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opencc-zeroNov 2020View details →

Data and R Code for publication: Should dispersers be fast learners? Modelling the role of cognition in dispersal

Both cognitive abilities and dispersal tendencies can vary strongly between individuals. Since cognitive abilities may help dealing with unknown circumstances it is conceivable that dispersers may rely more heavily on learning abilities than residents. However, cognitive abilities are costly and leaving a familiar place might result in losing the advantage of having learned to deal with local conditions. Thus, individuals which invested in learning to cope with local conditions may be more reluctant to leave their natal place. In order to disentangle the complex relationship between dispersal and learning abilities we implemented individual-based simulations. By allowing for developmental plasticity, individuals could either develop a "resident" or "dispersal" cognitive phenotype. In line with our expectations, the correlation between learning abilities and dispersal could take any direction, depending how much time individuals had to recoup their investment in cognition. Both, longevity and the timing of dispersal within lifecycles determine the time individuals have to recoup that investment and thus crucially influence this correlation. We therefore suggest that species' life-history will strongly impact the expected cognitive abilities of dispersers, relative to their resident conspecifics, and that cognitive abilities might be an integral part of dispersal syndromes.

opencc-zeroDec 2014View details →

Data from: PolyPatEx: an R package for paternity exclusion in autopolyploids

Microsatellite markers have demonstrated their value for performing paternity exclusion and hence exploring mating patterns in plants and animals. Methodology is well established for diploid species and several software packages exist for elucidating paternity in diploids, however these issues are not so readily addressed in polyploids due to the increased complexity of the exclusion problem and a lack of available software. We introduce PolyPatEx, an R package for paternity exclusion analysis using microsatellite data in autopolyploid, monoecious or dioecious/bisexual species with a ploidy of 4n, 6n or 8n. Given marker data for a set of offspring, their mothers, and a set of candidate fathers, PolyPatEx uses allele matching to exclude candidates whose marker alleles are incompatible with the alleles in each offspring-mother pair. PolyPatEx can analyse marker data sets in which allele copy numbers are known (genotype data) or unknown (allelic phenotype data) – for data sets in which allele copy numbers are unknown, comparisons are made taking into account all possible genotypes that could arise from the compared allele sets. PolyPatEx is a software tool that provides population geneticists with the ability to investigate the mating patterns of autopolyploids using paternity exclusion analysis on data from codominant markers having multiple alleles per locus.

opencc-zeroDec 2016View details →

Data from: Multi-DICE: R package for comparative population genomic inference under hierarchical co-demographic models of independent single-population size changes

Population genetic data from multiple taxa can address comparative phylogeographic questions about community-scale response to environmental shifts, and a useful strategy to this end is to employ hierarchical co-demographic models that directly test multi-taxa hypotheses within a single, unified analysis while benefiting in statistical power from aggregating datasets. This approach has been applied to classical phylogeographic datasets such as mitochondrial barcodes as well as reduced-genome polymorphism datasets that can yield 10,000s of SNPs, produced by emergent technologies such as RAD-seq and GBS. A strategy for the latter had been accomplished by adapting the site frequency spectrum to a novel summarization of population genomic data across multiple taxa called the aggregate site frequency spectrum (aSFS), which potentially can be deployed under various inferential frameworks including approximate Bayesian computation, random forest, and composite likelihood optimization. Here, we introduce the R package Multi-DICE, a wrapper program that exploits existing simulation software for straight-forward and flexible execution of hierarchical model-based inference using the aSFS, which is derived from genomic-scale data, as well as mitochondrial data. We validate several novel software features such as applying alternative inferential frameworks, enforcing a minimal threshold of time surrounding event pulses, and specifying flexible hyperprior distributions. In sum, Multi-DICE provides comparative analysis within the familiar R environment while allowing a high degree of user customization, and will thus serve as a valuable tool for comparative phylogeography and population genomics.

opencc-zeroDec 2016View details →

Data from: The NBS-LRR architectures of plant R-proteins and metazoan NLRs evolved in independent events

