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Abstract Plant diversity effects on community productivity often increase over time. Whether the strengthening of diversity effects is caused by temporal shifts in species-level overyielding (i.e., higher species-level productivity in diverse communities compared with monocultures) remains unclear. Here, using data from 65 grassland and forest biodiversity experiments, we show that the temporal strength of diversity effects at the community scale is underpinned by temporal changes in the species that yield. These temporal trends of species-level overyielding are shaped by plant ecological strategies, which can be quantitatively delimited by functional traits. In grasslands, the temporal strengthening of biodiversity effects on community productivity was associated with increasing biomass overyielding of resource-conservative species increasing over time, and with overyielding of species characterized by fast resource acquisition either decreasing or increasing. In forests, temporal trends in species overyielding differ when considering above- versus belowground resource acquisition strategies. Overyielding in stem growth decreased for species with high light capture capacity but increased for those with high soil resource acquisition capacity. Our results imply that a diversity of species with different, and potentially complementary, ecological strategies is beneficial for maintaining community productivity over time in both grassland and forest ecosystems. 

Summary Leaf traits are essential for understanding many physiological and ecological processes. Partial least squares regression (PLSR) models with leaf spectroscopy are widely applied for trait estimation, but their transferability across space, time, and plant functional types (PFTs) remains unclear.We compiled a novel dataset of paired leaf traits and spectra, with 47 393 records for > 700 species and eight PFTs at 101 globally distributed locations across multiple seasons. Using this dataset, we conducted an unprecedented comprehensive analysis to assess the transferability of PLSR models in estimating leaf traits.While PLSR models demonstrate commendable performance in predicting chlorophyll content, carotenoid, leaf water, and leaf mass per area prediction within their training data space, their efficacy diminishes when extrapolating to new contexts. Specifically, extrapolating to locations, seasons, and PFTs beyond the training data leads to reducedR²(0.12–0.49, 0.15–0.42, and 0.25–0.56) and increased NRMSE (3.58–18.24%, 6.27–11.55%, and 7.0–33.12%) compared with nonspatial random cross‐validation. The results underscore the importance of incorporating greater spectral diversity in model training to boost its transferability.These findings highlight potential errors in estimating leaf traits across large spatial domains, diverse PFTs, and time due to biased validation schemes, and provide guidance for future field sampling strategies and remote sensing applications. 

Abstract AimAngiosperm epiphytes have long been reported to have larger geographic ranges than terrestrial species, despite evidence of their outstanding diversity and endemism. This apparent contradiction calls for further investigation of epiphytes' poorly understood range size patterns. Here, we address the question of whether epiphytes have larger geographic ranges and different vulnerability to extinction than terrestrial species. LocationThe Atlantic Forest of Brazil, a global centre of tropical epiphyte diversity with relatively well‐known flora, where we can estimate the geographic ranges of a large number of species with reasonable confidence. Time periodOccurrence records from the 17th century to the year 2021. Major taxa studiedFlowering plants (angiosperms). MethodsWe downloaded, processed and cleaned all occurrence records for the angiosperm species native to the Atlantic Forest of Brazil available in the speciesLink network and the Global Biodiversity Information Facility. We estimated the extent of occurrence and area of occupancy of 12,679 native flowering plants, including 1251 epiphytic species. We compared the geographic ranges of epiphytes and other life forms at broad (e.g. Angiosperms, Monocots) and more restricted taxonomic scales (e.g. individual families), assuming species are independent entities and also when accounting for species phylogenetic dependence. ResultsWe found that epiphytes have among the smallest geographic ranges of flowering plants. We found no consistent evidence that epiphytism leads to differences in geographic ranges between close relatives. However, both epiphytes and non‐epiphytes in epiphyte‐rich lineages have small ranges and likely a high vulnerability to extinction. Main ConclusionsOur findings contrast with the long‐held hypothesis that epiphytes have larger geographic ranges than terrestrial species. Epiphytes and their close relatives share many diversification mechanisms and ecological adaptations (‘epiphyte‐like traits’), which probably explain why both sets of species have small range sizes and high vulnerability to extinction. 

Abstract AimTheoretical, experimental and observational studies have shown that biodiversity–ecosystem functioning (BEF) relationships are influenced by functional community structure through two mutually non‐exclusive mechanisms: (1) the dominance effect (which relates to the traits of the dominant species); and (2) the niche partitioning effect [which relates to functional diversity (FD)]. Although both mechanisms have been studied in plant communities and experiments at small spatial extents, it remains unclear whether evidence from small‐extent case studies translates into a generalizable macroecological pattern. Here, we evaluate dominance and niche partitioning effects simultaneously in grassland systems world‐wide. LocationTwo thousand nine hundred and forty‐one grassland plots globally. Time period2000–2014. Major taxa studiedVascular plants. MethodsWe obtained plot‐based data on functional community structure from the global vegetation plot database “sPlot”, which combines species composition with plant trait data from the “TRY” database. We used data on the community‐weighted mean (CWM) and FD for 18 ecologically relevant plant traits. As an indicator of primary productivity, we extracted the satellite‐derived normalized difference vegetation index (NDVI) from MODIS. Using generalized additive models and deviation partitioning, we estimated the contributions of trait CWM and FD to the variation in annual maximum NDVI, while controlling for climatic variables and spatial structure. ResultsGrassland communities dominated by relatively tall species with acquisitive traits had higher NDVI values, suggesting the prevalence of dominance effects for BEF relationships. We found no support for niche partitioning for the functional traits analysed, because NDVI remained unaffected by FD. Most of the predictive power of traits was shared by climatic predictors and spatial coordinates. This highlights the importance of community assembly processes for BEF relationships in natural communities. Main conclusionsOur analysis provides empirical evidence that plant functional community structure and global patterns in primary productivity are linked through the resource economics and size traits of the dominant species. This is an important test of the hypotheses underlying BEF relationships at the global scale. 

