A. Zizka

The paper examines the relationship between evolutionary age and range size in species, finding that age correlates with larger ranges but this effect is modulated by insularity and dispersal ability.

This study tests automated methods for estimating extinction risk and population trends for plant species, finding moderate agreement with expert assessments but highlighting limitations for rare and complex species.

This paper develops models to predict the probability of species meeting specific IUCN Red List criteria, improving extinction risk assessments by identifying key predictors for each criterion.

This paper uses herbarium specimens and citizen science observations to define cactus bioregions, finding that human observations significantly enhance data in areas with collection biases.

The paper identifies unknown soil fungi using PacBio sequencing and evaluates standardization methods to analyze global diversity, endemicity, and vulnerability patterns.

The paper identifies 1,097 insular woody species and infers 175 evolutionary transitions, finding that aseasonal climate, drought, and island isolation drive insular woodiness.

IUCNN uses deep learning to predict species' extinction risk from occurrence data, outperforming existing methods on orchid datasets.

This study uses a deep learning model to automate conservation assessments for 13,910 orchid species, identifying 31.2% as Possibly Threatened and highlighting priority conservation areas.

The paper estimates the timing of woodiness origin in Canary Island plant lineages and links it to historical aridification events.

The paper improves the taxonomic reference list for vascular plants by resolving taxonomic status for 184,000 names and providing an updated resource with an R-package for integration into data pipelines.

The paper evaluates the impact of 13 automatic filters on biodiversity analyses using GBIF data for 18 Neotropical taxa, finding significant variation in problematic records across taxonomic groups.

This study uses phylogenomic analysis to clarify the relationships within the African palm genus Raphia, finding five clades and supporting morphological classification while highlighting unresolved species boundaries.

The paper quantifies how different political regimes affect biodiversity management by linking democracy levels to natural history specimen registrations.

The paper introduces sampbias, a method to quantify geographic sampling biases in species occurrence data using a Bayesian approach, demonstrating its application on mammal data from Borneo.

This study integrates fossil and molecular data to estimate the evolutionary history of New World monkeys, revealing earlier origins and key morphological and geographic changes.