Critical habitats for sharks and rays in Asia remain largely unprotected - Adriana Gonzalez-Pestana; Peter M. Kyne; Emiliano García-Rodríguez; Ryan Charles; Vanessa Bettcher Brito; Asia O. Armstrong; Amanda Batlle-Morera; Marta D. Palacios; Christoph A. Rohner; Giuseppe Notarbartolo di Sciara; Jo Marie V. Acebes; Serena Adam; et al. (Biodiversity and Conservation, 2026)
The Asia region harbors exceptional chondrichthyan (shark, ray, and chimaera) diversity but faces intense fishing pressure. The Important Shark and Ray Areas (ISRA) process provides a collaborative, evidence-based framework to identify critical habitats and inform spatial management. We assessed ISRAs across the Bay of Bengal, Southeast Asia, and the Northwest Pacific to characterize their extent, ecological significance, and conservation relevance. We delineated 122 ISRAs spanning ~ 1 million km 2 (~ 3% of the region) across 12 jurisdictions and international waters, encompassing habitats for 121 species (~ 30% of Asia’s chondrichthyans), 76% of which are threatened. Depleted taxa (e.g., giant guitarfishes, Glaucostegidae) were represented, but charismatic megafauna (e.g., Whale Shark Rhincodon typus ) were overrepresented. In contrast, deepwater and freshwater species were underrepresented. Reproductive Areas were the most common ISRA sub-criterion applied (52% of ISRAs), largely in nearshore zones, while areas for range-restricted species were less frequently (18%) identified. Twelve ISRAs overlapped with biodiversity hotspots, including seven in areas of high overall chondrichthyan species richness and five in areas of high range-restricted species richness. Citizen science was the predominant research method used to delineate ISRAs, while fisheries data were underused despite the region’s major fisheries footprint. Geographic coverage was uneven: Indonesia held the most ISRAs (n = 40; 71.7% of ISRA coverage) while eight jurisdictions (e.g., Viet Nam, China, Republic of Korea) lacked ISRAs due to data gaps. Protection shortfalls are stark: MPAs cover

BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series - Maria Dornelas; Laura H. Antão; Amanda E. Bates; Viviana Brambilla; Jonathan M. Chase; Cher F. Y. Chow; Ada Fontrodona‐Eslava; Anne E. Magurran; Inês S. Martins; Faye Moyes; Alban Sagouis; Samuel Adu‐Acheampong; et al. (Global Ecology and Biogeography, 2025)
Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample‐level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

Dominance and rarity in tree communities across the globe: Patterns, predictors and threats - Iris Hordijk; Lalasia Bialic‐Murphy; Thomas Lauber; Devin Routh; Lourens Poorter; Malin C. Rivers; Hans ter Steege; Jingjing Liang; Peter B. Reich; Sergio de‐Miguel; Gert‐Jan Nabuurs; Javier G. P. Gamarra; et al. (Global Ecology and Biogeography, 2024)
Aim Ecological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species? Location Global. Time period 1990–2017. Major taxa studied Trees. Methods We used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated. Results Community dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large‐scale land degradation. Main conclusions By linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large‐scale management and conservation practices.

Correction: On the Relationship Between Aquatic CO2 Concentration and Ecosystem Fluxes in Some of the World’s Key Wetland Types - Jessica L. Richardson; Ankur R. Desai; Jonathan Thom; Kim Lindgren; Hjalmar Laudon; Matthias Peichl; Mats Nilsson; Audrey Campeau; Järvi Järveoja; Peter Hawman; Deepak R. Mishra; Dontrece Smith; et al. (Wetlands, 2024)

On the Relationship Between Aquatic CO2 Concentration and Ecosystem Fluxes in Some of the World’s Key Wetland Types - Jessica L. Richardson; Ankur R. Desai; Jonathan Thom; Kim Lindgren; Hjalmar Laudon; Matthias Peichl; Mats Nilsson; Audrey Campeau; Järvi Järveoja; Peter Hawman; Deepak R. Mishra; Dontrece Smith; et al. (Wetlands, 2024)

Global maps of soil temperature - Jonas J. Lembrechts; Johan van den Hoogen; Juha Aalto; Michael B. Ashcroft; Pieter De Frenne; Julia Kemppinen; Martin Kopecký; Miska Luoto; Ilya M. D. Maclean; Thomas W. Crowther; Joseph J. Bailey; Stef Haesen; et al. (Global Change Biology, 2022)
Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1‐km 2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1‐km 2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse‐grained air temperature estimates from ERA5‐Land (an atmospheric reanalysis by the European Centre for Medium‐Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome‐specific offsets emphasize that the projected impacts of climate and climate change on near‐surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil‐related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

SoilTemp: A global database of near‐surface temperature - Jonas J. Lembrechts; Juha Aalto; Michael B. Ashcroft; Pieter De Frenne; Martin Kopecký; Jonathan Lenoir; Miska Luoto; Ilya M. D. Maclean; Olivier Roupsard; Eduardo Fuentes‐Lillo; Rafael A. García; Loïc Pellissier; et al. (Global Change Biology, 2020)
Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long‐term average thermal conditions at coarse spatial resolutions only. Hence, many climate‐forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold‐air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free‐air temperatures, microclimatic ground and near‐surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near‐surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

TRY plant trait database – enhanced coverage and open access - Jens Kattge; Gerhard Bönisch; Sandra Díaz; Sandra Lavorel; Iain Colin Prentice; Paul Leadley; Susanne Tautenhahn; Gijsbert D. A. Werner; Tuomas Aakala; Mehdi Abedi; Alicia T. R. Acosta; George C. Adamidis; et al. (Global Change Biology, 2020)
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Persistent benthic communities in the extreme dynamic intertidal mudflats of the Amazonian coast: an overview of the Tanaidacea (Crustacea, Peracarida) - H. Thanh Nguyen; C. Dupuy; J. Jourde; C. Lefrançois; P.-Y. Pascal; A. Carpentier; J. Chevalier; P. Bocher (Marine Biodiversity, 2018)

Effects of a 5-h hilly running on ankle plantar and dorsal flexor force and fatigability - François Fourchet; Grégoire P. Millet; Katja Tomazin; Kenny Guex; Ken Nosaka; Pascal Edouard; Francis Degache; Guillaume Y. Millet (European Journal of Applied Physiology, 2012)