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15,460 results for “Neotropics”
Ant Functional Diversity in Temperate Zone Forests: A Comparison with Neotropical Ants 2010
Predicted impacts of climatic change on ant functional diversity and distributions in eastern North American forests Aims--Climatic change is expected to rearrange species assemblages and ultimately affect organism-mediated ecosystem processes. We focus on identifying patterns and relationships between common ant species (representing 99% of total ant records) richness and functional diversity; modelling how these patterns may change at local and regional scales in future climatic conditions; and interpreting how these changes might influence ant-mediated ecosystem processes. Location--Forested ecosystems of eastern North America. Methods--We used a previously published dataset to evaluate functional diversity at 67 sites in the eastern U.S. and quantified 14 taxonomic, morphometric and natural history traits for 70 common ant species in the region. We used functional diversity metrics, functional groups and species distribution modelling methods to address our aims. We used stacked species distribution models and stacked functional group models to predict species assemblages and functional richness at the 67 sites and at a regional scale for current and future climatic conditions. Results--Species richness and functional diversity are positively correlated throughout the region. Under future climate scenarios, species richness and functional group richness were predicted to decrease in southern ecoregions and increase in northern ecoregions. This may be due to increased thermal stress for species in the southern extent of their ranges and increased habitat suitability in the northern ecoregions. Decomposers, arthropod community regulators and seed dispersers are forecast to be the most threatened ant functional groups. Main Conclusions--Climate change will likely lead to major changes in ant species richness and functional group richness in the forests of the north-eastern United States, and this may substantially alter ant-mediated ecosystem processes and services
Greenhouse experiment (FCE) in April and August 2001: Responses of neotropical mangrove saplings to the combined effect of hydroperiod and salinity/Biomass
A greenhouse experiment was performed for 13.5 months to evaluate the effect of salinity and hydroperiod on seedling growth rates of 2 mangrove species( Laguncularia racemosa and Rizhophora mangle). Data analyses are currently being performed.
Bridging archaeology and marine conservation in the Neotropics (Supplementary information)
<p>Supplementary information from the article "Bridging archaeology and marine conservation in the Neotropics" published in the Journal Plos ONE.</p>
Frugivoria: A trait database for birds and mammals exhibiting frugivory across contiguous Neotropical moist forests
Biodiversity in many areas is rapidly shifting and declining as a consequence of global change. As such, there is an urgent need for new tools and strategies to help identify, monitor, and conserve biodiversity hotspots. One way to identify these areas is by quantifying functional diversity, which measures the unique roles of species within a community and is valuable for conservation because of its relationship with ecosystem functioning. Unfortunately, the trait information required to evaluate functional diversity is often lacking and is difficult to harmonize across disparate data sources. Biodiversity hotspots are particularly lacking in this information. To address this knowledge gap, we compiled Frugivoria, a trait database containing dietary, life-history, morphological, and geographic traits, for mammals and birds exhibiting frugivory, which are important for seed dispersal, an essential ecosystem service. Accompanying Frugivoria is an open workflow that harmonizes trait and taxonomic data from disparate sources and enables users to analyze traits in space. This version of Frugivoria contains mammal and bird species found in contiguous moist montane forests and adjacent moist lowland forests of Central and South America– the latter specifically focusing on the Andean states. In total, Frugivoria includes 45,216 unique trait values, including new values and harmonized values from existing databases. Frugivoria adds 23,707 new trait values (8,709 for mammals and 14,999 for birds) for a total of 1,733 bird and mammal species. These traits include diet breadth, habitat breadth, habitat specialization, body size, sexual dimorphism, and range-based geographic traits including range size, average annual mean temperature and precipitation, and metrics of human impact calculated over the range. Frugivoria fills gaps in trait categories from other databases such as diet category, home range size, generation time, and longevity, and extends certain traits, once only a
