223 research outputs found
Seal Molt Model
No full text<p>Programs for fitting progress of molt in elephant seals, written in C++. THe program should work on a Linux system as is, using the data included, but knowledge of C++ and Bayesian statistics are necessary to understand the output or adapt the code. The program fits a logistic curve to observations that increase from 0 to 100% molt for multiple individuals across multiple years. Individual logistic parameters are fitted to a hyperdistribution across years and animals. </p>
<p>Files with extension .h or .cpp contain the code:<br>1) modelMolt.h defines the molt class and runs all calculations, and includes subroutines in header files<br>2) utilities.cpp has commonly used subroutines<br>3) util.h has commonly used subroutines<br>4) Array2D.h is used within subroutines<br>5) likelihood.h has common likelihood functions for statistical calculations<br>6) statistics.h has common statistical functions<br>7) randomgenerator.h has a random number generator<br>8) modelMolt.cpp has the main function, accepting command-line parameters and executing a complete run</p>
<p><br>The file FemaleMolt.csv has sample data. It includes 4 tab-delimited columns:<br>1) animalID is an arbitrary identifier of individuals, always an integer<br>2) year is an integer<br>3) yday is day of the year, with 1=1Jan, treated as a double<br>4) molt is observation of the molt status of the given animal on the given day, always in [0,100], a double</p>
<p>The first 7 rows of data showing observed molt progress in animal 44168 in year 2016:<br>animalID year yday molt<br>44168 2016 126 0<br>44168 2016 129 0<br>44168 2016 130 0<br>44168 2016 137 0<br>44168 2016 139 5<br>44168 2016 146 15<br>44168 2016 171 100</p>
<p><br>To illustrate compilation, assume file #8 and the data file are in a folder FOLDERNAME. The following creates an executable program in FOLDERNAME:<br>> cd FOLDERNAME<br>> g++ -Wall modelMolt.cpp -o modelMolt.exe</p>
<p>Before compiling, edit lines 103-104 in modelMolt.h. They identify the folder to which results will be written. Those should be renamed as needed, and both folders must be created before executing. Then, to execute a run for 4000 steps, showing results every 500 steps, with output files named OUTPUT within those folders:<br>> ./modelMolt.exe FOLDERNAME FemaleMolt 4000 500 1 OUTPUT</p>
<p>There is one output file showing all parameter estimates of the Gibbs chain for every individual animal within the folder named 'pathFemale' (line 104). There are files of parameters for each year and grand hyperparameters within the folder named 'path' (line 103). Each file has 4000 rows for the 4000 steps chosen at run time.</p>
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Marker rescue mapping of the combined Condit/Dales collection of temperature-sensitive vaccinia virus mutants
No full textAbstractComplementation analysis of the combined Condit/Dales collection of vaccinia virus temperature-sensitive mutants has been reported (Lackner, C.A., D'Costa, S.M., Buck, C., Condit, R.C., 2003. Complementation analysis of the Dales collection of vaccinia virus temperature-sensitive mutants. Virology 305, 240–259), however not all complementation groups have previously been assigned to single genes on the viral genome. We have used marker rescue to map at least one representative of each complementation group to a unique viral gene. The final combined collection contains 124 temperature-sensitive mutants affecting 38 viral genes, plus five double mutants
Adaptive gene amplification as an intermediate step in the expansion of virus host range.
