -  -  -  -  -  -  -  <i>Fordia brachybotrys</i> <br> -  -  -  -  -  -  -  <i>Fordia splendidissima</i> <br> -  -  -  -  -  -  <i>Dialium</i> <br> -  -  -  -  -  -  -  <i>Dialium indum</i> <br> -  -  -  -  -  -  -  <i>Dialium kunstleri</i> <br> -  -  -  -  -  -  <i>Archidendron</i> <br> -  -  -  -  -  -  -  <i>Archidendron clypearia</i> <br> -  -  -  -  -  -  <i>Cynometra</i> <br> -  -  -  -  -  -  -  <i>Cynometra mirabilis</i> <br> -  -  -  -  Sapindales <br> -  -  -  -  -  Meliaceae <br> -  -  -  -  -  -  <i>Chisocheton</i> <br> -  -  -  -  -  -  -  <i>Chisocheton ceramicus</i> <br> -  -  -  -  -  -  -  <i>Chisocheton macranthus</i> <br> -  -  -  -  -  -  -  <i>Chisocheton patens</i> <br> -  -  -  -  -  -  <i>Dysoxylum</i> <br> -  -  -  -  -  -  -  <i>Dysoxylum cyrtobotryum</i> <br> -  -  -  -  -  -  -  <i>Dysoxylum densiflorum</i> <br> -  -  -  -  -  -  <i>Aphanamixis</i> <br> -  -  -  -  -  -  -  <i>Aphanamixis polystachya</i> <br> -  -  -  -  -  -  <i>Lansium</i> <br> -  -  -  -  -  -  -  <i>Lansium domesticum</i> <br> -  -  -  -  -  -  <i>Aglaia</i> <br> -  -  -  -  -  -  -  <i>Aglaia crassinervia</i> <br> -  -  -  -  -  -  -  <i>Aglaia leptantha</i> <br> -  -  -  -  -  -  -  <i>Aglaia macrocarpa</i> <br> -  -  -  -  -  -  -  <i>Aglaia odoratissima</i> <br> -  -  -  -  -  -  -  <i>Aglaia oligophylla</i> <br> -  -  -  -  -  -  -  <i>Aglaia silvestris</i> <br> -  -  -  -  -  -  -  <i>Aglaia tomentosa</i> <br> -  -  -  -  -  Sapindaceae <br> -  -  -  -  -  -  <i>Nephelium</i> <br> -  -  -  -  -  -  <i>Paranephelium</i> <br> -  -  -  -  -  -  -  <i>Paranephelium macrophyllum</i> <br> -  -  -  -  -  -  -  <i>Paranephelium xestophyllum</i> <br> -  -  -  -  -  -  <i>Dimocarpus</i> <br> -  -  -  -  -  -  -  <i>Dimocarpus longan</i> <br> -  -  -  -  -  -  <i>Tristiropsis</i> <br> -  -  -  -  -  -  -  <i>Tristiropsis acutangula</i> <br> -  -  -  -  -  -  <i>Pometia</i> <br> -  -  -  -  -  -  -  <i>Pometia pinnata</i> <br> -  -  -  -  -  Burseraceae <br> -  -  -  -  -  -  <i>Santiria</i> <br> -  -  -  -  -  -  -  <i>Santiria laevigata</i> <br> -  -  -  -  -  -  <i>Canarium</i> <br> -  -  -  -  -  -  -  <i>Canarium decumanum</i> <br> -  -  -  -  -  -  -  <i>Canarium denticulatum</i> <br> -  -  -  -  -  -  -  <i>Canarium odontophyllum</i> <br> -  -  -  -  -  -  -  <i>Canarium pilosum</i> <br> -  -  -  -  -  -  <i>Dacryodes</i> <br> -  -  -  -  -  -  -  <i>Dacryodes rostrata</i> <br> -  -  -  -  -  -  -  <i>Dacryodes rugosa</i> <br> -  -  -  -  -  Rutaceae <br> -  -  -  -  -  -  <i>Melicope</i> <br> -  -  -  -  -  -  -  <i>Melicope confusa</i> <br> -  -  -  -  -  Anacardiaceae <br> -  -  -  -  -  -  <i>Mangifera</i> <br> -  -  -  -  -  -  -  <i>Mangifera odorata</i> <br> -  -  -  -  -  -  <i>Parishia</i> <br> -  -  -  -  -  -  -  <i>Parishia insignis</i> <br> -  -  -  -  -  -  <i>Gluta</i> <br> -  -  -  -  -  -  -  <i>Gluta aptera</i> <br> -  -  -  -  -  -  -  <i>Gluta wallichii</i> <br> -  -  -  -  -  -  <i>Melanochyla</i> <br> -  -  -  -  -  -  -  <i>Melanochyla