Our November issue is online now! Our penultimate issue of the year contains 18 articles about the latest methods in ecology and evolution.
This month we have methods for long-term acoustic monitoring, automated landmarking of 3D biological structures, assessing the movement of small mammals and more, plus two Applications and two Practical Tools articles for your reading. Find out more below!
A primer on partially observable Markov decision processes Partially observable Markov decision processes (POMDPs) are a convenient mathematical model to solve sequential decision-making problems under imperfect observations, but despite an increasing number of applications in ecology, POMDPs are still poorly understood. Here, Chades et al. propose to bridge this gap by providing a primer on POMDPs, a typology of case studies drawn from the literature, and a repository of POMDP problems.
The Kinabalu Recorder New low-cost options to long-term acoustic monitoring in terrestrial ecology are becoming increasingly available. However, integration of acoustic stations with sensors for logging of additional data, such as temperature and barometric pressure is rare. In this Practical Tools article, Karlsson et al. present the Kinabalu Recorder, a hardware system for both acoustic and environmental data logging where the board design is released under a creative commons license that been field tested in a tropical setting.
Ecological learning from machine learning (open access) The ecological and environmental science communities have embraced machine learning (ML) for empirical modelling and prediction, but going beyond prediction to draw insights into underlying functional relationships between response variables and environmental drivers is less straightforward; deriving ecological insights from fitted ML models requires techniques to extract the ‘learning’ hidden in the ML models. Here, Yu et al. revisit the theoretical background and effectiveness of four approaches for deriving insights from ML and explore the use of a surrogate model for visualisation and interpretation of complex multivariate relationships between response variables and environmental drivers.
ALPACA (open access) With the ever-increasing density of digitised landmarks, the possible development of a fully-automated method of landmark placement has attracted considerable attention. Despite recent progress in image registration techniques, which could provide a pathway to automation, 3D morphometric data are still mainly gathered by trained experts. For the most part, the large infrastructure requirements necessary to perform image-based registration, together with its system specificity and its overall speed, have prevented its wide dissemination. In answer to this, Porto et al. propose and implement a general and lightweight point cloud-based approach to automatically collect high-dimensional landmark data in 3D surfaces.
Assessing the movement of small mammals Rats are especially ubiquitous in urban slums, where they are a threat to infrastructure and public health due to the pathogens they carry and transmit. Effective control of rat populations in most urban areas has been unsuccessful, and limited information about rat movement distance has hindered identification of control units and effective scales at which to enact control during interventions. Here, Awoniyi et al. evaluate the suitability of Rhodamine B, a non-toxic biomarker, for assessing the distance travelled by rats in urban slums.
The Data Pool Initiative for the Bohemian Forest Ecosystem Effects of climate change-induced events on forest ecosystem dynamics of composition, function and structure call for increased long-term, interdisciplinary and integrated research on biodiversity indicators, in particular within strictly protected areas with extensive non-intervention zones. In this Perspective article, Latifi et al. introduce the concept of data pools as a smaller-scale, user-driven and reasonable alternative to co-develop remote sensing and forest ecosystem science to validated products, biodiversity indicators and management plans. They demonstrate this concept with the Bohemian Forest Ecosystem Data Pool, which has been established as an interdisciplinary, international data pool within the strictly protected Bavarian Forest and Šumava National Parks and currently comprises 10 active partners.
GEODIV (open access) Smith et al. present GEODIV, an R package which calculates gradient surface metrics from imagery and other gridded datasets to provide continuous measures of landscape heterogeneity for landscape pattern analysis. It is the first open-source, command line toolbox for calculating many gradient surface metrics and easily integrates parallel computing for applications with large images or rasters (e.g. remotely sensed data). All functions may be applied either globally to derive a single metric for an entire image or locally to create a texture image over moving windows of a user-defined extent.
Estimating canopy fuel load with hemispherical photographs Canopy fuel load (CFL) affects wildfire intensity and is a critical input for fire behaviour models; however, measuring CFL in the field is time-consuming and costly. Here, Cameron et al. describe an inexpensive and effective method for estimating CFL in the field opportunistically using canopy openness and leaf area index values derived from hemispherical photographs taken in variable lighting conditions with a smartphone and fisheye lens attachment.
The Wolf on the Cover
This month’s cover shows grey wolf (Canis lupus) in Mediterranean scrub along the mountain ranges of Sierra Morena (Andalucia, Spain). Using genome-wide single nucleotide polymorphisms, the phylogeography of this carnivore (native to Eurasia and North America) is examined by Herrando-Pérez et al. as a case example illustrating the functionality of the new R package smartsnp for fast and friendly analyses of big genomic data. Photo credit: ©Alfonso Roldán.