No full textThe majority of recently emerging infectious diseases in humans is due to cross-species pathogen transmissions from animals. To establish a productive infection in new host species, viruses must overcome barriers to replication mediated by diverse and rapidly evolving host restriction factors such as protein kinase R (PKR). Many viral antagonists of these restriction factors are species specific. For example, the rhesus cytomegalovirus PKR antagonist, RhTRS1, inhibits PKR in some African green monkey (AGM) cells, but does not inhibit human or rhesus macaque PKR. To model the evolutionary changes necessary for cross-species transmission, we generated a recombinant vaccinia virus that expresses RhTRS1 in a strain that lacks PKR inhibitors E3L and K3L (VVΔEΔK+RhTRS1). Serially passaging VVΔEΔK+RhTRS1 in minimally-permissive AGM cells increased viral replication 10- to 100-fold. Notably, adaptation in these AGM cells also improved virus replication 1000- to 10,000-fold in human and rhesus cells. Genetic analyses including deep sequencing revealed amplification of the rhtrs1 locus in the adapted viruses. Supplying additional rhtrs1 in trans confirmed that amplification alone was sufficient to improve VVΔEΔK+RhTRS1 replication. Viruses with amplified rhtrs1 completely blocked AGM PKR, but only partially blocked human PKR, consistent with the replication properties of these viruses in AGM and human cells. Finally, in contrast to AGM-adapted viruses, which could be serially propagated in human cells, VVΔEΔK+RhTRS1 yielded no progeny virus after only three passages in human cells. Thus, rhtrs1 amplification in a minimally permissive intermediate host was a necessary step, enabling expansion of the virus range to previously nonpermissive hosts. These data support the hypothesis that amplification of a weak viral antagonist may be a general evolutionary mechanism to permit replication in otherwise resistant host species, providing a molecular foothold that could enable further adaptations necessary for efficient replication in the new host
Neighbours consistently influence tree growth and survival in a frequently burned open oak landscape
No full textThe 16-ha Cedar Creek plot had all trees at least 2 cm dbh measured every 5 years from 1990 to 2015. Additional censuses were carried out every year, but trees were only checked for survival in those intervening censuses. The six growth censuses are thus numbered 1, 6, 11, 16, 21, 26. Data included here were used in Davis and Condit (2022). More details on methods and other uses of the data appear Davis (2021) and Davis et al. (1997, 2005).
References
Davis, M. A., Duke, A., Ibsen, T., Tran, H., and Rhodes, R. 1997. Spatial Distribution of Penstemon grandiflorus(Nutt.) and Geomys bursarius in a fragmented oak woodland in Minnesota, USA. Natural Areas Journal 17:136-143.
Davis, M. A., Curran, C., Tietmeyer, A., and Miller, A. 2005. Dynamic tree aggregation patterns in a species-poor temperate woodland disturbed by fire. Journal of Vegetation Science 16: 167-174.
Davis, M. A. 2021. Twenty-five years of tree demography in a frequently burned oak woodland: implications for savanna restoration. Ecosphere 2(12):e03844. 10.1002/ecs2.3844.
Davis, M. A., Condit R. 2022. Neighbors consistently influence tree growth and survival in a frequently burned open oak landscape. Journal of Ecology, in press.The 16-ha Cedar Creek plot had all trees at least 2 cm dbh measured every 5 years from 1990 to 2015. Additional censuses were carried out every year, but trees were only checked for survival in those intervening censuses. The six growth censuses are thus numbered 1, 6, 11, 16, 21, 26.
Summary Results: We present four short tables in pdf format with median growth and survival rates as a function of density. Detailed legends for each table appear in the pdf.
Table 1. Median growth rate of bur oak vs. neighborhood density, both conspecific and heterospecific. Densities were binned into four categories, giving 16 combinations and clearly separating effects of conspecifics and heterospecifics. Growth rate decline consistently with density, moreso with conspecifics than heterospecifics. Growth is transformed with the equation given the the text.
Table 2. Growth rate of pin oak vs. neighborhood density, as in Table 1. Growth rate declined with conspecific density, but not heterospecific.
Table 3. Five-year survival rates of bur oak vs. neighborhood density, as in Tables 1-2. Survival rates increased sharply with density of neighbors, especially conspecifics, and trees in the highest density categories had extremely low death rates.
Table 4. Five-year survival rates of pin oak vs. neighborhood density, as in Table 3. Survival rates increased sharply with density of neighbors, especially heterospecifics, and trees in the highest density categories had extremely low death rates.