Supplementary data for: On the Neotropical spider genus Ciniflella Mello-Leitão, 1921 (Araneae: Zoropsidae, Tengellinae)
<p>Phylogenetic datasets, trees and supplementary figures.</p>
Dataset and R code: Above and belowground functional trait coordination in the Neotropical understory genus Costus
<p>Dataset and R code accompanying the paper "Above and belowground functional trait coordination in the Neotropical understory genus <em>Costus</em>" published by AoB Plants. </p>
Data from: The legacy of the extinct Neotropical megafauna on plants and biomes
<p>The main dataset consists of ecoregion-level data on five plant functional traits (wood density, leaf size, stem spines, leaf spines and latex production), as well as ecoregion-level data on extinct megafauna historical patterns, fire, climate, soil, hurricanes and geografical variables (first spreadsheet) for the Neotropical biogeographic realm (Table 1). It also includes species-level plant functional trait data, and the abundance (presence-absence for leaf size) of these species, and the occurrences extinct megafauna and extant mammal herbivore species per Neotropical ecoregion, as well as diet data compiled for megafauna species. The species-level functional trait data was compiled from the literature and the names of the species in these data was used to search for occurrence data for these species in the Global Biodiversity Information Facility (Data available from GBIF using the following doi: WD: 10.15468/dl.3vua3x; Stem spines: 10.15468/dl.ar5ddj; Latex: 10.15468/dl.m8dzjd; Leaf spines: 10.15468/dl.vv8gw4; Leaf size: 10.15468/dl.k98nxc). During the process, species level were corrected and updated using tools from the "rgbif" package for R. We then croped only the Neotropical region, and calculate ecoregion level trait means for continuous traits (Wood Density and Leaf Size) and maximum por binary traits (Stem and Leaf Spines, Latex), using the ecoregion shapefile provided in https://storage.googleapis.com/teow2016/Ecoregions2017.zip. We obtained data on historical distribution of megafauna species and extant mammal species from the MegaPast2Future/PHYLACINE_1.2 dataset, and obtained diet information from literature sources. Climate data was obtained from WorldClim 2.1 (10 minute spatial resolution) and was based on climate data from 1970 and 2000. Soil data were obtained from SoilGrids (5 km of spatial resolution), and consisted of mean values for two depths, 0.05 and 2 m. We obtained the number (a proxy for frequency) and intensity of wildfires per ecoregion area using the MODIS active fire location product (MCD14ML). We only considered fires with detection confidence of 95% or higher occurring from November 2000 to December 2019 (both included). To ensure that only wildfires were considered, we associated each fire pixel with a land cover type (300 m of spatial resolution) from for a buffer area of 1000 m surrounding the fire pixel centroid. We excluded all of the fires occurring in areas in which more than 10% of the surrounding land cover pixels corresponded to agricultural, urban and water classes. We calculated the number of wildfires per ecoregion area by dividing the fire count of each Ecoregion by the ecoregion area, and multiplying the resulting value by the proportion of vegetated land cover pixels (same classes used to exclude fires in anthropogenic areas and water bodies above). Fire intensity was estimated as the average fire radiative power across all detected wildfires in the ecoregion. We also classified ecoregions into insular (1), when most of the ecoregion area was located in islands, vs. continental (0), otherwise. We also compiled data on hurricane activity, as woody density was suggested to confer resistance against this disturbance. We used data from 1990 to 2019 from the HURDAT2 dataset, containing six-hourly information about the location of all of the known tropical and subtropical cyclones (0.1° latitude/longitude). We used the sum of hurricane occurrences per ecoregions divided by ecoregion area as an indicator of hurricane activity.</p> <p>Three .txt files containing the custom codes developed for building the Ecoregion-level dataset (predictors and traits) and for data analyses used in the article are also included.</p>
Data from: Vegetative phenologies of lianas and trees in two Neotropical forests with contrasting rainfall regimes