There are intriguing parallels between plants and animals, with respect to the structures of their innate immune receptors, that suggest universal principles of innate immunity. The cytosolic nucleotide binding site–leucine rich repeat (NBS-LRR) resistance proteins of plants (R-proteins) and the so-called NOD-like receptors of animals (NLRs) share a domain architecture that includes a STAND (signal transduction ATPases with numerous domains) family NTPase followed by a series of LRRs, suggesting inheritance from a common ancestor with that architecture. Focusing on the STAND NTPases of plant R-proteins, animal NLRs, and their homologs that represent the NB-ARC (nucleotide-binding adaptor shared by APAF-1, certain R gene products and CED-4) and NACHT (named for NAIP, CIIA, HET-E, and TEP1) subfamilies of the STAND NTPases, we analyzed the phylogenetic distribution of the NBS-LRR domain architecture, used maximum-likelihood methods to infer a phylogeny of the NTPase domains of R-proteins, and reconstructed the domain structure of the protein containing the common ancestor of the STAND NTPase domain of R-proteins and NLRs. Our analyses reject monophyly of plant R-proteins and NLRs and suggest that the protein containing the last common ancestor of the STAND NTPases of plant R-proteins and animal NLRs (and, by extension, all NB-ARC and NACHT domains) possessed a domain structure that included a STAND NTPase paired with a series of tetratricopeptide repeats. These analyses reject the hypothesis that the domain architecture of R-proteins and NLRs was inherited from a common ancestor and instead suggest the domain architecture evolved at least twice. It remains unclear whether the NBS-LRR architectures were innovations of plants and animals themselves or were acquired by one or both lineages through horizontal gene transfer.

opencc-zeroDec 2014View details →

Data from: Genetic differentiation and phylogeography of partially sympatric species complex Rhizophora mucronata Lam. and R. stylosa Griff. using SSR markers

Mangrove forests are ecologically important but globally threatened intertidal plant communities. Effective mangrove conservation requires the determination of species identity management units and genetic structure. Here we investigate the genetic distinctiveness and genetic structure of an iconic but yet taxonomically confusing species complex Rhizophora mucronata and R. stylosa across their distributional range by employing a suite of 20 informative nuclear SSR markers. Our results demonstrated the general genetic distinctiveness of R. mucronata and R. stylosa and potential hybridization or introgression between them. We investigated the population genetics of each species without the putative hybrids and found strong genetic structure between oceanic regions in both R. mucronata and R. stylosa. In R. mucronata a strong divergence was detected between populations from the Indian Ocean region (Indian Ocean and Andaman Sea) and the Pacific Ocean region (Malacca Strait South China Sea and Northwest Pacific Ocean). In R. stylosa the genetic break was located more eastward between populations from South and East China Sea and populations from the Southwest Pacific Ocean. The location of these genetic breaks coincided with the boundaries of oceanic currents thus suggesting that oceanic circulation patterns might have acted as a cryptic barrier to gene flow. Our findings have important implications on the conservation of mangroves especially relating to replanting efforts and the definition of ESUs in Rhizophora species. We outlined the genetic structure and identified geographical areas that require further investigations for both R. mucronata and R. stylosa. These results serve as the foundation for the conservation genetics of R. mucronata and R. stylosa and highlighted the need to recognize the genetic distinctiveness of closely-related species determine their respective genetic structure and avoid artificially promoting hybridization in mangrove restoration programmes.

opencc-zeroDec 2014View details →

Data from: An R package for analyzing survival using continuous-time open capture-recapture models