FullPlot Data: The main data includes tables of all trees, stems, and environmental variables. These were the basis of all analyses in Davis and Condit (2022), as well as Tables 1-4 above. The three tables are in tab-delimited ascii format: 1) Trees, 2) Stems, 3) Environment. The README file has a full description of every column in the tables.Funding provided by: Division of Environmental BiologyAward Number: BSR/8717847Funding provided by: Division of Environmental BiologyAward Number: DEB/0208125Funding provided by: Division of Environmental BiologyAward Number: DEB/9419922Funding provided by: Division of Environmental BiologyAward Number: DEB/9873673See references under abstract
Annual dendrometer data from the Barro Colorado Island 50-ha forest dynamics plot for 2015-2020
No full textPlease cite these data as
Ramos, Pablo, Paulino Villareal, Richard Condit, KC Cushman, and Helene C. Muller-Landau. 2022. Annual dendrometer data from the Barro Colorado Island 50-ha forest dynamics plot for 2015-2020. Smithsonian Figshare. DOI 10.25573/data.19985066
Corresponding author: Helene C. Muller-Landau, [email protected]
These are data from recensuses of dendrometer bands on selected trees on the Barro Colorado Island 50 ha forest dynamics plot, part of the Smithsonian ForestGEO network of large forest dynamics plots.
They appear in the form in which they were used by Jessica F. Needham in analyses for the following publication:
Needham, J.F., Arellano, G., Davies, S.J., Fisher, R.A., Hammer, V., Knox, R., Mitre, D., Muller-Landau, H.C., Zuleta, D., and Koven, C.D. Tree crown damage and its effects on forest carbon cycling in a tropical forest. 2022. Global Change Biology.
The data archived here are for six dendrometer censuses that took place in the late wet seasons of 2015 (census 16), 2016 (census 18), 2017 (census 20), 2018 (census 22), 2019 (census 23), and 2020 (census 24).
Contributions:
Research design and supervision: Helene C. Muller-Landau
Data collection: Pablo Ramos, Paulino Villareal
Database design and curation procedure: Richard Condit, Helene C. Muller-Landau, Anudeep Singh
Calculation of diameter with correction for curvature: Matteo Detto, Helene C. Muller-Landau
Data QAQC (quality assurance and quality control): Helene C. Muller-Landau, Pablo Ramos, Richard Condit, KC Cushman, Adam Collins, Pete Kerby-Miller, Suzanne Lao.
Funding: The BCI 50 ha plot dendrometer data collection was initiated with funding from the HSBC Climate Partnership (2007-2011) and was continued with funding from the Smithsonian Institution ForestGEO program.
This study was located within and enabled by the Barro Colorado 50-ha plot.
The data for the main censuses of this plot through 2015 are available in the following data publication:
Condit R., Perez, R., Aguilar, S., Lao, S., Foster, R., Hubbell, S.P. 2019. Complete data from the Barro Colorado 50-ha plot: 423617 trees, 35 years, 2019 version. https://doi.org/10.15146/5xcp-0d46.
Trees were selected in a size-stratified and spatially stratified design, as detailed below.
100 40x40 m subplots were placed randomly across the plot, with the constraint that these plots were nonoverlapping and that their edges aligned with the edges of 20x20 m quadrats. The centers of these plots, in 50 ha plot coordinates (units of meters), are given in the file “bci40x40sxy.txt”, included as part of this repository. All trees with a dbh (diameter at 1.3 m or above buttresses) of 80 cm or larger were included throughout the plot. Trees with a dbh of 40-80 cm were included if they were located within the 40x40 m subplots. Trees with a dbh of 20-40 cm were included if they were located within 20x20 m subplots centered within the 40x40 m subplots. Trees with a dbh of 10-20 cm were included if they were located within 10x10 m subplots centered within the 40x40 m subplots. Trees with a dbh of 5-10 cm were included if they were located within 5x5 m subplots centered within the 40x40 m subplots. (Here, dbh of 5-10 cm means dbh greater than or equal to 5 cm, and less than 10 cm, and so forth.)
The initial sample was selected in 2007 (based on the 2005 census data), and new recruits into the spatially and size-stratified sample were added after each main plot census (main plot censuses in 2010, 2015). In adding trees to the initial census based on the 2005 census data, the size threshold for checking trees was lower than the size threshold for inclusion, to try to insure that trees that had grown into the size class since the 2005 census were included. Some selected trees were not appropriate for installation of dendrometers for one or more of the following reasons: palms (excluded because they do not generally grow in diameter), strangler figs (form too irregular for band dendrometers to provide useful information about woody growth), very large buttresses which would require a band being placed above 7.6 m (not possible to safely place and remeasure bands at this height with the available ladder and personnel), or large lianas or strangler figs affixed so closely to the trunk that a band could not be placed underneath them and that a band above them would not provide useful information on tree growth. In the case of multi-stemmed individuals, bands were placed on all stems above 5 cm if the biggest stem qualified for inclusion, and smaller stems were measured with calipers.
