This month’s issue features articles on evaluating biodiversity offsetting, managing remotely-collected data, quantifying log decay and much more.
Senior Editor Aaron Ellison has selected six featured articles this month – find out about them below. We also have three Applications and seven articles that are freely available to everyone – no subscription required!
embarcadero (Application): Bayesian additive regression trees are a powerful machine learning approach that has yet to be applied to species distribution modelling. Here, Colin J. Carlson introduces embarcadero, an R package of convenience tools for species distribution modelling with Bayesian additive regression trees. To show how embarcadero can be used by ecologists, the workflow is demonstrated on a virtual species distribution model. Free access
Evaluating biodiversity offsetting: Biodiversity offsetting involves balancing ecological damage with restoration and protection elsewhere. Uncomplicated, quantitative approaches to spatial analysis of offsets are rare, and their use is often restricted by availability of suitable spatial data. Here, Moilanen et al. describe a practical method for evaluating offsetting proposals, tested on the boreal forests of Finland but applicable to biomes around the world. Open access
FunctionInk: The increasing amount of data in biology has prompted the development of multidimensional networks, where dimensions reflect the multiple qualitative properties of nodes and links. To facilitate their interpretation, communities can be detected; sets of nodes sharing certain properties. Here, Pascual García & Bell develop a method that detects two types of communities – modules and guilds – and show, with examples, that detection of functional groups uncovers information about how disparate ecological communities operate.
Wood and bark decay rates: The importance of wood decay for carbon and nutrient cycles is widely recognised, but relatively little is known about decay dynamics. Decay rates of logs are often quantified as loss in tissue density, yielding large underestimates. Chang et al. have developed a more accurate method of measuring mass loss in both bark and wood, finding that bark decomposed faster than wood in 20 species tested. Open access
epiRADseq for population genomics: Crotti et al. tested the robustness of epiRADseq data for population genomics, using datasets from European whitefish and corals. Single nucleotide polymorphisms from epiRADseq and ddRADseq were highly similar, and equivalent for estimating genetic diversity and population structure. This finding is useful for researchers interested in obtaining genetic and epigenetic data from organisms using one method. Open access
AMMonitor (Application): Ecological research programs are increasingly using autonomous monitoring units to collect large volumes of acoustic and photo data. The data management requirements are often overwhelming, with a considerable amount of processing to translate raw data into models and analyses. Therefore, Balantic & Donovan have created AMMonitor, an R package for simplifying the process of moving from raw, remotely collected data to analysis and results. Free access
We have three Applications articles in this issue. Two of them have been covered in our Featured Articles above, so here is number three.
smartR (Application) A spatial‐explicit approach to the management of demersal fishing effort could protect essential fish habitats and minimise the impact of trawlers on areas where juveniles of commercial species concentrate. smartR provides an R package for spatial modelling of fisheries and scenario simulation of management strategies. Its data‐driven model implements a spatially explicit bio‐economic model to edit and format the raw fisheries data, construct and maintain coherent datasets, simulate management scenarios and forecast the possible effects in terms of resources status and economic performances of the fleets. Free access
Other open access articles
Count transformation models: The effect of explanatory environmental variables on a species’ distribution is often assessed using a count regression model. Siegfried & Hothorn propose a novel framework of linear models for count data, which applies a transformation that is estimated from the data (not defined a priori) and the exact discrete likelihood is optimised for parameter estimation and inference. The models are more flexible than Poisson or negative binomial models but still maintain interpretability of multiplicative effects. Open access
The Log on the Cover
“The fallen petals are not as cruel as they seem; they fertilise those in full bloom instead.” ‐ Gong Zizhen (Qing Dynasty).
This issue’s cover shows Hypholoma fungus growing on a decaying log in Pacific Spirit Regional Park, Canada. Both bark and wood decomposition are vital processes in global carbon and nutrient cycles, and the ability to accurately estimate the decay rates of each log component is important. In their article, Chang et al. present a user‐friendly method for quantifying bark and wood volume loss during decomposition, and percentage reduction of bark cover. Results can be compared with those based on the prevalent decay class classification method, making it possible to understand woody debris decay dynamics across species at regional and global scales. To read more about this article, Chenhui Chang discusses the paper in this blog post.
Photo credit: ©Liam Coleman