bullata</i> <br> -  -  -  -  -  -  -  <i>Melanochyla tomentosa</i> <br> -  -  -  -  Laurales <br> -  -  -  -  -  Lauraceae <br> -  -  -  -  -  -  <i>Actinodaphne</i> <br> -  -  -  -  -  -  <i>Beilschmiedia</i> <br> -  -  -  -  -  -  -  <i>Beilschmiedia micrantha</i> <br> -  -  -  -  -  -  <i>Phoebe</i> <br> -  -  -  -  -  -  -  <i>Phoebe grandis</i> <br> -  -  -  -  -  -  <i>Litsea</i> <br> -  -  -  -  -  -  -  <i>Litsea accedens</i> <br> -  -  -  -  -  -  -  <i>Litsea angulata</i> <br> -  -  -  -  -  -  -  <i>Litsea caulocarpa</i> <br> -  -  -  -  -  -  -  <i>Litsea garciae</i> <br> -  -  -  -  -  -  -  <i>Litsea grandis</i> <br> -  -  -  -  -  -  -  <i>Litsea cordata</i> (as synonym: <i>Litsea mappacea</i>)<br> -  -  -  -  -  -  -  <i>Litsea rubiginosa</i> <br> -  -  -  -  -  -  <i>Lindera</i> <br> -  -  -  -  -  -  -  <i>Lindera lucida</i> <br> -  -  -  -  -  -  <i>Eusideroxylon</i> <br> -  -  -  -  -  -  -  <i>Eusideroxylon zwageri</i> <br> -  -  -  -  -  -  <i>Nothaphoebe</i> <br> -  -  -  -  -  -  -  <i>Nothaphoebe umbelliflora</i> <br> -  -  -  -  -  -  <i>Cryptocarya</i> <br> -  -  -  -  -  -  -  <i>Cryptocarya nigra</i> <br> -  -  -  -  -  -  -  <i>Cryptocarya nitens</i> <br> -  -  -  -  -  -  <i>Caryodaphnopsis</i> <br> -  -  -  -  -  -  -  <i>Caryodaphnopsis tonkinensis</i> <br> -  -  -  -  -  -  <i>Dehaasia</i> <br> -  -  -  -  -  -  -  <i>Dehaasia caesia</i> <br> -  -  -  -  -  -  -  <i>Dehaasia incrassata</i> <br> -  -  -  -  Magnoliales <br> -  -  -  -  -  Annonaceae <br> -  -  -  -  -  -  <i>Cyathocalyx</i> <br> -  -  -  -  -  -  <i>Monoon</i> <br> -  -  -  -  -  -  <i>Polyalthia</i> <br> -  -  -  -  -  -  -  <i>Polyalthia obliqua</i> <br> -  -  -  -  -  -  <i>Sageraea</i> <br> -  -  -  -  -  -  -  <i>Sageraea elliptica</i> <br> -  -  -  -  -  -  <i>Miliusa</i> <br> -  -  -  -  -  -  -  <i>Miliusa macropoda</i> <br> -  -  -  -  -  -  <i>Stelechocarpus</i> <br> -  -  -  -  -  -  -  <i>Stelechocarpus cauliflorus</i> <br> -  -  -  -  -  -  <i>Xylopia</i> <br> -  -  -  -  -  -  -  <i>Xylopia ferruginea</i> <br> -  -  -  -  -  -  -  <i>Xylopia stenopetala</i> <br> -  -  -  -  -  -  <i>Phaeanthus</i> <br> -  -  -  -  -  -  -  <i>Phaeanthus splendens</i> <br> -  -  -  -  -  -  <i>Maasia</i> <br> -  -  -  -  -  -  -  <i>Maasia sumatrana</i> <br> -  -  -  -  -  -  <i>Neo-uvaria</i> <br> -  -  -  -  -  -  -  <i>Neo-uvaria acuminatissima</i> <br> -  -  -  -  -  -  <i>Orophea</i> <br> -  -  -  -  -  -  -  <i>Orophea myriantha</i> <br> -  -  -  -  -  -  <i>Pseuduvaria</i> <br> -  -  -  -  -  -  -  <i>Pseuduvaria borneensis</i> <br> -  -  -  -  -  Magnoliaceae <br> -  -  -  -  -  -  <i>Magnolia</i> <br> -  -  -  -  -  -  -  <i>Magnolia borneensis</i> <br> -  -  -  -  -  -  -  <i>Magnolia liliifera</i> <br> -  -  -  -  -  -  -  <i>Magnolia tsiampacca</i> <br> -  -  -  -  -  Myristicaceae <br> -  -  -  -  -  -  <i>Knema</i> <br> -  -  -  -  -  -  -  <i>Knema glauca</i> <br> -  -  -  -  -  -  -  <i>Knema latifolia</i> <br> -  -  -  -  -  -  -  <i>Knema laurina</i> <br> -  -  -  -  -  -  -  <i>Knema oblongata</i> <br> -  -  -  -  -  -  <i>Myristica</i> <br> -  -  -  -  -  -  -  <i>Myristica smythiesii</i> <br> -  -  -  -  -  -  <i>Horsfieldia</i> <br> -  -  -  -  -  -  -  <i>Horsfieldia crassifolia</i> <br> -  -  -  -  Ericales <br> -  -  -  -  -  Primulaceae <br> -  -  -  -  -  -  <i>Ardisia</i> <br> -  -  -  -  -  -  -  <i>Ardisia macrophylla</i> <br> -  -  -  -  -  Lecythidaceae <br> -  -  -  -  -  -  <i>Planchonia</i> <br> -  -  -  -  -  -  -  <i>Planchonia brevistipitata</i> <br> -  -  -  -  -  -  <i>Barringtonia</i> <br> -  -  -  -  -  -  -  <i>Barringtonia lanceolata</i> <br> -  -  -  -  -  -  -  <i>Barringtonia macrostachya</i> <br> -  -  -  -  -  -  -  <i>Barringtonia sarcostachys</i> <br> -  -  -  -  -  Symplocaceae <br> -  -  -  -  -  -  <i>Symplocos</i> <br> -  -  -  -  -  -  -  <i>Symplocos fasciculata</i> <br> -  -  -  -  -  Ebenaceae <br> -  -  -  -  -  -  <i>Diospyros</i> <br> -  -  -  -  -  -  -  <i>Diospyros andamanica</i> <br> -  -  -  -  -  -  -  <i>Diospyros curranii</i> <br> -  -  -  -  -  -  -  <i>Diospyros daemona</i> <br> -  -  -  -  -  -  -  <i>Diospyros dictyoneura</i> <br> -  -  -  -  -  -  -  <i>Diospyros macrophylla</i> <br> -  -  -  -  -  -  -  <i>Diospyros muricata</i> <br> -  -  -  -  -  -  -  <i>Diospyros tuberculata</i> <br> -  -  -  -  -  -  -  <i>Diospyros pilosanthera</i> <br> -  -  -  -  -  Theaceae <br> -  -  -  -  -  -  <i>Pyrenaria</i> <br> -  -  -  -  -  -  -  <i>Pyrenaria tawauensis</i> <br> -  -  -  -  -  Pentaphylacaceae <br> -  -  -  -  -  -  <i>Adinandra</i> <br> -  -  -  -  -  -  -  <i>Adinandra dumosa</i> <br> -  -  -  -  -  Sapotaceae <br> -  -  -  -  -  -  <i>Payena</i> <br> -  -  -  -  -  -  -  <i>Payena acuminata</i> <br> -  -  -  -  -  -  <i>Madhuca</i> <br> -  -  -  -  -  -  -  <i>Madhuca dubardii</i> <br> -  -  -  -  -  -  -  <i>Madhuca korthalsii</i> <br> -  -  -  -  -  -  <i>Palaquium</i> <br> -  -  -  -  -  -  -  <i>Palaquium dasyphyllum</i> <br> -  -  -  -  -  -  -  <i>Palaquium sericeum</i> <br> -  -  -  -  Oxalidales <br> -  -  -  -  -  Elaeocarpaceae <br> -  -  -  -  -  -  <i>Elaeocarpus</i> <br> -  -  -  -  -  -  -  <i>Elaeocarpus floribundus</i> <br> -  -  -  -  -  -  -  <i>Elaeocarpus pedunculatus</i> <br> -  -  -  -  -  -  -  <i>Elaeocarpus stipularis</i> <br> -  -  -  -  -  -  <i>Sloanea</i> <br> -  -  -  -  -  -  -  <i>Sloanea javanica</i> <br> -  -  -  -  Myrtales <br> -  -  -  -  -  Melastomataceae <br> -  -  -  -  -  -  <i>Memecylon</i> <br> -  -  -  -  -  -  -  <i>Memecylon oleifolium</i> <br> -  -  -  -  -  Combretaceae <br> -  -  -  -  -  -  <i>Terminalia</i> <br> -  -  -  -  -  -  -  <i>Terminalia citrina</i> <br> -  -  -  -  -  -  -  <i>Terminalia foetidissima</i> <br> -  -  -  -  -  Myrtaceae <br> -  -  -  -  -  -  <i>Syzygium</i> <br> -  -  -  -  -  -  -  <i>Syzygium chloranthum</i> <br> -  -  -  -  -  -  -  <i>Syzygium elopurae</i> <br> -  -  -  -  -  -  -  <i>Syzygium grande</i> <br> -  -  -  -  -  -  -  <i>Syzygium griffithii</i> <br> -  -  -  -  -  -  -  <i>Syzygium kunstleri</i> <br> -  -  -  -  -  -  -  <i>Syzygium lineatum</i> <br> -  -  -  -  -  -  -  <i>Syzygium panzeri</i> <br> -  -  -  -  -  -  -  <i>Syzygium pustulatum</i> (as synonym: <i>Syzygium perpuncticulatum</i>)<br> -  -  -  -  -  -  -  <i>Syzygium racemosum</i> <br> -  -  -  -  -  -  -  <i>Syzygium rheophyticum</i> <br> -  -  -  -  -  -  <i>Syzygium</i> <br> -  -  -  -  -  -  -  <i>Syzygium chloranthum</i> <br> -  -  -  -  -  -  -  <i>Syzygium elopurae</i> <br> -  -  -  -  -  -  -  <i>Syzygium grande</i> <br> -  -  -  -  -  -  -  <i>Syzygium griffithii</i> <br> -  -  -  -  -  -  -  <i>Syzygium kunstleri</i> <br> -  -  -  -  -  -  -  <i>Syzygium lineatum</i> <br> -  -  -  -  -  -  -  <i>Syzygium panzeri</i> <br> -  -  -  -  -  -  -  <i>Syzygium pustulatum</i> (as synonym: <i>Syzygium perpuncticulatum</i>)<br> -  -  -  -  -  -  -  <i>Syzygium racemosum</i> <br> -  -  -  -  -  -  -  <i>Syzygium rheophyticum</i> <br> -  -  -  -  -  -  <i>Syzygium</i> <br> -  -  -  -  -  -  -  <i>Syzygium chloranthum</i> <br> -  -  -  -  -  -  -  <i>Syzygium elopurae</i> <br> -  -  -  -  -  -  -  <i>Syzygium grande</i> <br> -  -  -  -  -  -  -  <i>Syzygium griffithii</i> <br> -  -  -  -  -  -  -  <i>Syzygium kunstleri</i> <br> -  -  -  -  -  -  -  <i>Syzygium lineatum</i> <br> -  -  -  -  -  -  -  <i>Syzygium panzeri</i> <br> -  -  -  -  -  -  -  <i>Syzygium pustulatum</i> (as synonym: <i>Syzygium perpuncticulatum</i>)<br> -  -  -  -  -  -  -  <i>Syzygium racemosum</i> <br> -  -  -  -  -  -  -  <i>Syzygium rheophyticum</i> <br> -  -  -  -  -  Lythraceae <br> -  -  -  -  -  -  <i>Duabanga</i> <br> -  -  -  -  -  -  -  <i>Duabanga moluccana</i> <br></div><p></p>
melian009/Mispark: Preliminary analysis mutualistic networks in space, rarefaction, sierra size and sampling individuals, species, and traits
<p>Mutualistic networks in space, morphological traits and colors, or how to put all together to understand rare and common species in rapidly changing landscapes</p>
Data for: Strong phenotypic trait correlations between mating partners do not result from assortative mating in wild great tits (Parus major)
<p>There is considerable debate about the occurrence of assortative mating between phenotypic traits measured within natural populations. Meta-analyses have implied that assortative mating occurs generally in natural populations but recent work indicates these conclusions largely result from biased data. Specifically, estimates of phenotypic correlations between mating partners do not solely result from non-random associations between individual-level traits of partners but also from other biological processes (joint phenotypic plasticity, indirect genetic effects), methodological practices (observer bias), and other unexplained residual correlations (e.g. correlated measurement error). This paper puts this critique to test. First, we estimated the overall phenotypic correlation between phenotypic traits of