Dendrometer censuses were initially conducted twice per year, at the beginning of the wet season (May-June) and end of the wet season (November-December). However, the early wet season censuses often showed shrinkage of trees from the previous late wet season measurements. Biweekly remeasurements of another smaller sample of trees on the nearby AVA plot showed that dry season shrinkage was common in many trees, and that many did not recover to their previous dbh until well into the wet season. Thus for the purposes of annual growth measurements, it was decided to abandon the early wet season measurements starting in 2019.
Tree measurements and observations followed the protocol at https://figshare.com/s/00d6ba1e9f113bcf3ac3
The calculation of dbh from the band dendrometer data follows the procedure described at
https://figshare.com/s/43e3375f6614253a8bdd</p
Complete Tree Species of Panama
No full text<p>1 June 2020</p>
<p>This data archive presents a complete compilation of the tree species of Panama, including the full geographic range and local abundance of each. The species list is based on the most recent monographs, especially the Flora Mesoamericana, along with herbarium records, especially those online at the Missouri Botanic Garden, and our tree census plots, mostly in the forests around the Panama Canal, including the 50 ha plot at Barro Colorado. The full set of occurrence records was collected from the BIEN database and from Tropicos (Missouri Botanical Garden), plus our tree plots, and a geographic range was calculated as the minimum convex polygon around all occurrences. Details of methods can be found in Condit et al. (2020), and that paper includes a complete bibliography of the taxonomic literature consulted.</p>
<p>Species were included based if they root in the ground as free-standing woody plants, and reach a height of at least 3 m as reproductives. Epiphytes, lianas, and herbs were excluded. Species were included broadly, thus even if only occasionally terrestrial and free-standing while usually not; this aspect forces a loose gray area between trees and non-trees. The category shrub or descriptor shrubby were never considered, as they are poorly defined and used in inconsistent ways. An online version of the database (http://conditdatacenter.tech/PanamaTrees/) includes range maps and notes on growth form for marginal species. Tables of all coordinates from BIEN and Tropicos used in the estimates of range size can be downloaded from http://conditdatacenter.tech/TreeMap/txt.</p>
<p>References</p>
<ul>
<li>Condit, R., Perez, R., Aguilar, S. 2020. Tree species of Panama: a complete checklist with every geographic range. In press.</li>
<li>Condit, R., Engelbrecht, B. M. J., Pino, D., Pérez, R., and Turner, B. L. 2013. Species distributions in response to individual soil nutrients and seasonal drought across a community of tropical trees. Proceedings of the National Academy of Sciences 110:5064–5068. pdf http://conditdatacenter.org/pdfs/ConditEtAlPNAS2013.pdf</li>
<li>Condit, R., Chisholm, R. A., and Hubbell, S. P. 2012. Thirty years of forest census at Barro Colorado and the importance of immigration in maintaining diversity. PLoS ONE 7:e49826. pdf http://conditdatacenter.org/pdfs/ConditChisholmHubbell2012.pdf</li>
<li>Condit, R., Pérez, R., Aguilar, S., Lao, S., and Hubbell, S. P. 2017. Demographic trends and climate over 35 years in the Barro Colorado 50 ha plot. Forest Ecosystems 4:1–13. pdf http://conditdatacenter.org/pdfs/Condit_et_al-2017-Forest_Ecosystems.pdf</li>
<li>Davidse, G. M.; Sousa, M. S.; Knapp, S.; Chiang, F. & Ulloa, C. U. (Eds.) 1994-2018. Flora Mesoamericana (6 Volumes).</li>
</ul><p>Table 1. PanamaTreeSpecies.tsv. A tab-delimited ascii table including a record for 3045 tree species we consider native to Panama. Taxa in the table are identified by the Family, Latin name, and taxonomic authority, and include the following columns of data:</p>
<ul>
<li>countries -- Number of countries observed, ostensibly in a natural state (countries)</li>
<li>minLat -- Minimum latitude of species occurrences</li>
<li>maxLat -- Maximum latitude</li>
<li>minLong -- Minimum longitude</li>
<li>maxLong -- Maximum longitude</li>
<li>Npan -- Number of those records in Panama</li>
