More Like this

1. charisma: An R package to perform reproducible colour characterization of digital images for biological studies

   https://doi.org/10.1111/2041-210x.70310  

   Schwartz, Shawn T; Tsai, Whitney_L E; Karan, Elizabeth A; Juhn, Mark S; Shultz, Allison J; McCormack, John E; Smith, Thomas B; Alfaro, Michael E (June 2026, Methods in Ecology and Evolution)

   Abstract Advances in digital imaging and software tools have provided increasingly accessible datasets and methods for analysing colour evolution. Despite the variety of computational packages available, most rely on colour classification before running analyses. Previous methods to characterize colour limit the ability to analyse large‐scale image databases and are not always representative of biologically relevant colour classes, which decrease the accuracy of downstream analyses.Here, we presentcharisma, an R package designed to characterize the distribution of distinct colour classes in images suitable for large‐scale studies of biological organisms. We demonstrate the utility of our package through an analysis of colour evolution in a sample of diverse and charismatic birds, tanagers, in the subfamily Thraupinae.We show thatcharismacan quickly and accurately classify every pixel in an image and validate these results using pre‐identified, canonical colour swatches. We find thatcharismacolour classifications are consistent with those made by colour pattern experts in the field. Applyingcharismato tanager colour evolution, we find thatcharismaoutputs seamlessly integrate with downstream evolutionary analyses.Our results demonstrate that usingcharismato manually curate and characterize colours in images provides a standardized, reliable and reproducible framework for high‐throughput colour classification. 

   more » « less
2. neonSoilFlux: An R package for continuous sensor‐based estimation of soil CO₂ fluxes

   https://doi.org/10.1111/2041-210x.70216  

   Zobitz, John; Ayres, Edward; Werbin, Zoey; Abdi, Ridwan; Ashburner‐Wright, Natalie; Brown, Lillian; Frink‐Sobierajski, Ryan; Lee, Lajntxiag; Mehmeti, Dijonë; Tran, Christina; et al (December 2025, Methods in Ecology and Evolution)

   Abstract Accurate quantification of soil carbon fluxes is essential to reduce uncertainty in estimates of the terrestrial carbon sink. However, these fluxes vary over time and across ecosystem types and so, it can be difficult to estimate them accurately across large scales. The flux‐gradient method estimates soil carbon fluxes using co‐located measurements of soil CO₂concentration, soil temperature, soil moisture and other soil properties. The National Ecological Observatory Network (NEON) provides such data across 20 ecoclimatic domains spanning the continental U.S., Puerto Rico, Alaska and Hawai‘i.We present an R software package (neonSoilFlux) that acquires soil environmental data to compute half‐hourly soil carbon fluxes for each soil replicate plot at a given terrestrial NEON site. To assess the computed fluxes, we visited six focal NEON sites and measured soil carbon fluxes using a closed‐dynamic chamber approach.Outputs from theneonSoilFluxshowed agreement with measured fluxes (R²between measured andneonSoilFluxoutputs ranging from 0.12 to 0.77 depending on calculation method used); measured outputs generally fell within the range of calculated uncertainties from the gradient method. Calculated fluxes fromneonSoilFluxaggregated to the daily scale exhibited expected site‐specific seasonal patterns.While the flux‐gradient method is broadly effective, its accuracy is highly sensitive to site‐specific inputs, including the extent to which gap‐filing techniques are used to interpolate missing sensor data and to estimates of soil diffusivity and moisture content. Future refinement and validation ofneonSoilFluxoutputs can contribute to existing databases of soil carbon flux measurements, providing near real‐time estimates of a critical component of the terrestrial carbon cycle. 

   more » « less
3. SiPhyNetwork : An R package for simulating phylogenetic networks

   https://doi.org/10.1111/2041-210X.14116  

   Justison, Joshua A.; Solis‐Lemus, Claudia; Heath, Tracy A. (July 2023, Methods in Ecology and Evolution)