<ol> <li>Among tropical forests, lianas are predicted to have a growth advantage over trees during seasonal drought, with substantial implications for tree and forest dynamics. We tested the hypotheses that lianas maintain higher water status than trees during seasonal drought and that lianas maximize leaf cover to match high, dry-season light conditions while trees are more limited by moisture availability during the dry season.</li> <li>We monitored the seasonal dynamics of predawn and midday leaf water potentials and leaf phenology for branches of 16 liana and 16 tree species in the canopy of two lowland tropical forests with contrasting rainfall regimes in Panama.</li> <li>In a wet, weakly seasonal forest, lianas maintained higher water balance than trees and maximized their leaf cover during dry-season conditions, when light availability was high, while trees experienced drought stress. In a drier, strongly seasonal forest, lianas and trees displayed similar dry season reductions in leaf cover following strong decreases in soil water availability.</li> <li>Greater soil moisture availability and a higher capacity to maintain water status allow lianas to maintain the turgor potentials critical for plant growth in a wet and weakly seasonal forest but not in a dry and strongly seasonal forest.</li> </ol>
Biogeographic history of a large clade of ectomycorrhizal fungi, the Russulaceae, in the Neotropics and adjacent regions
<p>## Metadata</p> <p>backbone_accessions.tsv - GenBank/INSDC accession numbers for LSU, rpb1 and rpb2 accessions used for the Russulaceae backbone tree including 472 taxa.</p> <p>ITS_sequences_OTUs.tsv - Metadata for all 34,624 ITS sequences used in the study. Columns: "accession": accession ID in analysis – GenBank/INSDC or UNITE accession number for compiled data, lab ID for newly generated data; "specimen": specimen/voucher number, for newly generated sequences; "INSDC_accession": INSDC/GenBank accession for new newly generated data; "taxon": specimen identification; "New": whether ITS sequences was generated in this study (*); "OTU": name of cluster/OTU, if not the sequence accession itself (*); "In_tree": whether sequence is represented in the Russulaceae supertree after filtering steps (*), "lb" long-branch accession removed during tree estimation, "ol" outlier removed during tree estimation; "area": biogeographic area assigned.</p> <p> </p> <p>## Sequences and alignments</p> <p>backbone_concat.fasta - Concatenated LSU-rpb1-rpb2 alignment for 372 backbone taxa.</p> <p>backbone_concat_part.txt - Gene partitions and substitution models applied to the backbone alignment.</p> <p>einsi_clade1_Russula_trimmed.fasta - Alignment of 2,279 representative ITS sequences in the Russula clade; alignment end columns with >90% missing data/gaps were trimmed.</p> <p>einsi_clade2_LactariusMultifurca_trimmed.fasta - Alignment of 621 representative ITS sequences in the Lactarius-Multifurca clade; alignment end columns with >90% missing data/gaps were trimmed.</p> <p>einsi_clade3_Lactifluus_trimmed.fasta - Alignment of 482 representative ITS sequences in the Lactifluus clade; alignment end columns with >90% missing data/gaps were trimmed.</p> <p> </p> <p>## Phylogenetic trees</p> <p>12_make_supertree.R - R script for grafting clade trees onto the backbone tree to produce a supertree.</p> <p>backbone_calibrated.nwk - Time-calibrated Russulaceae backbone phylogeny.</p> <p>backbone_TBE.raxml.support - Russulaceae backbone phylogeny annotated with transfer bootstrap expectation support values.</p> <p>clade1_Russula_TBE.raxml.support - Russula subclade ITS phylogeny (2,279 tips), annotated with transfer bootstrap expectation support values.</p> <p>clade2_LactariusMultifurca_TBE.raxml.support - Lactarius-Multifurca subclade ITS phylogeny (621 tips), annotated with transfer bootstrap expectation support values.</p> <p>clade3_Lactifluus_TBE.raxml.support - Lactifluus subclade ITS phylogeny (482 tips), annotated with transfer bootstrap expectation support values.</p> <p>supertree_calibrated.nwk - Combined Russulaceae supertree, time-calibrated (root age = 1).</p> <p>tree_calibrated_clade1_Russula.nwk - Russula subclade ITS backbone phylogeny, time-calibrated (root age = 1).</p> <p>tree_calibrated_clade2_LactariusMultifurca.nwk - Lactarius-Multifurca subclade ITS backbone phylogeny, time-calibrated (root age = 1).</p> <p>tree_calibrated_clade3_Lactifluus.nwk - Lactifluus subclade ITS backbone phylogeny, time-calibrated (root age = 1).</p> <p> </p> <p>## Biogeographic analysis</p> <p>3_disp_counts.R - R script to count dispersal events between biogeographic areas, based on stochastic mapping output.</p> <p>9_disp_count_time.R - R script to count dispersal events to and from each area through time, based on stochastic mapping output.</p> <p>area_codes.tab - Area letter coding and colours used for biogeographic analysis and plotting.</p> <p>area_shapes.zip - Shapefiles for the nine biogeographic areas defined, based on merged areas from Dinerstein et al. 2017 (https://doi.org/10.1093/biosci/bix014) and Löwenberg-Neto (2014: https://doi.org/10.11646/zootaxa.3802.2.12; 2015: https://doi.org/10.11646/10.11646/zootaxa.3985.4.9).</p> <p>areas_manually_zenodo.csv - Manual assignment of 800 ITS sequences to biogeographic areas based on associated literature records or metadata.</p> <p>corHMM_ER.Rdata - R data archive with input data and results for the corHMM/Mv biogeographic area reconstruction.