Aim Species distribution models (SDMs) address the whereabouts of species and are central to ecology. Deep learning (DL) is poised to further elevate the already significant role of SDMs in ecology ...

Abstract. The evolutionary dynamics of cryptic species remain poorly understood, and their detection relies primarily on methods that quantify divergence,

Benchmarking shows that detecting unknown species is more difficult than identifying known species with short DNA barcoding.

Successful applications of DNA barcoding/metabarcoding rely on the accurate taxonomic identification of sequence fragments. When biological surveys with DNA (meta)barcoding target underexplored biolog...

Abstract. DNA analyses have revolutionized species identification and taxonomic work. Yet, persistent challenges arise from little differentiation among an

Molecular sequence data have become a ubiquitous tool for delimiting species and are particularly important in organisms where morphological traits are not informative about species boundaries. A ran....

The most effective approaches for species discovery and species validation with genomic data remain underexplored. This study evaluates the merits and limitations of phylogenetic approaches based on ...

Machine learning is increasingly being applied to facilitate long-term, large-scale biodiversity monitoring. With most species on Earth still undiscovered or poorly documented, species-recognition mod...