   Abstract Gene flow is increasingly recognized as an important macroevolutionary process. The many mechanisms that contribute to gene flow (e.g. introgression, hybridization, lateral gene transfer) uniquely affect the diversification of dynamics of species, making it important to be able to account for these idiosyncrasies when constructing phylogenetic models. Existing phylogenetic‐network simulators for macroevolution are limited in the ways they model gene flow.We presentSiPhyNetwork, an R package for simulating phylogenetic networks under a birth–death‐hybridization process.Our package unifies the existing birth–death‐hybridization models while also extending the toolkit for modelling gene flow. This tool can create patterns of reticulation such as hybridization, lateral gene transfer, and introgression.Specifically, we model different reticulate events by allowing events to either add, remove or keep constant the number of lineages. Additionally, we allow reticulation events to be trait dependent, creating the ability to model the expanse of isolating mechanisms that prevent gene flow. This tool makes it possible for researchers to model many of the complex biological factors associated with gene flow in a phylogenetic context. 

   more » « less
4. Stronger increase of methane emissions from coastal wetlands by non‐native Spartina alterniflora than non‐native Phragmites australis

   https://doi.org/10.1002/ppp3.10578  

   Fuchs, Andrea; Davidson, Ian C; Megonigal, J Patrick; Devaney, John L; Simkanin, Christina; Noyce, Genevieve L; Lu, Meng; Cott, Grace M (January 2025, PLANTS, PEOPLE, PLANET)

   Societal Impact StatementThe invasive speciesS. alternifloraandP. australisare fast growing coastal wetland plants sequestering large amounts of carbon in the soil and protect coastlines against erosion and storm surges. In this global analysis, we found thatSpartinaandPhragmitesincrease methane but not nitrous oxide emissions, withPhragmiteshaving a lesser effect. The impact of the invasive species on emissions differed greatly among different types of native plant groups, providing valuable information to managers and policymakers during coastal wetland planning and restoration efforts. Further, our estimated net emissions per wetland plant group facilitate regional and national blue carbon estimates. SummaryGlobally,Spartina alternifloraandPhragmites australisare among the most pervasive invasive plants in coastal wetland ecosystems. Both species sequester large amounts of atmospheric carbon dioxide (CO₂) and biogenic carbon in soils but also support production and emission of methane (CH₄). In this study, we investigated the magnitude of their net greenhouse gas (GHG) release from invaded and non‐invaded habitats.We conducted a meta‐analysis of GHG fluxes associated with these two species and related soil carbon content and plant biomass in invaded coastal wetlands.Our results show that both invasive species increase CH₄fluxes compared to uninvaded coastal wetlands, but they do not significantly affect CO₂and N₂O fluxes. The magnitude of emissions fromSpartinaandPhragmitesdiffers among native habitats. GHG fluxes, soil carbon and plant biomass ofSpartina‐invaded habitats were highest compared to uninvaded mudflats and succulent forb‐dominated wetlands, while being lower compared to uninvaded mangroves (except for CH₄).This meta‐analysis highlights the important role of individual plant traits as drivers of change by invasive species on plant‐mediated carbon cycles. 

   more » « less
5. swaRmverse: An R package for the comparative analysis of collective motion

   https://doi.org/10.1111/2041-210x.14460  

   Papadopoulou, Marina; Garnier, Simon; King, Andrew J (January 2025, Methods in Ecology and Evolution)

   Abstract Collective motion, that is the coordinated spatial and temporal organisation of individuals, is a core element in the study of collective animal behaviour. The self‐organised properties of how a group moves influence its various behavioural and ecological processes, such as predator–prey dynamics, social foraging and migration. However, little is known about the inter‐ and intra‐specific variation in collective motion. Despite the significant advancement in high‐resolution tracking of multiple individuals within groups, providing collective motion data for animals in the laboratory and the field, a framework to perform quantitative comparisons across species and contexts is lacking.Here, we present theswaRmversepackage. Building on two existing R packages,trackdfandswaRm,swaRmverseenables the identification and analysis of collective motion ‘events’, as presented in Papadopoulou et al. (2023), creating a unit of comparison across datasets. We describe the package's structure and showcase its functionality using existing datasets from several species and simulated trajectories from an agent‐based model.From positional time‐series data for multiple individuals (x‐y‐t‐id),swaRmverseidentifies events of collective motion based on the distribution of polarisation and group speed. For each event, a suite of validated biologically meaningful metrics are calculated, and events are placed into a ‘swarm space’ through dimensional reduction techniques.Our package provides the first automated pipeline enabling the analysis of data on collective behaviour. The package allows the calculation and use of complex metrics for users without a strong quantitative background and will promote communication and data‐sharing across disciplines, standardising the quantification of collective motion across species and promoting comparative investigations. 

   more » « less