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35 results for “tree species composition”
Not all trees can make a forest: tree species composition and competition control forest encroachment in a tropical savanna
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Data from: Can variation in seed removal patterns of Neotropical pioneer tree species be explained by local ant community composition?
<p>Many plants depend on animals for seed dispersal, and ants commonly fill this role. We examined if heterogeneity in ant community composition among sites, between above- and below-ground foraging guilds, or between seasons predicts observed variation in seed removal rates for 12 nonmyrmecochorous Neotropical pioneer tree species on Barro Colorado Island, Panama. We also investigated if ants associated with removing seeds differed in specific morphological characters from the larger ant community. We observed ant-seed interactions at caches to determine which ants removed seeds of 12 tree species. We also sampled ant community composition by placing 315 pitfall traps and 160 subterranean traps across the five sites where seed removal rates were quantified. Above-ground ant community composition varied by site but not season. Among-site variation in ant composition did not predict seed removal patterns at these same sites. Below-ground ant communities differed from above-ground ant communities but were not structured by either site or seed cache type. Finally, ants that removed seeds did not differ morphologically from the broader ant community. Overall, our results suggest ant communities vary over relatively small spatial scales but exhibit a high degree of functional redundancy in terms of seed removal services provided for Neotropical pioneer tree species.</p>
Species TX OK Distribution Map FH Hosts Phloeotribus liminaris (Harris) 1* 1* SENA 15 ph Prunus Phloeotribus pseudoscabricollis Atkinson 1 MEX+NT 16 ph Zanthoxylum Phloeotribus texanus Schaeffer 1 1* SE+MEX 17 ph Celtis Phloeosinina Chramesus chapuisii LeConte 1 1 SE+MEX 18 ph Celtis Chramesus hicoriae LeConte 1* 1* SENA 19 ph Carya Chramesus mimosae Blackman 1 MEX+NT 18 ph Legume trees Chramesus subopacus Schaeffer 1 MEX+NT 20 ph Celtis Chramesus varius Wood 1 MEX+NT 19 ph Legume trees Phloeosinus cristatus (LeConte) 1 SWNA 21 ph Cupressus Phloeosinus dentatus (Say) 1 1 SENA 22 ph Juniperus Phloeosinus hoferi Blackman 1 SWNA 25 ph Juniperus Phloeosinus scopulorum neomexicanus Blackman 1 SWNA 23 ph Juniperus Phloeosinus serratus (LeConte) 1 SWNA 24 ph Juniperus Phloeosinus taxodii Blackman 1 SE+MEX 21 ph Taxodium Hypoborina Chaetophloeus fasciatus (Blackman) 1 SWNA 26 ph Prosopis Chaetophloeus heterodoxus (Casey) 1 SWNA ph Rosaceae Chaetophloeus mexicanus Wood 1* MEX+NT 27 ph Eysenhardtia Chaetophloeus sulcatus Wood 1* MEX+NT 28 ph Composite shrubs Liparthrum squamosum (Blackman) 1*? SENA 29 ph Maclura pomifera Polygraphina Carphobius arizonicus Blackman 1* SWNA 30 ph Juniperus Carphoborus bicornus Wood 1* 1* SENA 31 ph Pinus Carphoborus bifurcus (Chapuis) 1* SENA 32 ph Pinus Carphoborus convexifrons Wood 1 SWNA 31 ph Pinus in Atlas and checklist of the bark and ambrosia beetles of Texas and Oklahoma (Curculionidae: Scolytinae and Platypodinae)
Species TX OK Distribution Map FH Hosts Phloeotribus liminaris (Harris) 1* 1* SENA 15 ph Prunus Phloeotribus pseudoscabricollis Atkinson 1 MEX+NT 16 ph Zanthoxylum Phloeotribus texanus Schaeffer 1 1* SE+MEX 17 ph Celtis Phloeosinina Chramesus chapuisii LeConte 1 1 SE+MEX 18 ph Celtis Chramesus hicoriae LeConte 1* 1* SENA 19 ph Carya Chramesus mimosae Blackman 1 MEX+NT 18 ph Legume trees Chramesus subopacus Schaeffer 1 MEX+NT 20 ph Celtis Chramesus varius Wood 1 MEX+NT 19 ph Legume trees Phloeosinus cristatus (LeConte) 1 SWNA 21 ph Cupressus Phloeosinus dentatus (Say) 1 1 SENA 22 ph Juniperus Phloeosinus hoferi Blackman 1 SWNA 25 ph Juniperus Phloeosinus scopulorum neomexicanus Blackman 1 SWNA 23 ph Juniperus Phloeosinus serratus (LeConte) 1 SWNA 24 ph Juniperus Phloeosinus taxodii Blackman 1 SE+MEX 21 ph Taxodium Hypoborina Chaetophloeus fasciatus (Blackman) 1 SWNA 26 ph Prosopis Chaetophloeus heterodoxus (Casey) 1 SWNA ph Rosaceae Chaetophloeus mexicanus Wood 1* MEX+NT 27 ph Eysenhardtia Chaetophloeus sulcatus Wood 1* MEX+NT 28 ph Composite shrubs Liparthrum squamosum (Blackman) 1*? SENA 29 ph Maclura pomifera Polygraphina Carphobius arizonicus Blackman 1* SWNA 30 ph Juniperus Carphoborus bicornus Wood 1* 1* SENA 31 ph Pinus Carphoborus bifurcus (Chapuis) 1* SENA 32 ph Pinus Carphoborus convexifrons Wood 1 SWNA 31 ph Pinus
Dataset for: Interactive effects of tree species composition and water availability on growth and direct and indirect defences in Quercus ilex