mating partners for a wild population of great tits. Second, we estimated various key variance components to reveal the extent to which phenotypic correlations between partners resulted from assortative mating, reversible plasticity, social partner effects, and methodological practices. We performed our analyses for a range of phenotypic traits (body mass, breathing rate, exploration behaviour, wing and tarsus length) to derive general conclusions not hinging on the specifics of the traits involved. Our analyses support the conclusion that patterns of assortative mating exist at first glance but occur because of the biasing effects of correlated residuals likely caused by a combination of phenotypic responses to unknown environmental factors or measurement error – not because of intrinsic patterns of assortative mating.</p>
Selfing rate variation within species is unrelated to life-history traits or geographic range position
<p>Premise: In plants, populations and species vary widely along the continuum from outcrossing to selfing. Life-history traits and ecological circumstances influence among-species variation in selfing rates but their general role in explaining intraspecific variation is unknown. Using a database of plant species, we test whether life-history traits, geographic range position, or abundance predict selfing rate variation among populations. </p> <p>Methods: We identified species where selfing rates were estimated in at least three populations at known locations. Two key life-history traits (generation time and growth form) were used to predict within-species selfing rate variation. Populations sampled within a species' native range were assessed for proximity to the nearest edge and abundance. Finally, we conducted linear and segmented regressions to determine functional relationships between selfing rate and geographic range position within species.</p> <p>Key results: While woody species exhibit lower variation in selfing rates compared to herbs, this is explained by the lower average selfing rate of woody species. Relationships between selfing and peripherality or abundance significantly varied among species in their direction and magnitude. However, there was no general pattern of increased selfing towards range edges. A power analysis shows that tests of this hypothesis require studying many (i.e. 40+) populations.</p> <p>Conclusions: Intraspecific variation in plant mating systems is often substantial yet remains difficult to explain. Beyond sampling more populations, future tests of biogeographic hypotheses will benefit from phylogeographic information concerning specific range edges, the study of traits influencing mating system (e.g. herkogamy), and measures of abundance at local scales (e.g. population density).</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
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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
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