This issue contains the latest methods in ecology and evolution. Read to find out about this month’s featured articles and the article behind our cover!

Featured

Impact of acoustic index parameters on soundscape comparisons

Ecoacoustic indices are often used to characterise specific aspects of the acoustic environment. For several commonly used indices, the impacts of the parameter settings and sampling regimes on output values have not been fully explored, despite the potential to bias results. To address this, authors conducted three sensitivity analyses on acoustic index parameters. The analyses demonstrate that parameter selection alone can influence the magnitude and direction of difference between acoustic index outputs, in turn affecting comparative interpretation. These effects are also dependent on the soundscape data (e.g. sampling frequency, target frequency bands). In this study, authors provide insights into drivers of these effects and recommendations to better understand the implications of index variance for within- and between-study comparisons.

VANTAGE: An open‐source application for visualisation, navigation and analysis of video and ancillary time‐series data in bio‐logging studies

The deployment of animal-borne video cameras in addition to other time-series loggers has become popular in recent years. Such deployments generate large amounts of data that are often not synchronised and may be difficult to analyse. Here, authors present VANTAGE (Video Analysis and Navigation Tool for Advanced Graphical Exploration), a new open-source graphical user interface. VANTAGE aims to simplify time-consuming data processing and analyses through (1) concurrent visualisation of video footage and accompanying bio-logger time-series data, (2) temporal synchronisation of the different data streams, (3) efficient annotation across data types, and (4) video enhancement and machine learning functionalities.

EEMtoolbox: A user‐friendly R package for flexible ensemble ecosystem modelling

Ensemble ecosystem modelling (EEM) is a quantitative method used to parameterize models from theoretical ecosystem features rather than data. To facilitate the usage of EEM methods, authors introduce EEMtoolbox, an R package for calibrating quantitative ecosystem models. The package allows the generation of parameter sets satisfying ecosystem features by using either the standard accept–reject algorithm or the novel SMC procedure. The package extends the existing EEM methodology to two additional model structures and allows users to define their own model structures. With its simple interface, EEMtoolbox facilitates straightforward generation of EEM parameter sets, thus unlocking advanced statistical methods supporting conservation decisions using ecosystem network models.

A novel apparatus for studying fish cognition in the wild

There are few fish cognition studies that have been conducted in the field or with wild fish populations. Vila-Pouca et al. introduce a novel cognitive apparatus designed for fish in their natural habitats, demonstrating its efficacy by conducting two tests using a social foraging task. Results show that this low-cost, easy-to-adapt apparatus is effective for assessing a variety of cognitive abilities across different fish species. This study provides a starting point to test different aspects of fish cognition under natural conditions and can pave the way for examining in situ cognitive variation between species and populations exposed to different ecological conditions.

Handbook of protocols for standardized measurements of floral traits for pollinators in temperate communities

Floral traits describe organs or structures directly related to plant reproduction, and they are essential to understanding plant–pollinator interactions, notably for conservation purposes. The authors present a handbook of 24 standardized protocols dedicated to floral traits grouped into three categories: (visual and olfactory cues, accessibility and resources) that can be applied to a wide set of temperate plant species to quantify these traits at the scale of plant communities. They also provide four additional features related to flower abundance and phenology that they recommend measuring to scale up individual species’ trait values to overall plant communities.

Towards biologically realistic estimates of home range and spatial exposure for colonial animals

Authors propose a new Home Range (HR) estimation method for colonial animals that accounts for spatially complex interactions without computationally expensive individual-based modelling (IBM). The model for colony space uses the following mechanistic rules of (1) heterogeneous landscape permeability, (2) between- and within-colony density-dependent competition, (3) flexible definitions of overlap between colonies, and (4) secondary space use due to commuting. In contrast to industry-standard approaches, this method relies neither on exhaustive tracking from all colonies nor on computer-intensive IBMs. Rather, it can predict HRs from colony size estimates and locations and can be flexibly tuned to different species’ characteristics to investigate fundamental and applied questions on colonial space-use patterns.

Cover Image

This photo shows a freediver setting up a hydrophone for passive acoustic monitoring (PAM) near Lizard Island, Australia, as part of the Australian Coral Reef Resilience Initiative. PAM is emerging as a scalable tool for environmental surveying in both marine and terrestrial environments. PAM is often supported by ecoacoustic indices, which are intended to summarise soundscape data and provide useful ecological insights. Ecoacoustic indices, while widely utilised, are still a relatively new technique, and best practices for use are still in development. In their article, Kemp et al. show how parameter selection can affect index outputs in both absolute terms and for comparative PAM studies, potentially altering interpretation. Determining how sensitive a metric is to parameterisation with a given dataset is important for understanding the ecological validity of ecoacoustic studies. The authors present guidance for utilising sensitivity analyses in future work.

Read the article here.