<br> <br> corHMM_ER_stoch_maps.Rdata - R data archive with results from the corHMM/Mv biogeographic stochastic mapping.</p> <p>disp_counts_focal.tab - Dispersal counts to and from each focal area through time, based on BioGeoBEARS stochastic mapping output.</p> <p>disp_counts_sam_afr.tab - Dispersal counts between Afrotopics and lowland tropical S. America through time, based on BioGeoBEARS stochastic mapping output.</p> <p>disp_matrix_025.txt - Dispersal rates between biogeographic areas (2.5% quantiles), based on stochastic mapping output.</p> <p>disp_matrix_975.txt - Dispersal rates between biogeographic areas (97.5% quantiles), based on stochastic mapping output.</p> <p>disp_matrix_median.txt - Dispersal rates between biogeographic areas (median values), based on stochastic mapping output.</p> <p> </p> <p>## Diversification analysis</p> <p>5_rates_per_area.R - R script to partition diversification rates by biogeographic area, both overall and through time, based on BAMM diversification rates and area stochastic mapping.</p> <p>event_data.txt - Posterior samples of diversification rate regimes estimated with BAMM.</p> <p>div_rates_area_overall.txt - Overall diversification rates per biogeographic area, based on BAMM diversification rates and area stochastic mapping.</p> <p>div_rates_per_area_025.tsv - Diversification rates through time (2.5% quantiles) partitioned by biogeographic area, based on BAMM diversification rates and area stochastic mapping.</p> <p>div_rates_per_area_975.tsv - Diversification rates through time (97.5% quantiles) partitioned by biogeographic area, based on BAMM diversification rates and area stochastic mapping.</p> <p>div_rates_per_area_median.tsv - Diversification rates through time (means) partitioned by biogeographic area, based on BAMM diversification rates and area stochastic mapping.</p> <p>mcmc_out.txt - BAMM posterior sample characteristics.</p>
Data for: The function of stilt roots in the growth strategy of Socratea exorrhiza (Arecaceae) at two neotropical sites
<p>We provide the raw and processed data used in the following study: Goldsmith, G. R., & Zahawi, R. A. (2007). The function of stilt roots in the growth strategy of Socratea exorrhiza (Arecaceae) at two neotropical sites. <em>Revista de Biología Tropical</em>, <em>55</em>(3-4), 787-793.</p> <p><strong>Methods</strong> can be found in the file entitled "README-GoldsmithZahawi-SocrateaData-5Mar23F.txt," while metadata for data columns can be found in the file entitled: "GoldsmithZahawi-SocrateaMetaData-5March2023.csv."</p> <p><strong>Original Published Abstract</strong>: Arboreal palms have developed a variety of structural root modifications and systems to adapt to the<br> harsh abiotic conditions of tropical rain forests. Stilt roots have been proposed to serve a number of functions<br> including the facilitation of rapid vertical growth to the canopy and enhanced mechanical stability. To examine<br> whether stilt roots provide these functions, we compared stilt root characteristics of the neotropical palm tree<br> Socratea exorrhiza on sloped (>20º) and flat locations at two lowland neotropical sites. S. exorrhiza (n=80 trees)<br> did not demonstrate differences in number of roots, vertical stilt root height, root cone circumference, root cone<br> volume, or location of roots as related to slope. However, we found positive relationships between allocation<br> to vertical growth and stilt root architecture including root cone circumference, number of roots, and root cone<br> volume. Accordingly, stilt roots may allow S. exorrhiza to increase height and maintain mechanical stability<br> without having to concurrently invest in increased stem diameter and underground root structure. This strategy<br> likely increases the species ability to rapidly exploit light gaps as compared to non-stilt root palms and may also<br> enhance survival as mature trees approach the theoretical limits of their mechanical stability.</p>
Figures from: A Saharan fossil and the dawn of Neotropical armoured catfishes in Gondwana
<p>This repository contains high-resolution versions of the figures from the manuscript by Paulo M. Brito et al., "A Saharan fossil and the dawn of Neotropical armoured catfishes in Gondwana"</p>
Frugivoria: an open trait database of birds and mammals exhibiting frugivory in moist montane Neotropical forest