Capture–recapture software packages have proven to be very powerful tools for analysing factors affecting survival in wild populations. However, all such packages are limited to discrete-time protocols. Appropriate survival analysis tools are still lacking for data acquired from continuous-time protocols. We have developed a statistical method and propose an r package for analysing such data based on an extension of classical survival analysis models incorporating an inhomogeneous Poisson process for modelling capture histories. First, data were simulated from a continuous-time protocol. These data were used to (i) compare survival estimation biases of discrete- and continuous-time approaches and (ii) investigate the performance and accuracy of our r package for four types of covariates: factors varying between individuals (like sex), in time (like climatic factors), both in time and between individuals (like physical condition) and age (as a categorical factor). Secondly, the r package has been applied to a real data set for survival analysis of cats in the Kerguelen archipelago (regrouping 682 cats over 20 years) as an illustrative example. Results of the simulated data analysis show that the method performs better than its discrete-time counterpart for analysing data acquired from continuous-time protocols. It provides unbiased parameter estimates for all parameters except those that vary both in time and between individuals – which is not surprising, since in our case, these factors were not updated in continuous time (i.e. only upon capture). When applied to the Kerguelen cat data set, the results suggest that survival is lower in juveniles than in adults and subadults, varies between study sites and increases with physical condition, and this latter effect being more important in females than in males. Sex, season, temporal linear trend in survival and the NDVI vegetation index were also tested but were not found to be significant. However, confidence intervals were too large (due to a low recapture rate) for excluding such effects. Further analyses are still needed for rigorous covariate testing in this context. In conclusion, continuous-time approaches – such as that presented in this paper – should be preferred when data acquired from continuous-time protocols is analysed.

opencc-zeroDec 2011View details →

Data from: Clinal variation in colony breeding structure and level of inbreeding in the subterranean termites Reticulitermes flavipes and R. grassei

Social insects exhibit remarkable variation in their colony breeding structures, both within and among species. Ecological factors are believed to be important in shaping reproductive traits of social insect colonies, yet there is little information linking specific environmental variables with differences in breeding structure. Subterranean termites (Rhinotermitidae) show exceptional variation in colony breeding structure, differing in the number of reproductives and degree of inbreeding; colonies can be simple families headed by a single pair of monogamous reproductives (king and queen) or they can be extended families headed by multiple inbreeding neotenic reproductives (wingless individuals). Using microsatellite markers, we characterized colony breeding structure and levels of inbreeding in populations over large parts of the range of the subterranean termites Reticulitermes flavipes in the USA and R. grassei in Europe. Combining these new data with previous results on populations of both species, we found that latitude had a strong effect on the proportion of extended-family colonies in R. flavipes and on levels of inbreeding in both species. We examined the effect of several environmental variables that vary latitudinally; while the degree of inbreeding was greatest in cool, moist habitats in both species, seasonality affected the species differently. Inbreeding in R. flavipes was most strongly associated with climatic variables (mean annual temperature and seasonality), whereas nonclimatic variables, including the availability of wood substrate and soil composition, were important predictors of inbreeding in R. grassei. These results are the first showing that termite breeding structure is shaped by local environmental factors and that species can vary in their responses to these factors.

opencc-zeroDec 2016View details →

Data from: SIDER: an R package for predicting trophic discrimination factors of consumers based on their ecology and phylogenetic relatedness

Stable isotope mixing models (SIMMs) are an important tool used to study species' trophic ecology. These models are dependent on, and sensitive to, the choice of trophic discrimination factors (TDF) representing the offset in stable isotope delta values between a consumer and their food source when they are at equilibrium. Ideally, controlled feeding trials should be conducted to determine the appropriate TDF for each consumer, tissue type, food source, and isotope combination used in a study. In reality however, this is often not feasible nor practical. In the absence of species-specific information, many researchers either default to an average TDF value for the major taxonomic group of their consumer, or they choose the nearest phylogenetic neighbour for which a TDF is available. Here, we present the SIDER package for R, which uses a phylogenetic regression model based on a compiled dataset to impute (estimate) a TDF of a consumer. We apply information on the tissue type and feeding ecology of the consumer, all of which are known to affect TDFs, using Bayesian inference. Presently, our approach can estimate TDFs for two commonly used isotopes (nitrogen and carbon), for species of mammals and birds with or without previous TDF information. The estimated posterior probability provides both a mean and variance, reflecting the uncertainty of the estimate, and can be subsequently used in the current suite of SIMM software. SIDER allows users to place a greater degree of confidence on their choice of TDF and its associated uncertainty, thereby leading to more robust predictions about trophic relationships in cases where study-specific data from feeding trials is unavailable. The underlying database can be updated readily to incorporate more stable isotope tracers, replicates and taxonomic groups to further increase the confidence in dietary estimates from stable isotope mixing models, as this information becomes available.

