Behavioural Diversity of Fishes: Concepts, Drivers and Its Role in Conservation and Management - Marie Prchalová; Robert Arlinghaus; Samuel Westrelin; Ivan Jarić; Michael G. Bertram; Josep Alós; Henrik Baktoft; Jack A. Brand; Tomas Brodin; Adolfo Cordero‐Rivera; Carlina Feldmann; Ryo Futamura; et al. (Fish and Fisheries, 2026)
Human activity has altered nearly all ecosystems on Earth, contributing to substantial biodiversity loss across taxonomic, genetic and functional dimensions, from the intraspecific to the ecosystem scale. Yet some components of biodiversity remain hidden or underappreciated, including behavioural diversity. Behaviour is often among the earliest whole‐organism responses to environmental change, and diversity in behaviour can occur within individuals, among individuals, among populations and across communities and ecosystems. This variation may influence growth, survival, reproduction, ecological interactions and responses to anthropogenic pressures, although its effects on population stability and resilience are likely context‐, scale‐ and component‐dependent. In this review, we examine behavioural diversity in fishes, defined here as variation in behavioural traits across levels of biological organisation, from individuals to ecosystems. Our review has two complementary aims. First, we provide a conceptual overview of behavioural diversity, clarify how it differs from related constructs such as personality, plasticity, and behavioural syndromes, and summarise the evolutionary, ontogenetic, ecological, stochastic and anthropogenic processes that generate or erode it. Second, we evaluate why behavioural diversity matters for fish ecology, fisheries management, aquaculture, restoration and conservation. We conclude by identifying key research needs, including improved quantification, stronger empirical links between behavioural diversity and ecological outcomes, and the development of management approaches sensitive to behavioural diversity. More explicit consideration of behavioural diversity should improve our ability to predict fish behavioural diversity responses and to design conservation and management measures that account for variation rather than only average behavioural responses.

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.

Evaluation of the effect of Carica papaya seed on the growth performance of fattening rabbits - Basile Konmy; Mariano G. Bossikponsi; Christian C. Dansou; Kisito B. Arigbo; Geraldo T. Houmenou; Carine A. Adoho; Erick V. B. Azando; Sanni-yo Doko Allou; Pascal A. Olounladé (Tropical Animal Health and Production, 2024)

Reading tea leaves worldwide: Decoupled drivers of initial litter decomposition mass‐loss rate and stabilization - Judith M. Sarneel; Mariet M. Hefting; Taru Sandén; Johan van den Hoogen; Devin Routh; Bhupendra S. Adhikari; Juha M. Alatalo; Alla Aleksanyan; Inge H. J. Althuizen; Mohammed H. S. A. Alsafran; Jeff W. Atkins; Laurent Augusto; et al. (Ecology Letters, 2024)
The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large‐scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass‐loss rates and stabilization factors of plant‐derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy‐to‐degrade components accumulate during early‐stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass‐loss rates and stabilization, notably in colder locations. Using TBI improved mass‐loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early‐stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models.

New antimicrobial cyclolignan and others constituents from the leaves of Scyphocephalium mannii (Benth. & Hook.f.) Warb - Dieu Ne Dort Nganteng; Raduis Melong; Timoleon Maffo; Roland T. Tchuenguem; Aurelien Crochet; Jean Paul Dzoyem; Pascal Wafo; Christian G. Bochet; Bonaventure Tchaleu Ngadjui (Natural Product Research, 2022)

Impact of bacterial strain acquisition in the lung of patients with COPD: the AERIS study - Lucio Malvisi; Aparna Yarraguntla; Marie-Cécile Mortier; Karen Osman; David W. Cleary; Béatrice Sente; Thierry G. Pascal; Vincent Weynants; Stuart C. Clarke; Laura Taddei; Tom M. A. Wilkinson; Jeanne-Marie Devaster; et al. (Infectious Diseases, 2022)

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.

Trypanosomiasis challenge estimation using the diminazene aceturate (Berenil) index in Zebu in Gabon - Brieuc G. A. Cossic; Brice Adjahoutonon; Pierre Gloaguen; Gui Lov Dibanganga; Gael Maganga; Pascal Leroy; Ewan T. MacLeod; Kim Picozzi (Tropical Animal Health and Production, 2017)

The Variability of Refractivity in the Atmospheric Boundary Layer of a Tropical Island Volcano Measured by Ground-Based Interferometric Radar - G. Wadge; A. Costa; K. Pascal; C. Werner; T. Webb (Boundary-Layer Meteorology, 2016)

Detection of interspecies hybridisation in Chondrichthyes: hybrids and hybrid offspring between Australian (Carcharhinus tilstoni) and common (C. limbatus) blacktip shark found in an Australian fishery - Jess A. T. Morgan; Alastair V. Harry; David J. Welch; Raewyn Street; Jimmy White; Pascal T. Geraghty; William G. Macbeth; Andrew Tobin; Colin A. Simpfendorfer; Jennifer R. Ovenden (Conservation Genetics, 2012)

Nutrient biogeochemistry in the water column (N, P, Si) and porewater (N) of sandy sediment of the Scheldt estuary (SW-Netherlands) - Pascal M. A. Boderie; John J. G. Zwolsman; Gijsbertus T. M. Eck; Cornelis H. Weijden (Aquatic Ecology, 1993)