Our December issue is online now! Our final issue of the year contains 16 fantastic articles about the latest methods in ecology and evolution.

This month we have methods for fine tuning biodiversity assessments, visual analysis of wood samples, analysing environmental audio recordings and much more! Read on to find out all about them.

Dealing with software complexity in individual‐based models *open access* Individual-based models are doubly complex: as well as representing complex ecological systems, the software that implements them is complex in itself. Both forms of complexity must be managed to create reliable models. However, the ecological modelling literature to date has focussed almost exclusively on the biological complexity. In this Perspective, Vedder et al. discuss methods for containing software complexity.

Fine‐tuning biodiversity assessments *open access* Accurate quantification of biodiversity can be demanding and expensive. Although environmental DNA (eDNA) metabarcoding can facilitate biodiversity assessments through non-invasive, cost-efficient and rapid surveys, the approach struggles to outperform traditional morphological approaches in providing reliable quantitative estimates for surveyed species. Here, Pereira et al. present an integrated methodology for improving biodiversity surveys that pairs eDNA metabarcoding with morphological data, following a series of taxonomic and geographical filters.

geomorph v4.0 and gmShiny Geometric morphometric (GM) tools are essential for meaningfully quantifying and understanding patterns of variation in complex traits like shape. In this field, the breadth of answerable questions has grown dramatically in recent years through the development of new analyses and increased computational efficiency. Here, Baken et al. present geomorph v4.0 and describe the ways in which this version has dramatically improved upon previous versions. They also present gmShiny, a new graphical user interface for easy implementation.

The Wood Image Analysis and Dataset Images of wood contain a wealth of information such as colours and textures but are most commonly reduced to ring-width measurements before they can be shared in various common file formats. Archiving digital images of wood samples in publicly-available libraries occurs rarely. In answer to this, Rademacher et al. have developed the Wood Image Analysis and Dataset, an open-source application including a web interface to integrate basic visual analysis of wood samples, such as increment cores, thin sections or X-ray films, basic data processing, and archiving of the images and derived data to facilitate transparency and reproducibility in studies using visual characteristics of wood.

Solving the sample size problem for resource selection functions Sample size sufficiency is a critical consideration for estimating resource selection functions (RSFs) from GPS-based animal telemetry. Cited thresholds for sufficiency render many RSF-based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations. Here, Street et al. provide the first comprehensive solution for RSF sample size by deriving closed-form mathematical expressions for the number of animals and the number of relocations per animal required for model outputs to a given degree of precision.


scikit-maad Passive acoustic monitoring is increasingly being applied to terrestrial, marine and freshwater environments, providing cost-efficient methods for surveying biodiversity. However, processing the avalanche of audio recordings remains challenging, and represents a major bottleneck that slows down its application in research and conservation. Here, Ulloa et al. present scikit-maad, an open-source Python package dedicated to the analysis of environmental audio recordings. scikit-maad allows the user to efficiently scan large audio datasets and easily integrate additional machine learning Python packages into the analysis, allowing to measure acoustic properties and identify key patterns in all kinds of soundscapes.

Sashimi Digitised specimens are an indispensable resource for rapidly acquiring big datasets and typically must be pre-processed prior to conducting analyses. One crucial image pre-processing step in any image analysis workflow is image segmentation, or the ability to clearly contrast the foreground target from the background noise in an image. This procedure is typically done manually, creating a potential bottleneck for efforts to quantify biodiversity from image databases. Here, Schwartz & Alfaro present Sashimi, a user-friendly command line toolkit to facilitate rapid, automated high-throughput image segmentation of digitized organisms. Sashimi is accessible to non-programmers and does not require experience with deep learning to use.

poems Spatially explicit population models (SEPMs) can simulate spatiotemporal changes in species’ range dynamics in response to variation in climatic and environmental conditions, and anthropogenic activities. When combined with pattern-oriented modelling methods, ecological processes and drivers of range shifts and extinctions can be identified, and plausible chains of causality revealed. Fordham et al. present poems, an R package providing functionality for simulating and validating projections of species’ range dynamics using stochastic, lattice-based population models. They illustrate its features and versatility by simulating the historical decline and extinction of the Thylacine Thylacinus cynocephalus, an icon of recent extinctions in Australia.

track2KBA *open access* Identifying important sites for biodiversity is vital for conservation and management. However, there is a lack of accessible, easily-applied tools that enable practitioners to delineate important sites for highly mobile species using established criteria. Beal et al. introduce the R package ‘track2KBA’, a tool to identify important sites at the population level using tracking data from individual animals based on three key steps: (a) identifying individual core areas, (b) assessing population-level representativeness of the sample and (c) quantifying spatial overlap among individuals and scaling up to the population.

The Seal on the Cover

This issue’s cover shows an unoccupied aircraft system (UAS, or drone) used to image grey seals (Halichoerus grypus) in Nova Scotia, Canada. In their study, Shero et al. present a novel method using UAS for structure-from-motion three-dimensional (3-D) photogrammetry of whole groups of animals at once. In the study, the method is first validated by comparing aerial and ground-volumetric measurements collected from the same individual animals. Their study then demonstrates the applicability of the method by 3-D modeling hundreds of seals. The UAS photogrammetric method captured significant changes in the top predator’s energy dynamics across lactation and also between two years with remarkably different sea ice conditions. This method is likely to be broadly applicable to other species, and the ability to measure large numbers of animals non-invasively makes strides towards ‘weighing populations’.