Biodiversity in many areas is rapidly shifting and declining as a consequence of global change. As such, there is an urgent need for new tools and strategies to help identify, monitor, and conserve biodiversity hotspots. One way to identify these areas is by quantifying functional diversity, which measures the unique roles of species within a community and is valuable for conservation because of its relationship with ecosystem functioning. Unfortunately, the functional trait information required to evaluate functional diversity is often lacking and is difficult to harmonize across disparate data sources. Biodiversity hotspots are particularly lacking in this information. To address this knowledge gap, we compiled Frugivoria, a trait database containing dietary, life-history, and morphological traits as well as IUCN conservation status, for mammals and birds exhibiting frugivory, which are important for seed dispersal, an essential ecosystem service. Accompanying Frugivoria is an open workflow that harmonizes trait and taxonomic data from disparate sources and enables users to analyze traits in space. This version of Frugivoria encompasses species in moist montane forests of Central and South America. Compared with existing trait databases, Frugivoria adds 25 species (reclassifying 199 to align with the most recent taxonomic changes), adds new traits such as observed and inferred range size, habitat specialization, and body size, and also fills gaps in trait categories from other databases such as diet category, home range size, generation time, and longevity. Overall, Frugivoria adds 2,045 new trait values for mammals and 4,022 for birds, and includes a total of 17,454 trait entries with minimums and maximums reported for certain traits. Frugivoria and its workflow enables researchers to quantify relationships between traits and the environment, as well as spatial trends in functional diversity, contributing to basic knowledge and applied conservation of frugivores
Figures 1-7 in Pentatomiana beckerae gen. nov. and sp. nov., a new Neotropical Pentatomini (Hemiptera, Heteroptera, Pentatomidae)
Figures 1-7. Pentatomiana beckerae sp. nov.: (1) holotype; (2) right hemelytron of male paratype; (3-5) pygophore, respectively dorsal, caudal and ventral views.; (6-7) genital plates, respectively lateral and ventral views. (dr) Dorsal rim, (gc8) gonocoxite 8, (gc9) gonocoxite 9, (gcp) genital cup process, (la8) laterotergite 8, (la9) laterotergite 9, (pa) paramere, (VII) seventh segment, (vr) ventral rim, (X) tenth segment.Figures 3-5 and 6-7 respectively, in same scale.
Fig. 3 in Genetic diversity and population structure of Brycon nattereri (Characiformes: Bryconidae): a Neotropical fish under threat of extinction
Fig. 3. Haplotype network based on partial sequencing of the D-loop region (mtDNA) of 92 individuals of Brycon nattereri from the Laranjinha River. Circle sizes are pro- portional to haplotype frequency.
Fig. 3 in Water temperature affects aggressive interactions in a Neotropical cichlid fish
Fig. 3. Mean ± SE of initial (third day) and final (eighth day) frequencies of a. restrained aggression and b. overt aggression of group-housed fish. Different letters show differences among treatments. Mixed Model ANOVA completed by Fisher-LSD post hoc test.
Fig. 1 in Temperature affects the hypoxia tolerance of neotropical Cichlid Geophagus brasiliensis
Fig. 1. Malate Dehydrogenase enzyme activity of Geophagus brasiliensis exposed to normoxic (90% oxygen saturation) and hypoxia (20% oxygen saturation) conditions for 8 hours at 20°C, 24°C and 28°C. a. in liver; b. in white muscle; and c. in heart. Asterisks indicates significant differences between treatments at the same temperature, p <0.05. Different lowercase letters indicate significant differences for the same treatment at the temperatures studied, p <0.05.
Fig. 3 in Temperature affects the hypoxia tolerance of neotropical Cichlid Geophagus brasiliensis
Fig. 3. Citrate Synthase enzyme activity of Geophagus brasiliensis exposed to normoxic (90% oxygen saturation) and hypoxic (20% oxygen saturation) conditions for 8 hours at 20°C, 24°C and 28°C. a. in liver; b. in white muscle; and c. in heart. Asterisks indicates significant differences between treatments at the same temperature, p <0.05. Different lowercase letters indicate significant differences for the same treatment at the temperatures studied, p <0.05.
Figure 11 in New tribes, overview and checklist of Neotropical Cladonotinae (Orthoptera: Caelifera: Tetrigidae)
Figure 11. Haitianotettix tuberculatus Perez-Gelabert, Hierro and Otte, 1998, holotype of Haitianotettix monstruosus Perez-Gelabert, Hierro and Otte, 1998. A) Left lateral view. B) Right lateral view. C) Dorsal view. D) Frontal view. E) Labels. Scale bar = 0.5 cm.
Figure 4 in New tribes, overview and checklist of Neotropical Cladonotinae (Orthoptera: Caelifera: Tetrigidae)
Figure 4. Choriphyllum bahamensis Perez-Gelabert and Otte, 1999, paratype male. A) Left lateral view. B) Dorsal view. C) Frontal view. D) Labels. Photos by Kyle E. Schnepp (FSCA).
Figure 20 in New tribes, overview and checklist of Neotropical Cladonotinae (Orthoptera: Caelifera: Tetrigidae)
Figure 20. Cota strumosa Bolívar, 1887, lectotype male. A) Left lateral view. B) Dorsal view with labels. Photos by Josip Skejo (MNCN).
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Allen Brain Atlas
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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.
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