<li>N -- Total number of records in combined BIEN and Tropicos databases, counting only unique locations</li>
<li>range -- Extent of range, in thousands of square km, calculated as minimum convex polygon around BIEN records</li>
<li>plots -- Number of our tree plots in Panama in which the species was observed</li>
<li>dens -- Mean density in the plots (including zeroes) </li>
<li>inventories -- Number of our tree inventories in Panama in which the species was observed</li>
<li>maxht -- Maximum height in meters according to taxonomic monographs</li>
</ul>
<p>Table 2. PanamaTreeNameLookup.tsv. A tab-delimited ascii table including a record for 4497 Latin names which we found to be associated with the native tree species of Panama, including the 3045 currently accepted names plus 1452 alternate names. These are the most relevant recent synonyms, those appearing in recent treatments, at BIEN, or at Tropicos. For the 3045 current names, the column ValidLatin matches the column Latin. For the other 1452, the name in the column Latin is not valid in Panama and should be replaced by ValidLatin throughout the country. The column Scope applies to those 1452 cases: where Scope = everywhere, Latin should be replaced by ValidLatin everywhere the species is found, and Latin is now an obsolete name. In the remained 62 cases, where Scope = only Panama, the name Latin is misused in Panama and should be replaced there, but not elsewhere.</p>
<p>Table 3. PanamaTreeBIENError.tsv. A tab-delimited ascii table including 1035 tree species names appearing incorrectly in the BIEN database with records in Panama. All of these are based either on erroneous records, ie in the wrong country, or misidentified, or are based on cultivated specimens of species not native to Panama. </p>
Complete Tree Species of Panama
No full text<p>1 June 2020</p>
<p>This data archive presents a complete compilation of the tree species of Panama, including the full geographic range and local abundance of each. The species list is based on the most recent monographs, especially the Flora Mesoamericana, along with herbarium records, especially those online at the Missouri Botanic Garden, and our tree census plots, mostly in the forests around the Panama Canal, including the 50 ha plot at Barro Colorado. The full set of occurrence records was collected from the BIEN database and from Tropicos (Missouri Botanical Garden), plus our tree plots, and a geographic range was calculated as the minimum convex polygon around all occurrences. Details of methods can be found in Condit et al. (2020), and that paper includes a complete bibliography of the taxonomic literature consulted.</p>
<p>Species were included based if they root in the ground as free-standing woody plants, and reach a height of at least 3 m as reproductives. Epiphytes, lianas, and herbs were excluded. Species were included broadly, thus even if only occasionally terrestrial and free-standing while usually not; this aspect forces a loose gray area between trees and non-trees. The category shrub or descriptor shrubby were never considered, as they are poorly defined and used in inconsistent ways. An online version of the database (http://conditdatacenter.tech/PanamaTrees/) includes range maps and notes on growth form for marginal species. Tables of all coordinates from BIEN and Tropicos used in the estimates of range size can be downloaded from http://conditdatacenter.tech/TreeMap/txt.</p>
<p>References</p>
<ul>
<li>Condit, R., Perez, R., Aguilar, S. 2020. Tree species of Panama: a complete checklist with every geographic range. In press.</li>
<li>Condit, R., Engelbrecht, B. M. J., Pino, D., Pérez, R., and Turner, B. L. 2013. Species distributions in response to individual soil nutrients and seasonal drought across a community of tropical trees. Proceedings of the National Academy of Sciences 110:5064–5068. pdf http://conditdatacenter.org/pdfs/ConditEtAlPNAS2013.pdf</li>
<li>Condit, R., Chisholm, R. A., and Hubbell, S. P. 2012. Thirty years of forest census at Barro Colorado and the importance of immigration in maintaining diversity. PLoS ONE 7:e49826. pdf http://conditdatacenter.org/pdfs/ConditChisholmHubbell2012.pdf</li>