<p>Plant diversity has often been reported to decrease insect herbivory in plants. Of the numerous mechanisms that have been proposed to explain this phenomenon, how plant diversity influences plant defences via effects on growth has received little attention. In addition, plant diversity effects may be contingent on abiotic conditions (e.g., resource and water availability). Here, we used a long-term experiment to explore the interactive effects of tree species composition and water availability on growth, direct (i.e. phenolics) and indirect (i.e. Volatile Organic Compounds – VOCs) defences and leaf herbivory in <em>Quercus ilex</em>. We quantified herbivory by chewing insects, phenolic compounds and VOCs in <em>Q. ilex</em> trees growing in stands differing in tree species composition (<em>Q. ilex</em>, <em>Q. ilex</em> + <em>Betula Pendula</em>, <em>Q. ilex</em> + <em>Pinus pinaster</em> and <em>Q. ilex</em> + <em>B. pendula</em> + <em>P. pinaster</em>) and water availability (irrigated vs control). Both direct and indirect defences were affected by tree species composition, but such changes were not mediated by changes in tree stem diameter. <em>Q. ilex</em> trees growing in stands with <em>P. pinaster</em> had the lowest concentration of both direct and indirect defences. Importantly, the effects of tree species composition on VOCs were exacerbated on irrigated blocks. Despite variation in defences, tree species composition did not affect herbivory in <em>Q. ilex</em>. Accordingly, we did not find any association between defences and insect herbivory. Our results suggest that changes in the micro-environment rather than growth-defence associations may mediate tree diversity effects on defences. In addition, reduced defensive investment in more diverse stands could negatively impact tree resistance masking the beneficial effects of species diversity at reducing insect herbivory.</p>
Litter and root traits control soil microbial composition and enzyme activities in 28 common subtropical tree species
<p><span>1. </span><span>Plant trait-based approaches are frequently used to explore the linkages between aboveground plant communities and belowground ecosystem functions. However, the role of plant leaf litter and living root traits in driving soil microbial biomass, community composition, and enzyme activities has rarely been explored.</span></p> <p><span>2. </span><span>Here, we measured the soil microbial biomass, community composition and enzyme activities related to carbon (C), nitrogen (N), and phosphorus (P) acquisition under three-year-old monocultures of 28 common subtropical tree species in China.</span></p> <p><span>3. </span><span>We found that plant leaf litter and absorptive root traits, including leaf litter C content, litter water holding capacity, and root N content, were the three best predictors for soil microbial biomass and enzyme activities. In particular, resource-exploitative tree species with higher root N contents were associated with microbial communities with lower fungi to bacteria ratios and lower C- and P-acquisition enzyme activities. Tree species with higher leaf litter water holding capacity were associated with microbial resource acquisition strategies for C and P acquisition.</span></p> <p><span>4. </span><span>Synthesis: Our findings highlighted that plant leaf litter and root traits are important for mechanistically understanding the ecological linkage between the plant community and ecosystem functions.</span></p>
Data for: Sun, Ogushi, Tseng -Lepidoptera species richness and community composition in urban street trees
<p>The triple threats of climate change, habitat loss, and environmental pollution have stimulated discussion on how urban areas can be modified to both mitigate heat increases and provide habitat for wildlife such as insects. The strategy of using trees to reduce temperatures has been adopted by numerous cities. However, the majority of street trees planted around the world are non-native. Studies conducted in non-urban areas have demonstrated in comparison to native plants, non-native plants are less likely to support native insect diversity. Here we use a database approach to quantify the number of native Lepidoptera species associated with 76 of the most common street tree species planted in Vancouver, Canada. We tested the prediction that compared to non-native trees, native street trees will support a higher diversity and unique community of native Lepidoptera. As predicted, native street trees were associated with five times as many native Lepidoptera species, and the Lepidoptera communities supported by native vs. non-native street trees were distinct. There was no difference in native Lepidoptera associations between broadleaf vs. coniferous street trees. These results are consistent with studies that have used active sampling techniques to investigate insect richness on a smaller subset of native and non-native tree species. Collectively, these data provide good evidence that the planting native instead of non-native trees will help stem the loss of insect diversity in urban areas.</p>
SDM results for 10,590 tree species from "Regional uniqueness of tree species composition and response to forest loss and climate change"
