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Wood density is a fundamental property related to tree biomechanics and hydraulic function while playing a crucial role in assessing vegetation carbon stocks by linking volumetric retrieval and a mass estimate. This study provides a high-resolution map of the global distribution of tree wood density at the 0.01° (~1 km) spatial resolution, derived from four decision trees machine learning models using a global database of 28,822 tree-level wood density measurements. An ensemble of four top-performing models combined with eight cross-validation strategies shows great consistency, providing wood density patterns with pronounced spatial heterogeneity. The global pattern shows lower wood density values in northern and northwestern Europe, Canadian forest regions and slightly higher values in Siberia forests, western United States, and southern China. In contrast, tropical regions, especially wet tropical areas, exhibit high wood density. Climatic predictors explain 49%-63% of spatial variations, followed by vegetation characteristics (25%-31%) and edaphic properties (11%-16%). Notably, leaf type (evergreen vs. deciduous) and leaf habit type (broadleaved vs. needleleaved) are the most dominant individual features among all selected predictive covariates. Wood density tends to be higher for angiosperm broadleaf trees compared to gymnosperm needleleaf trees, particularly for evergreen species. The distributions of wood density categorized by leaf types and leaf habit types have good agreement with the features observed in wood density measurements. This global map quantifying wood density distribution can help improve accurate predictions of forest carbon stocks, providing deeper insights into ecosystem functioning and carbon cycling such as forest vulnerability to hydraulic and thermal stresses in the context of future climate change., (© 2024 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Soil acidification induced by reactive nitrogen (N) inputs can alter the structure and function of terrestrial ecosystems. Because different N-transformation processes contribute to the production and consumption of H + , the magnitude of acidification likely depends on the relative amounts of organic N (ON) and inorganic N (IN) inputs. However, few studies have explicitly measured the effects of N composition on soil acidification. In this study, we first conducted a meta-analysis to test the effects of ON or IN inputs on soil acidification across 53 studies in grasslands. We then compared soil acidification across five different ON:IN ratios and two input rates based on long-term field N addition experiments. The meta-analysis showed that ON had weaker effects on soil acidification than IN when the N addition rate was above 20 g N m -2  year -1 . The field experiment confirmed the findings from meta-analysis: N addition with proportions of ON ≥ 20% caused less soil acidification, especially at a high input rate (30 g N m -2  year -1 ). Structural equation model analysis showed that this result was largely due to a relatively low rate of H + production from ON as NH 3 volatilization and uptake of ON and NH 4 + by the dominant grass species Leymus chinensis (which are both lower net contributors to H + production) result in less NH 4 + available for nitrification (which is a higher net contributor to H + production). These results indicate that the evaluation of soil acidification induced by N inputs should consider N forms and manipulations of relative composition of N inputs may provide an effective approach to alleviate the N-induced soil acidification., (© 2023 John Wiley & Sons Ltd.)

Plant respiration is an important contributor to the proposed positive global carbon-cycle feedback to climate change. However, as a major component, leaf mitochondrial ('dark') respiration (R d ) differs among species adapted to contrasting environments and is known to acclimate to sustained changes in temperature. No accepted theory explains these phenomena or predicts its magnitude. Here we propose that the acclimation of R d follows an optimal behaviour related to the need to maintain long-term average photosynthetic capacity (V cmax ) so that available environmental resources can be most efficiently used for photosynthesis. To test this hypothesis, we extend photosynthetic co-ordination theory to predict the acclimation of R d to growth temperature via a link to V cmax , and compare predictions to a global set of measurements from 112 sites spanning all terrestrial biomes. This extended co-ordination theory predicts that field-measured R d and V cmax accessed at growth temperature (R d,tg and V cmax,tg ) should increase by 3.7% and 5.5% per degree increase in growth temperature. These acclimated responses to growth temperature are less steep than the corresponding instantaneous responses, which increase 8.1% and 9.9% per degree of measurement temperature for R d and V cmax respectively. Data-fitted responses proof indistinguishable from the values predicted by our theory, and smaller than the instantaneous responses. Theory and data are also shown to agree that the basal rates of both R d and V cmax assessed at 25°C (R d,25 and V cmax,25 ) decline by ~4.4% per degree increase in growth temperature. These results provide a parsimonious general theory for R d acclimation to temperature that is simpler-and potentially more reliable-than the plant functional type-based leaf respiration schemes currently employed in most ecosystem and land-surface models., (© 2019 John Wiley & Sons Ltd.)

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., (© 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

The functional composition of plant communities is commonly thought to be determined by contemporary climate. However, if rates of climate-driven immigration and/or exclusion of species are slow, then contemporary functional composition may be explained by paleoclimate as well as by contemporary climate. We tested this idea by coupling contemporary maps of plant functional trait composition across North and South America to paleoclimate means and temporal variation in temperature and precipitation from the Last Interglacial (120 ka) to the present. Paleoclimate predictors strongly improved prediction of contemporary functional composition compared to contemporary climate predictors, with a stronger influence of temperature in North America (especially during periods of ice melting) and of precipitation in South America (across all times). Thus, climate from tens of thousands of years ago influences contemporary functional composition via slow assemblage dynamics., (© 2018 John Wiley & Sons Ltd.)

