Reconsidering how we measure forests with LiDAR

Post provided by Jeff W. Atkins (he/him)

Ecological researchers have adopted light detection and ranging (LiDAR) as a means of quantifying ecosystem structure over the past 25+ years. This is especially true in forest-related research, as LiDAR provides the ability to estimate ecosystem structure with incredibly fine detail, over broad areas. LiDAR can work at the scale of individual trees—for example crown delineation algorithms that identify singular tree canopies—or the stand-level with aggregate structural metrics. In this blog post, Jeff shares insight from he and his co-author’s recent publication “Scale dependency of LiDA R -derived forest structural diversity,” which proposes that using LiDAR requires statistical reassessment to ensure we are measuring what we think we are.

Ben WhittakerFebruary 16, 2023February 14, 20231 Comment

Statistical methods

A Multiple-Part Morphospace

Post provided by Daniel Thomas

Many biologists dedicate their careers to finding out why life has taken the shape it has. Darwinian natural selection gives us the how, but researchers are deeply interested in why we find particular morphologies amongst certain organisms, when these morphologies arose, and what these morphologies mean for the organisms and the communities in which they reside. In this post, Daniel Thomas (Massey University, New Zealand) describes the philosophy behind the new morphoBlocks package for R. The package is presented in a new paper within the ‘Realising the promise of large data and complex models’ Special Feature for Methods in Ecology and Evolution. Researchers interested in exploring the morphoBlocks package are encouraged to try these three vignettes.

Ben WhittakerDecember 16, 2021December 16, 2021Leave a comment

Conferences and Meetings

Countdown to the first ISEC in Africa!

Post provided by SEEC The Centre for Statistics in Ecology, Environment and Conservation (SEEC) invites you to ISEC2022 in Cape Town, South Africa, 27 June – 1 July 2022 – the first International Statistical Ecology Conference (ISEC) to be held in Africa! Registration is now open and we would like to welcome all of you to join this exciting event. Statistical ecology is an inherently … Continue reading Countdown to the first ISEC in Africa!

India StephensonDecember 1, 2021March 30, 2022Leave a comment

Methods papers, Statistical methods

Smart genetic analysis made fast and easy

Post provided by: Salvador Herrando-Pérez

If you use genetics to differentiate populations, the new package smartsnp might be your new best friend. Written in R language and available from GitHub and CRAN, this package performs principal component analysis with control for genetic drift, projects ancient samples onto modern genetic space, and tests for population differences in genotypes. The package can load big datasets and run complex stats in the blink of an eye.

In this post, Salvador Herrando-Pérez discusses the features of this new package which is fully described in the new paper “smartsnp, an R package for fast multivariate analyses of big genomic data” recently published in Methods in Ecology & Evolution.

Ben WhittakerAugust 11, 2021August 11, 2021Leave a comment

Code and Applications, Ecology, Evolution, Methods papers, Statistical methods, Theoretical methods

Stop, think, and beware of default options

Post provided by Paula Pappalardo (with contributions from Elizabeth Hamman, Jim Bence, Bruce Hungate & Craig Osenberg)

Esta publicación también está disponible en español.

You spent months carefully collecting data from articles addressing your favorite scientific question, you have dozens of articles neatly arranged on a spreadsheet, you found software or code to analyze the data, and then daydream about how your publication will be the most cited in your field while making cool plots. If that sounds familiar, you have probably done a meta-analysis. Meta-analysis uses statistical models to combine data from different publications to answer a specific question.

What you may not have realized when going down the meta-analysis rabbit hole, is that small, seemingly inconsequential, choices can greatly affect your results. If you want to know about one of them lurking behind the scenes… read on!

Daniel CaetanoAugust 4, 2020August 3, 2020Leave a comment

Code and Applications, Ecology, Evolution, Methods papers, Second Language Post, Statistical methods, Theoretical methods

Para, piensa, y ten cuidado con las configuraciones por defecto

Post escrito por Paula Pappalardo (con aportes de Elizabeth Hamman, Jim Bence, Bruce Hungate & Craig Osenberg)

This post is also available in English.

Pasaste meses laboriosamente colectando datos de artículos científicos acerca de tu pregunta favorita, tienes decenas de artículos perfectamente organizados en una base de datos, ya encontraste el programa o código para analizar los datos, y entonces imaginas como tu publicación va a ser la más citada en tu campo de investigación mientras haces unos gráficos lindísimos. Si esto te suena familiar, seguramente has hecho un meta-análisis. Un meta-análisis usa modelos estadísticos para combinar datos de distintas publicaciones para responder a una pregunta específica.

Lo que quizás no te diste cuenta mientras navegabas los pasos del meta-análisis, es que pequeñas decisiones (a veces pareciendo de muy poca importancia) pueden tener grandes efectos en los resultados. Si quieres saber más acerca de una de estas decisiones en particular… ¡sigue leyendo!

Daniel CaetanoAugust 4, 2020August 3, 2020Leave a comment

Code and Applications, Conservation and management, Ecology, Evolution, Methods papers, Statistical methods, Theoretical methods

MInOSSE: all you need to reconstruct past species geographic range is in the fossil record!

Post provided by Francesco Carotenuto

A very important ecological feature of a species is its geographic range, which can be described by its size, position and shape. Studying the geographic range can be useful to understand the ecological needs of a species and, thereby, to plan conservation strategies. In ecological studies, mathematical models are the new standard to reconstruct the distribution of living species on Earth because of their accuracy in predicting a species presence or absence at unsampled locations. These methods are able to reconstruct the climatic niche of a species and to project it onto a geographic domain in order to predict the species’ spatial distribution. To do this, besides the occurrences of a species, the models necessarily require the spatial maps of environmental variables, like temperature and precipitation, for all the study area.

Daniel CaetanoJuly 9, 2020July 7, 2020Leave a comment

Code and Applications, Ecology, Methods papers, Statistical methods, Theoretical methods

A brief history about the R package ‘metan’

Post provided by Tiago Olivoto

Este post também pode ser lido em Português

In our recent paper in Methods in Ecology and Evolution, Alessandro Lúcio and I describe a new R package, metan, for multi-environment trial analysis. Multi-environment trials are a kind of trial in plant breeding programs where several genotypes are evaluated in a set of environments. Analyzing such data requires the combination of several approaches including data manipulation, visualization and modelling. The latest stable version of metan (v1.5.1) is now on CRAN. So, I want to share the history about my first foray into using R, creating an R package, and submitting a paper to a journal that I’ve never had submitted before.

Daniel CaetanoMay 28, 2020May 26, 20201 Comment

Code and Applications, Ecology, Methods papers, Second Language Post, Statistical methods, Theoretical methods

Uma breve história sobre o pacote R ‘metan’

Post ESCRITO POR Tiago Olivoto

This post is also available in English

Em nosso recente artigo na Methods in Ecology and Evolution, Alessandro D. Lúcio e eu descrevemos um novo pacote R para análise de ensaios multi-ambientes chamado metan. Ensaios multi-ambientes são um tipo de ensaio em programas de melhoramento de plantas, onde vários genótipos são avaliados em um conjunto de ambientes. A análise desses dados requer a combinação de várias abordagens, incluindo manipulação, visualização e modelagem de dados. A versão estável mais recente do metan (v1.5.1) está disponível agora no repositório CRAN. Então, pensei em compartilhar a história da minha primeira incursão no uso do R criando um pacote e submetendo um artigo para uma revista que nunca havia submetido antes.