Abstract Plant trait data are used to quantify how plants respond to environmental factors and can act as indicators of ecosystem function. Measured trait values are influenced by genetics, trade‐offs, competition, environmental conditions, and phenology. These interacting effects on traits are poorly characterized across taxa, and for many traits, measurement protocols are not standardized. As a result, ancillary information about growth and measurement conditions can be highly variable, requiring a flexible data structure. In 2007, the TRY initiative was founded as an integrated database of plant trait data, including ancillary attributes relevant to understanding and interpreting the trait values. The TRY database now integrates around 700 original and collective datasets and has become a central resource of plant trait data. These data are provided in a generic long‐table format, where a unique identifier links different trait records and ancillary data measured on the same entity. Due to the high number of trait records, plant taxa, and types of traits and ancillary data released from the TRY database, data preprocessing is necessary but not straightforward. Here, we present the ‘rtry’ R package, specifically designed to support plant trait data exploration and filtering. By integrating a subset of existing R functions essential for preprocessing, ‘rtry’ avoids the need for users to navigate the extensive R ecosystem and provides the functions under a consistent syntax. ‘rtry’ is therefore easy to use even for beginners in R. Notably, ‘rtry’ does not support data retrieval or analysis; rather, it focuses on the preprocessing tasks to optimize data quality. While ‘rtry’ primarily targets TRY data, its utility extends to data from other sources, such as the National Ecological Observatory Network (NEON). The ‘rtry’ package is available on the Comprehensive R Archive Network (CRAN;https://cran.r‐project.org/package=rtry) and the GitHub Wiki (https://github.com/MPI‐BGC‐Functional‐Biogeography/rtry/wiki) along with comprehensive documentation and vignettes describing detailed data preprocessing workflows. 

Abstract Yield gaps, here defined as the difference between actual and attainable yields, provide a framework for assessing opportunities to increase agricultural productivity. Previous global assessments, centred on a single year, were unable to identify temporal variation. Here we provide a spatially and temporally comprehensive analysis of yield gaps for ten major crops from 1975 to 2010. Yield gaps have widened steadily over most areas for the eight annual crops and remained static for sugar cane and oil palm. We developed a three-category typology to differentiate regions of ‘steady growth’ in actual and attainable yields, ‘stalled floor’ where yield is stagnated and ‘ceiling pressure’ where yield gaps are closing. Over 60% of maize area is experiencing ‘steady growth’, in contrast to ∼12% for rice. Rice and wheat have 84% and 56% of area, respectively, experiencing ‘ceiling pressure’. We show that ‘ceiling pressure’ correlates with subsequent yield stagnation, signalling risks for multiple countries currently realizing gains from yield growth. 

Abstract Warming shifts the thermal optimum of net photosynthesis (T_optA) to higher temperatures. However, our knowledge of this shift is mainly derived from seedlings grown in greenhouses under ambient atmospheric carbon dioxide (CO₂) conditions. It is unclear whether shifts inT_optAof field-grown trees will keep pace with the temperatures predicted for the 21^stcentury under elevated atmospheric CO₂concentrations. Here, using a whole-ecosystem warming controlled experiment under either ambient or elevated CO₂levels, we show thatT_optAof mature boreal conifers increased with warming. However, shifts inT_optAdid not keep pace with warming asT_optAonly increased by 0.26–0.35 °C per 1 °C of warming. Net photosynthetic rates estimated at the mean growth temperature increased with warming in elevated CO₂spruce, while remaining constant in ambient CO₂spruce and in both ambient CO₂and elevated CO₂tamarack with warming. Although shifts inT_optAof these two species are insufficient to keep pace with warming, these boreal conifers can thermally acclimate photosynthesis to maintain carbon uptake in future air temperatures. 

Abstract The determinants of fire-driven changes in soil organic carbon (SOC) across broad environmental gradients remains unclear, especially in global drylands. Here we combined datasets and field sampling of fire-manipulation experiments to evaluate where and why fire changes SOC and compared our statistical model to simulations from ecosystem models. Drier ecosystems experienced larger relative changes in SOC than humid ecosystems—in some cases exceeding losses from plant biomass pools—primarily explained by high fire-driven declines in tree biomass inputs in dry ecosystems. Many ecosystem models underestimated the SOC changes in drier ecosystems. Upscaling our statistical model predicted that soils in savannah–grassland regions may have gained 0.64 PgC due to net-declines in burned area over the past approximately two decades. Consequently, ongoing declines in fire frequencies have probably created an extensive carbon sink in the soils of global drylands that may have been underestimated by ecosystem models. 

Abstract Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories – the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis – are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections. 

Abstract As climate change advances, there is a need to examine climate conditions at scales that are ecologically relevant to species. While microclimates in forested systems have been extensively studied, microclimates in grasslands have received little attention despite the climate vulnerability of this endangered biome. We employed a novel combination of iButton temperature and humidity measurements, fine-scale spatial observations of vegetation and topography collected by unpiloted aircraft system, and gridded mesoclimate products to model microclimate anomalies in temperate grasslands. We found that grasslands harbored diverse microclimates and that primary productivity (as represented by normalized difference vegetation index), canopy height, and topography were strong spatial drivers of these anomalies. Microclimate heterogeneity is likely of ecological importance to grassland organisms seeking out climate change refugia, and thus there is a need to consider microclimate complexity in the management and conservation of grassland biodiversity.