Intense droughts combined with increased temperatures are one of the major threats to forest persistence in the 21st century. Despite the direct impact of climate change on forest growth and shifts in species abundance, the effect of altered demography on changes in the composition of functional traits is not well known. We sought to (1) quantify the recent changes in functional composition of European forests; (2) identify the relative importance of climate change, mean climate and forest development for changes in functional composition; and (3) analyse the roles of tree mortality and growth underlying any functional changes in different forest types. We quantified changes in functional composition from the 1980s to the 2000s across Europe by two dimensions of functional trait variation: the first dimension was mainly related to changes in leaf mass per area and wood density (partially related to the trait differences between angiosperms and gymnosperms), and the second dimension was related to changes in maximum tree height. Our results indicate that climate change and mean climatic effects strongly interacted with forest development and it was not possible to completely disentangle their effects. Where recent climate change was not too extreme, the patterns of functional change generally followed the expected patterns under secondary succession (e.g. towards late-successional short-statured hardwoods in Mediterranean forests and taller gymnosperms in boreal forests) and latitudinal gradients (e.g. larger proportion of gymnosperm-like strategies at low water availability in forests formerly dominated by broad-leaved deciduous species). Recent climate change generally favoured the dominance of angiosperm-like related traits under increased temperature and intense droughts. Our results show functional composition changes over relatively short time scales in European forests. These changes are largely determined by tree mortality, which should be further investigated and modelled to adequately predict the impacts of climate change on forest function., (© 2017 John Wiley & Sons Ltd.)

Fire is a primary driver of boreal forest dynamics. Intensifying fire regimes due to climate change may cause a shift in boreal forest composition toward reduced dominance of conifers and greater abundance of deciduous hardwoods, with potential biogeochemical and biophysical feedbacks to regional and global climate. This shift has already been observed in some North American boreal forests and has been attributed to changes in site conditions. However, it is unknown if the mechanisms controlling fire-induced changes in deciduous hardwood cover are similar among different boreal forests, which differ in the ecological traits of the dominant tree species. To better understand the consequences of intensifying fire regimes in boreal forests, we studied postfire regeneration in five burns in the Central Siberian dark taiga, a vast but poorly studied boreal region. We combined field measurements, dendrochronological analysis, and seed-source maps derived from high-resolution satellite images to quantify the importance of site conditions (e.g., organic layer depth) vs. seed availability in shaping postfire regeneration. We show that dispersal limitation of evergreen conifers was the main factor determining postfire regeneration composition and density. Site conditions had significant but weaker effects. We used information on postfire regeneration to develop a classification scheme for successional pathways, representing the dominance of deciduous hardwoods vs. evergreen conifers at different successional stages. We estimated the spatial distribution of different successional pathways under alternative fire regime scenarios. Under intensified fire regimes, dispersal limitation of evergreen conifers is predicted to become more severe, primarily due to reduced abundance of surviving seed sources within burned areas. Increased dispersal limitation of evergreen conifers, in turn, is predicted to increase the prevalence of successional pathways dominated by deciduous hardwoods. The likely fire-induced shift toward greater deciduous hardwood cover may affect climate-vegetation feedbacks via surface albedo, Bowen ratio, and carbon cycling., (© 2015 John Wiley & Sons Ltd.)

Earth system models demonstrate large uncertainty in projected changes in terrestrial carbon budgets. The lack of inclusion of adaptive responses of vegetation communities to the environment has been suggested to hamper the ability of modeled vegetation to adequately respond to environmental change. In this study, variation in functional responses of vegetation has been added to an earth system model (ESM) based on ecological principles. The restriction of viable mean trait values of vegetation communities by the environment, called 'habitat filtering', is an important ecological assembly rule and allows for determination of global scale trait-environment relationships. These relationships were applied to model trait variation for different plant functional types (PFTs). For three leaf traits (specific leaf area, maximum carboxylation rate at 25 °C, and maximum electron transport rate at 25 °C), relationships with multiple environmental drivers, such as precipitation, temperature, radiation, and CO2 , were determined for the PFTs within the Max Planck Institute ESM. With these relationships, spatiotemporal variation in these formerly fixed traits in PFTs was modeled in global change projections (IPCC RCP8.5 scenario). Inclusion of this environment-driven trait variation resulted in a strong reduction of the global carbon sink by at least 33% (2.1 Pg C yr(-1) ) from the 2nd quarter of the 21st century onward compared to the default model with fixed traits. In addition, the mid- and high latitudes became a stronger carbon sink and the tropics a stronger carbon source, caused by trait-induced differences in productivity and relative respirational costs. These results point toward a reduction of the global carbon sink when including a more realistic representation of functional vegetation responses, implying more carbon will stay airborne, which could fuel further climate change., (© 2015 John Wiley & Sons Ltd.)

Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual- and trait-based version of the DGVM LPJmL (Lund-Potsdam-Jena managed Land) called LPJmL- flexible individual traits (LPJmL-FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL-FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N area ), the maximum carboxylation rate of Rubisco per leaf area (vcmaxarea), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade-offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade-offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species-rich center of the region with relatively low climatic variability. LPJmL-FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects., (© 2015 John Wiley & Sons Ltd.)