OOIR: Observatory of International Research

Papers

(The H4-Index of Methods in Ecology and Evolution is 42. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)

Article	Citations
Robustness of linear mixed‐effects models to violations of distributional assumptions	523
raxmlGUI 2.0: A graphical interface and toolkit for phylogenetic analyses using RAxML	388
Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package	341
metan: An R package for multi‐environment trial analysis	291
geomorph v4.0 and gmShiny: Enhanced analytics and a new graphical interface for a comprehensive morphometric experience	220
ENMeval 2.0: Redesigned for customizable and reproducible modeling of species’ niches and distributions	200
ntbox: An r package with graphical user interface for modelling and evaluating multidimensional ecological niches	182
Predicting into unknown space? Estimating the area of applicability of spatial prediction models	139
An empirical evaluation of camera trap study design: How many, how long and when?	112
Methods for testing publication bias in ecological and evolutionary meta‐analyses	103
Improving Landsat predictions of rangeland fractional cover with multitask learning and uncertainty	103
Redundancy analysis: A Swiss Army Knife for landscape genomics	102
A field and video annotation guide for baited remote underwater stereo‐video surveys of demersal fish assemblages	98
Deep learning‐based methods for individual recognition in small birds	96
A comprehensive and comparative evaluation of primers for metabarcoding eDNA from fish	96
Broad‐scale applications of the Raspberry Pi: A review and guide for biologists	93
Towards a more balanced combination of multiple traits when computing functional differences between species	85
A deep active learning system for species identification and counting in camera trap images	81
phyr: An r package for phylogenetic species‐distribution modelling in ecological communities	79
rTPC and nls.multstart: A new pipeline to fit thermal performance curves in r	74
Functional diversity metrics using kernel density n‐dimensional hypervolumes	68
phyloregion: R package for biogeographical regionalization and macroecology	68
SlicerMorph: An open and extensible platform to retrieve, visualize and analyse 3D morphology	64
adiv: An r package to analyse biodiversity in ecology	63
The Movebank system for studying global animal movement and demography	61

Generalized hidden Markov models for phylogenetic comparative datasets	57
Unbiased population heterozygosity estimates from genome‐wide sequence data	57
Deep learning as a tool for ecology and evolution	57
Automatic image‐based identification and biomass estimation of invertebrates	55
On the measurement of microclimate	55
The welfare and ethics of research involving wild animals: A primer	55
The use of Bayesian priors in Ecology: The good, the bad and the not great	54
embarcadero: Species distribution modelling with Bayesian additive regression trees in r	52
Plant and root‐zone water isotopes are difficult to measure, explain, and predict: Some practical recommendations for determining plant water sources	49
DeepForest: A Python package for RGB deep learning tree crown delineation	48
Automated detection of wildlife using drones: Synthesis, opportunities and constraints	47
Spatial thinning and class balancing: Key choices lead to variation in the performance of species distribution models with citizen science data	46
Machine learning and deep learning—A review for ecologists	44
Quality control for modern bone collagen stable carbon and nitrogen isotope measurements	44
A quick, easy and non‐invasive method to quantify coral growth rates using photogrammetry and 3D model comparisons	42
An assessment of minimum sequence copy thresholds for identifying and reducing the prevalence of artefacts in dietary metabarcoding data	42
Outstanding challenges and future directions for biodiversity monitoring using citizen science data	42