opennotspecifiedDec 2011View details →

FIGURE 11 in Redescription of Rhodostrophia leni s Wiltshire 1966 and R. vartianae Wiltshire, 1966, with new distributional data (Lepidoptera, Geometridae, Sterrhinae)

FIGURE 11. Wing venation of R. lenis, terminology after Scoble (1995); figs 12–19. genitalia morphology and abdominal structures. R. lenis: 12, female genitalia (G. prep. 1532, Paratype); 13, male genitalia (G. prep. WW195, Holotype); 14, aedeagus (same preparation, Holotype); 15, sternite A-8 (G. prep. 1534, Paratype). R. vartianae: 16 & 17, valva (16: G. prep. 1531, Paratype) & (17: G. prep. 1533, Paratype); 18, aedeagus (G. prep. 1531, Paratype); 19, sternite A-8 (G. prep. 1531, Paratype).

opennotspecifiedDec 2011View details →

FIGURES 1–9 in Redescription of Rhodostrophia leni s Wiltshire 1966 and R. vartianae Wiltshire, 1966, with new distributional data (Lepidoptera, Geometridae, Sterrhinae)

FIGURES 1–9. Adults of R. lenis and R. vartianae: R. lenis (male): 1, upperside; 2, underside; 3, labels; R. lenis (female): 4, upperside; 5, underside; 6, labels; R. vartianae (male): 7, upperside; 8, underside; 9, labels. Fig. 10. Habitat of R. lenis. Kuh-e Sorkh (north of Kashmar, 2100 m a.s.l.), "sorkh" in Farsi means red, which refers to the color of the landscape, the habitat is covered mostly by Astragalus spp. (Fabaceae) (photo by Wolfgang ten-Hagen).

FIGURE 11. General aspect female genitalia. A, R in Revision of genus Repipta Stål 1859 (Hemiptera: Heteroptera: Reduviidae: Harpactorinae) with new species and distribution data

FIGURE 11. General aspect female genitalia. A, R. antica Stål, B, R. argentinensis sp. nov., C, R. ayelenae sp. nov., D, R. coccinea (Herrich-Schaeffer), E, R. costarrisensis sp. nov., F, R. ecuadorensis sp. nov., G, R. flavicans Amyot & Serville, H, R. fuscipes Stål, I, R. lepidula Stål, J, R. obscuripes Stål, K, R. paraguayensis sp. nov., L, R. schaeferi sp. nov., M, R. taurus (Fabricius), N, R. unispina sp. nov.

FIGURE 13. Gonocoxite IX. A, R in Revision of genus Repipta Stål 1859 (Hemiptera: Heteroptera: Reduviidae: Harpactorinae) with new species and distribution data

FIGURE 13. Gonocoxite IX. A, R. antica Stål, B, R. argentinensis sp. nov., C, R. ayelenae sp. nov., D, R. coccinea (Herrich- Schaeffer), E, R. costarrisensis sp. nov., F, R. ecuadorensis sp. nov., G, R. flavicans Amyot & Serville, H, R. fuscipes Stål, I, R. lepidula Stål, J, R. obscuripes Stål, K, R. paraguayensis sp. nov., L, R. schaeferi sp. nov., M, R. taurus (Fabricius), N, R. unispina sp. nov. Arrows refer to character under descriptions/redescriptions.

FIGURE 7. Lateral aspect. A, R in Revision of genus Repipta Stål 1859 (Hemiptera: Heteroptera: Reduviidae: Harpactorinae) with new species and distribution data

FIGURE 7. Lateral aspect. A, R. spinosa (Fabricius), B–C, R. taurus (Fabricius), male (left) and female (right), F, R. unispina sp. nov. Arrows refer to character under descriptions/redescriptions.

FIGURE 5. Lateral aspect. A, R in Revision of genus Repipta Stål 1859 (Hemiptera: Heteroptera: Reduviidae: Harpactorinae) with new species and distribution data

FIGURE 5. Lateral aspect. A, R. antica Stål, B–C, R. argentinensis sp. nov., male (left) and female (right), D, R. ayelenae sp. nov., E, R. brailovskyi sp. nov., F, R. brasiliensis sp. nov., G, R. coccinea (Herrich-Schaeffer), H, R. costarrisensis sp. nov., I, R. ecuadorensis sp. nov., J–K, R. flavicans Amyot & Serville, male (left) and female (right), L, R. fuscospinosa Stål. Arrows refer to character under descriptions/redescriptions.