<li>Condit, R., Pérez, R., Aguilar, S., Lao, S., and Hubbell, S. P. 2017. Demographic trends and climate over 35 years in the Barro Colorado 50 ha plot. Forest Ecosystems 4:1–13. pdf http://conditdatacenter.org/pdfs/Condit_et_al-2017-Forest_Ecosystems.pdf</li>
<li>Davidse, G. M.; Sousa, M. S.; Knapp, S.; Chiang, F. & Ulloa, C. U. (Eds.) 1994-2018. Flora Mesoamericana (6 Volumes).</li>
</ul><p>Table 1. PanamaTreeSpecies.tsv. A tab-delimited ascii table including a record for 3045 tree species we consider native to Panama. Taxa in the table are identified by the Family, Latin name, and taxonomic authority, and include the following columns of data:</p>
<ul>
<li>countries -- Number of countries observed, ostensibly in a natural state (countries)</li>
<li>minLat -- Minimum latitude of species occurrences</li>
<li>maxLat -- Maximum latitude</li>
<li>minLong -- Minimum longitude</li>
<li>maxLong -- Maximum longitude</li>
<li>Npan -- Number of those records in Panama</li>
<li>N -- Total number of records in combined BIEN and Tropicos databases, counting only unique locations</li>
<li>range -- Extent of range, in thousands of square km, calculated as minimum convex polygon around BIEN records</li>
<li>plots -- Number of our tree plots in Panama in which the species was observed</li>
<li>dens -- Mean density in the plots (including zeroes) </li>
<li>inventories -- Number of our tree inventories in Panama in which the species was observed</li>
<li>maxht -- Maximum height in meters according to taxonomic monographs</li>
</ul>
<p>Table 2. PanamaTreeNameLookup.tsv. A tab-delimited ascii table including a record for 4497 Latin names which we found to be associated with the native tree species of Panama, including the 3045 currently accepted names plus 1452 alternate names. These are the most relevant recent synonyms, those appearing in recent treatments, at BIEN, or at Tropicos. For the 3045 current names, the column ValidLatin matches the column Latin. For the other 1452, the name in the column Latin is not valid in Panama and should be replaced by ValidLatin throughout the country. The column Scope applies to those 1452 cases: where Scope = everywhere, Latin should be replaced by ValidLatin everywhere the species is found, and Latin is now an obsolete name. In the remained 62 cases, where Scope = only Panama, the name Latin is misused in Panama and should be replaced there, but not elsewhere.</p>
<p>Table 3. PanamaTreeBIENError.tsv. A tab-delimited ascii table including 1035 tree species names appearing incorrectly in the BIEN database with records in Panama. All of these are based either on erroneous records, ie in the wrong country, or misidentified, or are based on cultivated specimens of species not native to Panama. </p>
Complementation Analysis of the Dales Collection of Vaccinia Virus Temperature-Sensitive Mutants
No full textAbstractA collection of randomly generated temperature-sensitive (ts) vaccinia virus (strain IHD-W) mutants were reported by S. Dales et al., (1978, Virology, 84, 403–428) in 1978 and characterized by electron microscopy. We have performed further genetic analysis on the Dales collection of mutants to make the mutants more useful to the scientific community. We obtained the entire Dales collection, 97 mutants, from the American Type Culture Center (ATCC). All 97 mutants were grown and reassessed for temperature sensitivity. Of these, 16 mutants were either very leaky or showed unacceptably high reversion indices even after plaque purification and therefore were not used for further analysis. The remaining 81 ts mutants were used to perform a complete complementation analysis with each other and the existing Condit collection of ts vaccinia virus (strain WR) mutants. Twenty-two of these 81 Dales mutants were dropped during complementation analysis due to erratic or weak behavior in the complementation test. Of the 59 mutants that were fit for further investigation, 30 fall into 13 of Condit's existing complementation groups, 5 comprise 3 previously identified complementation groups independent of the Condit collection, and 24 comprise 18 new complementation groups. The 59 mutants which were successfully characterized by complementation will be accessioned by and made available to the scientific community through the ATCC
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