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Aim: We analyse how functional diversity (FD) varies across European natural forests to understand the effects of environmental and competitive filtering on plant trait distribution. Location: Forest ecosystems in Europe from 11°W to 36°E and 29.5°N to 62°N. Taxon: Pinaceae, Fagaceae and Betulaceae, Oleaceae, Tiliaceae, Aceraceae, Leguminosae (unspecific). Methods: We adopted the existing Dynamic Global Vegetation Model Lund‐Potsdam‐Jena managed Land of flexible individual traits (LPJmL‐FIT) for Europe by eliminating both bioclimatic limits of plant functional types (PFTs) and replacing prescribed values of functional traits for PFTs with emergent values under influence of environmental filtering and competition. We quantified functional richness (FR), functional divergence (FDv) and functional evenness (FE) in representative selected sites and at Pan‐European scale resulting from simulated functional and structural trait combinations of individual trees. While FR quantifies the amount of occupied trait space, FDv and FE describe the distribution and abundance of trait combinations, respectively, in a multidimensional trait space. Results: Lund‐Potsdam‐Jena managed Land of flexible individual traits reproduces spatial PFTs and local trait distributions and agrees well with observed productivity, biomass and tree height of European natural forests. The observed site‐specific trait distributions and spatial gradients of traits of the leaf‐ and stem‐resource economics spectra coincide with environmental filtering and the competition for light and water in environments with strong abiotic stress. Where deciduous and needle‐leaved trees co‐occur, for example, in boreal and mountainous forests, the potential niche space is wide (high FR), and extreme ends in the niche space are occupied (high FDv). We find high FDv in Mediterranean forests where drought increasingly limits tree growth, thus niche differentiation becomes more important. FDv decreases in temperate forests where a cold climate increasingly limits growth efficiency of broad‐leaved summer green trees, thus reducing the importance of competitive exclusion. Highest FE was simulated in wet Atlantic and southern Europe which indicated relatively even niche occupation and thus high resource‐use efficiency. Main Conclusions: We find FD resulting from both environmental and competitive filtering. Pan‐European FR, FDv and FE demonstrate the influence of climate gradients and intra‐ and inter‐PFT competition. The indices underline a generally high FD of natural forests in Europe. Co‐existence of functionally diverse trees across PFTs emerges from alternative (life‐history) strategies, disturbance and tree demography. [ABSTRACT FROM AUTHOR]

Ecosystem service (ES) models can only inform policy design adequately if they incorporate ecological processes. We used the Lund-Potsdam-Jena managed Land (LPJmL) model, to address following questions for Mexico, Bolivia and Brazilian Amazon: (i) How different are C stocks and C sequestration quantifications under standard (when soil and litter C and heterotrophic respiration are not considered) and comprehensive (including all C stock and heterotrophic respiration) approach? and (ii)Howdoes the valuation of C stock and C sequestration differ in national payments for ES and global C funds or marketswhen comparing both approach?Wefound that up to 65%of C stocks have not been taken into account by neglecting to include C stored in soil and litter, resulting in gross underpayments (up to 500 times lower). Since emissions from heterotrophic respiration of organic material offset a large proportion of C gained through growth of living matter, we found thatmarkets and decision-makers are inadvertently overestimating up to 100 times C sequestrated. Newapproaches formodelling C services relevant ecological process-based can help accounting for C in soil, litter and heterotrophic respiration and become important for the operationalization of agreements on climate change mitigation following the COP21 in 2015. [ABSTRACT FROM AUTHOR]

Understanding the processes that determine above-ground biomass ( AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models ( DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity ( NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. [ABSTRACT FROM AUTHOR]

Identifying the relative importance of climatic and other environmental controls on the interannual variability and trends in global land surface phenology and greenness is challenging. Firstly, quantifications of land surface phenology and greenness dynamics are impaired by differences between satellite data sets and phenology detection methods. Secondly, dynamic global vegetation models (DGVMs) that can be used to diagnose controls still reveal structural limitations and contrasting sensitivities to environmental drivers. Thus, we assessed the performance of a new developed phenology module within the LPJmL (Lund-Potsdam-Jena managed Lands) DGVM with a comprehensive ensemble of three satellite data sets of vegetation greenness and ten phenology detection methods, thereby thoroughly accounting for observational uncertainties. The improved and tested model allows us quantifying the relative importance of environmental controls on interannual variability and trends of land surface phenology and greenness at regional and global scales. We found that start of growing season interannual variability and trends are in addition to cold temperature mainly controlled by incoming radiation and water availability in temperate and boreal forests. Warming-induced prolongations of the growing season in high latitudes are dampened by a limited availability of light. For peak greenness, interannual variability and trends are dominantly controlled by water availability and land-use and land-cover change (LULCC) in all regions. Stronger greening trends in boreal forests of Siberia than in North America are associated with a stronger increase in water availability from melting permafrost soils. Our findings emphasize that in addition to cold temperatures, water availability is a codominant control for start of growing season and peak greenness trends at the global scale. [ABSTRACT FROM AUTHOR]

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 ( Narea), the maximum carboxylation rate of Rubisco per leaf area ( [ABSTRACT FROM AUTHOR]

Global change includes multiple stressors to natural ecosystems ranging from direct climate and land-use impacts to indirect degradation processes resulting from fire. Humid tropical forests are vulnerable to projected climate change and possible synergistic interactions with deforestation and fire, which may initiate a positive feedback to rising atmospheric CO2. Here, we present results from a multifactorial impact analysis that combined an ensemble of climate change models with feedbacks from deforestation and accidental fires to quantify changes in Amazon Basin carbon cycling. Using the LPJmL Dynamic Global Vegetation Model, we modelled spatio-temporal changes in net biome production (NBP); the difference between carbon fluxes from fire, deforestation, soil respiration and net primary production. By 2050, deforestation and fire (with no CO2 increase or climate change) resulted in carbon losses of 7.4–20.3 Pg C with the range of uncertainty depending on socio-economic storyline. During the same time period, interactions between climate and land use either compensated for carbon losses due to wetter climate and CO2 fertilization or exacerbated carbon losses from drought-induced forest mortality (−20.1 to +4.3 Pg C). By the end of the 21st century, depending on climate projection and the rate of deforestation (including its interaction with fire), carbon stocks either increased (+12.6 Pg C) or decreased (−40.6 Pg C). The synergistic effect of deforestation and fire with climate change contributed up to 26–36 Pg C of the overall decrease in carbon stocks. Agreement between climate projections ( n=9), not accounting for deforestation and fire, in 2050 and 2098 was relatively low for the directional change in basin-wide NBP (19–37%) and aboveground live biomass (13–24%). The largest uncertainty resulted from climate projections, followed by implementation of ecosystem dynamics and deforestation. Our analysis partitions the drivers of tropical ecosystem change and is relevant for guiding mitigation and adaptation policy related to global change. [ABSTRACT FROM AUTHOR]