FIGURE 4. General aspect. A, R in Revision of genus Repipta Stål 1859 (Hemiptera: Heteroptera: Reduviidae: Harpactorinae) with new species and distribution data

FIGURE 4. General aspect. A, R. spinosa (Fabricius), B, R. unispina sp. nov. Arrows refer to character under descriptions/ redescriptions. Scale 1mm.

FIGURE 2. General aspect. A, R in Revision of genus Repipta Stål 1859 (Hemiptera: Heteroptera: Reduviidae: Harpactorinae) with new species and distribution data

FIGURE 2. General aspect. A, R. ecuadorensis sp. nov., B–C, R. flavicans Amyot & Serville, male (left) and female (right), D, R. fuscospinosa Stål, E–F, R. fuscipes Stål, male (left) and female (right), G, R. hondurensis sp. nov., H, R. lepidula Stål, I, R. mucosa Champion. Arrows refer to character under descriptions/redescriptions. Scale 1mm.

FIGURE 3. General aspect. A, R in Revision of genus Repipta Stål 1859 (Hemiptera: Heteroptera: Reduviidae: Harpactorinae) with new species and distribution data

FIGURE 3. General aspect. A, R. nigronotata Stål, B, R. nigrospinosa sp. nov., C, R. obscuripes Stål, D, R. paraguayensis sp. nov., E, R. ruficorpus sp. nov., F, R. schaeferi sp. nov., G, R. sexdens (Fabricius), H–I, R. taurus (Fabricius), male (left) and female (right). Arrows refer to character under descriptions/redescriptions. Scale 1mm.

FIGURE 1. General aspect. A, R. annulipes Barber, B–C, R in Revision of genus Repipta Stål 1859 (Hemiptera: Heteroptera: Reduviidae: Harpactorinae) with new species and distribution data

FIGURE 1. General aspect. A, R. annulipes Barber, B–C, R. argentinensis sp. nov., male (left) and female (right), D, R. antica Stål, E, R. ayelenae sp. nov., F, R. brailovskyi sp. nov., G, R. brasiliensis sp. nov., H, R. coccinea (Herrich-Schaeffer), I, R. costarrisensis sp. nov. Arrows refer to character under descriptions/redescriptions. Scale 1mm.

openOct 2023View details →

Data, Metadata, R-codes and R data files for publication "Comparative ungulate diversity and biomass change with human use and drought: implications for community stability and protected area prioritization in African savannas" by Bartzke et al. in Ecology and Evolution

These files contain data and metadata for modeling ungulate diversity and biomass in the Maasai Mara ecosystem in Kenya in the drought year of 1999 and a year with normal rainfall, 2002. The files also contain R codes and R data files. Metadata.pdf: Metadata for files "mc_333m.csv" and "mc_1km.csv" mc_333m.csv: A data file for 333-meter-by-333-meter sub-blocks. prepare_data.r: R code to impute missing vegetation records in 333-meter-by-333-meter subblocks and summarize the data over 1-kilometer-by-1-kilometer blocks for analysis. krige_vegetation.RData: An R data file containing the imputed vegetation records. mc_1km.csv: A data file for 1-kilometer-by-1-kilometer blocks for analysis. mc_1km.r: R code for modeling ungulate diversity and biomass; mc_1km_mod.RData: An R data file for loading the ungulate diversity and biomass models. mc_1km.RData: An R data file containing model predictions of ungulate diversity and biomass. mc_1km_plots.r: R code for plotting model predictions of ungulate diversity and biomass. MMNR_boundary.shp: A shapefile of the Maasai Mara National Reserve boundary in Kenya and associated files. These files are used for plotting the predictions of ungulate diversity and biomass. MMNR_border.zip: A shapefile and associated files for the Maasai Mara National Reserve border with Tanzania. These files are also used for plotting predictions of ungulate diversity and biomass.