<p>Output from species distribution models (SDMs) with geographic constraints to estimate the spatial distribution of tree species at the global level at a 30-arc second resolution, presented in the publication "Regional uniqueness of tree species composition and response to forest loss and climate change". </p> <h2>Data</h2> <p>This file contains the results for 10,590 tree species. The results for each species are contained in a directory with the species name connected by an underscore. For most species, the directory contains several .tif files that make up the tiles of the distribution maps for that species and a metadata file. The .tif files can be merged with the gdal_merge.py function to obtain a single .tif file per species (see example below). For some species, the directory contains a single .tif file which does not require merging. In all cases, the .tif files contain 9 bands that correspond to the predicted species distribution using climatic variables corresponding to various climate projections from Chelsa 2.1.</p> <h3>Band order</h3> <ol> <li>covariates_1981_2010: average of historical climate measurements from 1981 to 2010</li> <li>covariates_2011_2040_ssp126: average future climate projection for 2011-2040 under shared socioeconomic pathway (SSP) 1.26</li> <li>covariates_2011_2040_ssp370: average future climate projection for 2011-2040 under SSP 3.70</li> <li>covariates_2011_2040_ssp585: average future climate projection for 2011-2040 under SSP 5.85</li> <li>covariates_2041_2070_ssp126: average future climate projection for 2041-2070 under SSP 1.26</li> <li>covariates_2041_2070_ssp370: average future climate projection for 2041-2070 under SSP 3.70</li> <li>covariates_2041_2070_ssp585: average future climate projection for 2041-2070 under SSP 5.85</li> <li>covariates_2071_2100_ssp126: average future climate projection for 2071-2100 under SSP 1.26</li> <li>covariates_2071_2100_ssp370: average future climate projection for 2071-2100 under SSP 3.70</li> <li>covariates_2071_2100_ssp585: average future climate projection for 2071-2100 under SSP 5.85</li> </ol> <h3>Metadata</h3> <p>The metadata contains more information about the bands, as well as the following species-level properties:</p> <ul> <li>nobs: number of spatially distinct occurrence records used in model training</li> <li>precision: precision of binarised model output computed through 3-fold cross-validation</li> <li>threshold: threshold used to binarise probabilistic model output, determined as the threshold maximizing the true skill statistic (TSS) during 3-fold cross-validation</li> <li>f1: F1 score of binarised model output computed through 3-fold cross-validation</li> <li>auc: area under the ROC curve (AUC) of model output computed through 3-fold cross-validation</li> <li>prevalence: prevalence of presences (ie. occurrences records) throughout the training data which consisted of occurrence records and pseudo-absences</li> <li>tss: TSS of binarised model output computed through 3-fold cross-validation</li> <li>recall: recall of binarised model output computed through 3-fold cross-validation</li> <li>nativeness_info: indicates whether reported native countries were available for this species (possible values: "yes" or "no", should be "yes" for all species included)</li> <li>npa: number of pseudo-absences used in model training</li> <li>system:index: species name </li> </ul> <h3>Merging example</h3> <p>For example, the directory Abarema_barbouriana contains files Abarema_barbouriana_0.tif, Abarema_barbouriana_2.tif, ..., Abarema_barbouriana_9.tif and metadata.json. The tiles can be merged with the command "gdal_merge.py -o Abarema_barbouriana_merged.tif Abarema_barbouriana/Abarema_barbouriana_*.tif".</p>
Litter and root traits control soil microbial composition and enzyme activities in 28 common subtropical tree species
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Data from: Regional variation in Caribbean dry forest tree species composition
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Data for: Sun, Ogushi, Tseng -Lepidoptera species richness and community composition in urban street trees
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Data from: Tree species composition, breeding systems, pollination and dispersal syndromes in three forest successional stages in a tropical dry forest in Mesoamerica
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Data from: Can variation in seed removal patterns of Neotropical pioneer tree species be explained by local ant community composition?
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Community composition of tree and palm species in a forest with bamboo in southwestern Amazonia
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Dataset for: Interactive effects of tree species composition and water availability on growth and direct and indirect defences in Quercus ilex
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Single-nucleus transcriptomic sequencing and cross integration comparison of multiple species revealed new cell composition and specific gene marker in hippocampal aging of tree shrew
GEO Series GSE229035. Tupaia belangeri. 15 samples. Type: Expression profiling by high throughput sequencing.
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