One-dimensional fluids with second nearest-neighbor interactions

As is well known, one-dimensional systems with interactions restricted to first nearest neighbors admit a full analytically exact statistical-mechanical solution. This is essentially due to the fact that the knowledge of the first nearest-neighbor probability distribution function, $p_1(r)$, is enough to determine the structural and thermodynamic properties of the system. On the other hand, if the interaction between second nearest-neighbor particles is turned on, the analytically exact solution is lost. Not only the knowledge of $p_1(r)$ is not sufficient anymore, but even its determination becomes a complex many-body problem. In this work we systematically explore different approximate solutions for one-dimensional second nearest-neighbor fluid models. We apply those approximations to the square-well and the attractive two-step pair potentials and compare them with Monte Carlo simulations, finding an excellent agreement.Comment: 26 pages, 12 figures; v2: more references adde

Yakub_Tiffin_GCB_full_data_3oct_2016

phenotypic data on individual plant

Yakub_Tiffin_GCB_GBS_forarlequin

Variants identified by GBS and used for pop gen analyses (Dxy, Instruct

Recruitment data for experimental populations

Recruitment data for experimental populations of Chamaecrista fasciculata established in 2009 at 5 sites: interior (CERA), west edge (RNHA), north edge (SCRS), beyond west (CPBS) and beyond north (ACNW). At each site, I established 5 blocks with either 20 (interior and edge site) or 10 (beyond edge) experimental populations per block. Each experimental population consisted of 4 seeds from the same population. The experimental populations were planted in spring 2009 and survival and reproduction recorded. The plants, including seed pods, were left in the field. In June 2010, I returned to each site and recorded the number of seedlings found within 60cm of the center of each experimental population. The attached ReadMe file is the R script (R Project for Statistical Computing) that more fully explains the data and can be used to recreate the analysis included in the paper

Gorton_UrbanMS_Dryad

This zip file contains all data files and R code used for analyses in Gorton et al. 2018 "Little plant, big city: a test of adaptation to urban environments in common ragweed (Ambrosia artemisiifolia)". Each R script has meta-data at the top of each script

Online Appendix 5

The predictive posterior p-values for summary statistics simulated in goodness-of-fit tests of Populus trichocarpa and P. balsamifera divergence models

analysis script

R script for data analysis using CfE2_data.cs

Weather data for natural populations

Weather data needed for analysis of the natural populations. Data on total precipitation and average temperature during the growing season (1 May to 30 September) for each year from the weather station nearest to each site; either a weather station on site (IA and KS) or the nearest airport weather station (data downloaded from wunderground.com

Fitness data for experimental populations

Seeds were planted into 5 sites at different geographic range locations: the range interior (CERA), western edge (RNHA), northern edge (SCRS), beyond western edge (CPBS), beyond northern edge (ACNW). Because of poor germination, likely due to drought conditions in spring 2009, the first 5 blocks of the SCRS site were replanted in June and thus are included as a sixth site, SCRSb. Five plant seed source populations were used: Missouri (TYS), Kansas (KZA), Illinois (GRE), Iowa (CRA) and Minnesota (GCD). Eighty seeds at the interior and edge sites, and forty seeds at they beyond edge sites were planted into 10 blocks at each site. Within each block, 4 seeds from the same population were planted into experimental patches, with seeds located 20cm from each other in each patch, and a meter between patches. The patches were randomly assigned to either natural competition (competition) or reduced competition by neighbor removal (removal). Early-season survival, reproductive stage, plant height and leaf number at the middle of the season, and reproductive stage, height, and seed pod number were recorded. In early summer 2010, I returned to each site and recorded the number of seedlings recruiting into the 1 meter area surrounding each experimental patch (separate data file = CfE3_recruitment.csv). | DATA | id: plant identifier | site: site (see above) | block: block, 1-10 at each site | patch: patch within block. 1-20 at interior and edge sites, 1-10 at beyond edge sites | p.pos: position of seed within patch (4 positions, see Fig 1 in paper). | pop: seed source population (see above) | fam: seed source family within population. | esurv: early-season survival (0 - dead/not present, 1 - alive) | july.stage: life-history stage in July: 0 - dead/not present, 1 - vegetative, 2 - flowering, 3 - flower and pods, 4 - pods, 5 - completely senesced | july.height: height (cm) in July | july.leaf, leaf number in July | herbivory.category: percent category of leaf herbivory in July. 1: 0%, 2: 1-25%, 3: 26-75%, 4: 76-100% | For plants with <20 leaves, this was determined either by counting the number of leaves with herbivory, dividing by total leaves and placing in category. For plants with >20 leaves, the % category was visually estimated. | disease.category: percent category for disease in July. values same as herbivory | fall.stage: life-history stage at time of fall measurements, same as july.stage | branch.number: branch number at end of season | seed.pods: number of pods (counting pedicels where pods had broken off) | browsed: whether a plant was browsed. 0-not browsed, 1-plant browsed at some point in season (integrates across observation of browsing in July or at end-of-season) | The attached ReadMe file is the R script (R Project for Statistical Computing) that can be used to recreate the analysis performed in the paper

Appendix A. Supplementary tables containing population and transplant site information, and a figure of the life history stages included in the aster modeling.

Supplementary tables containing population and transplant site information, and a figure of the life history stages included in the aster modeling