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Abstract Droughts are a natural hazard of growing concern as they are projected to increase in frequency and severity for many regions of the world. The identification of droughts and their future characteristics is essential to building an understanding of the geography and magnitude of potential drought change trajectories, which in turn is critical information to manage drought resilience across multiple sectors and disciplines. Adding to this effort, we developed a dataset of global historical and projected future drought indices over the 1980–2100 period based on downscaled CMIP6 models across multiple shared socioeconomic pathways (SSP). The dataset is composed of two indices: the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) for 23 downscaled global climate models (GCMs) (0.25-degree resolution), including historical (1980–2014) and future projections (2015–2100) under four climate scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The drought indices were calculated for 3-, 6- and 12-month accumulation timescales and are available as gridded spatial datasets in a regular latitude-longitude format at monthly time resolution. 

Abstract Developing a predictive science of the biosphere depends heavily on the rapidly expanding biodiversity data that are commonly stored in biodiversity databases. Despite the proliferation of biodiversity databases, their independent operation has limited data discovery, comparison, and synthesis. Therefore, the biodiversity informatics community has called for improved alignment among these efforts to better catalog Earth's biodiversity. The primary challenges are incomplete knowledge of existing databases and incongruent taxonomic systems and data schemas. Addressing these issues will require development of a database registry, means to compare database contents, taxonomic harmonization, and tools that enable users to merge disparate databases based on their needs, all within a community of practice that enables people of various skill levels and roles to participate. We believe that synthesis and integration, driven by a growing and thriving community, will be the next stage of biodiversity informatics and will help unlock the full potential of biodiversity information. 

Abstract Trees are pivotal to global biodiversity and nature’s contributions to people, yet accelerating global changes threaten global tree diversity, making accurate species extinction risk assessments necessary. To identify species that require expert-based re-evaluation, we assess exposure to change in six anthropogenic threats over the last two decades for 32,090 tree species. We estimated that over half (54.2%) of the assessed species have been exposed to increasing threats. Only 8.7% of these species are considered threatened by the IUCN Red List, whereas they include more than half of the Data Deficient species (57.8%). These findings suggest a substantial underestimation of threats and associated extinction risk for tree species in current assessments. We also map hotspots of tree species exposed to rapidly changing threats around the world. Our data-driven approach can strengthen the efforts going into expert-based IUCN Red List assessments by facilitating prioritization among species for re-evaluation, allowing for more efficient conservation efforts. 

Abstract AimSpecies occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses. InnovationWe introduce an R package, occTest, that synthesizes a growing open‐source ecosystem of biodiversity cleaning workflows to prepare occurrence data for different modelling applications. It offers a structured set of algorithms to identify potential problems with species occurrence records by employing a hierarchical organization of multiple tests. The workflow has a hierarchical structure organized in testPhases(i.e. cleaning vs. testing)that encompass different testBlocksgrouping differenttestTypes(e.g.environmental outlier detection), which may use differenttestMethods(e.g.Rosner test, jacknife,etc.). Four differenttestBlockscharacterize potential problems in geographic, environmental, human influence and temporal dimensions. Filtering and plotting functions are incorporated to facilitate the interpretation of tests. We provide examples with different data sources, with default and user‐defined parameters. Compared to other available tools and workflows, occTest offers a comprehensive suite of integrated tests, and allows multiple methods associated with each test to explore consensus among data cleaning methods. It uniquely incorporates both coordinate accuracy analysis and environmental analysis of occurrence records. Furthermore, it provides a hierarchical structure to incorporate future tests yet to be developed. Main conclusionsoccTest will help users understand the quality and quantity of data available before the start of data analysis, while also enabling users to filter data using either predefined rules or custom‐built rules. As a result, occTest can better assess each record's appropriateness for its intended application. 

Abstract PremiseWithin plant communities, few species are abundant, and most are locally rare. Worldwide, 36% of plant species are exceedingly rare and often face high extinction risk. However, the community phylogenetic impact of the loss of rare plants is largely unknown in many systems. We address this gap by investigating how rare species contribute to phylogenetic diversity, considering multiple metrics of rarity and multiple elevations in a subalpine plant community. MethodsWe collected abundance data at three sites near the Rocky Mountain Biological Laboratory (Colorado, USA). We calculated each species' range size from public occurrence data. We calculated phylogenetic signal for abundance and range size, compared community phylogenetic metrics weighted by range size and abundance to unweighted metrics, and quantified the change in phylogenetic diversity when removing single species and groups of species ranked by rarity. ResultsWe found phylogenetic signal for abundance, but not range size. There was no difference between rarity‐weighted and ‐unweighted phylogenetic diversity metrics. Finally, phylogenetic diversity did not decline more when we removed single rare species or groups of rare species than when we removed single common species and groups of common species. ConclusionsWe found that rare species, whether at low abundance or with a small range, do not disproportionately contribute to phylogenetic diversity in our subalpine plant community. These results were consistent across elevations. Instead, rare species might provide phylogenetic redundancy with common species. Deeper understanding of functional differentiation is needed to understand contributions of rare species to this system. 

Abstract Biologists increasingly rely on computer code to collect and analyze their data, reinforcing the importance of published code for transparency, reproducibility, training, and a basis for further work. Here, we conduct a literature review estimating temporal trends in code sharing in ecology and evolution publications since 2010, and test for an influence of code sharing on citation rate. We find that code is rarely published (only 6% of papers), with little improvement over time. We also found there may be incentives to publish code: Publications that share code have tended to be low‐impact initially, but accumulate citations faster, compensating for this deficit. Studies that additionally meet other Open Science criteria, open‐access publication, or data sharing, have still higher citation rates, with publications meeting all three criteria (code sharing, data sharing, and open access publication) tending to have the most citations and highest rate of citation accumulation. 

Abstract Both tree size and life history variation drive forest structure and dynamics, but little is known about how life history frequency changes with size. We used a scaling framework to quantify ontogenetic size variation and assessed patterns of abundance, richness, productivity and light interception across life history strategies from >114,000 trees in a primary, neotropical forest. We classified trees along two life history axes: a fast–slow axis characterized by a growth–survival trade‐off, and a stature–recruitment axis with tall, long‐lived pioneers at one end and short, short‐lived recruiters at the other.Relative abundance, richness, productivity and light interception follow an approximate power law, systematically shifting over an order of magnitude with tree size. Slow saplings dominate the understorey, but slow trees decline to parity with rapidly growing fast and long‐lived pioneer species in the canopy.Like the community as a whole, slow species are the closest to obeying the energy equivalence rule (EER)—with equal productivity per size class—but other life histories strongly increase productivity with tree size. Productivity is fuelled by resources, and the scaling of light interception corresponds to the scaling of productivity across life history strategies, with slow and all species near solar energy equivalence. This points towards a resource‐use corollary to the EER: the resource equivalence rule.Fitness trade‐offs associated with tree size and life history may promote coexistence in tropical forests by limiting niche overlap and reducing fitness differences. Synthesis . Tree life history strategies describe the different ways trees grow, survive and recruit in the understorey. We show that the proportion of trees with a pioneer life history strategy increases steadily with tree size, as pioneers become relatively more abundant, productive, diverse and capture more resources towards the canopy. Fitness trade‐offs associated with size and life history strategy offer a mechanism for coexistence in tropical forests.