Peter M. van Bodegom

Quantitative assessment of the differential impacts of arbuscular and ectomycorrhiza on soil carbon cycling

A significant fraction of carbon stored in the Earths soil moves through arbuscular mycorrhiza (AM) and ectomycorrhiza (EM). The impacts of AM and EM on the soil carbon budget are poorly understood. We propose a method to quantify the mycorrhizal contribution to carbon cycling, explicitly accounting for the abundance of plant-associated and extraradical mycorrhizal mycelium. We discuss the need to acquire additional data to use our method, and present our new global database holding information on plant species-by-site intensity of root colonization by mycorrhizas. We demonstrate that the degree of mycorrhizal fungal colonization has globally consistent patterns across plant species. This suggests that the level of plant species-specific root colonization can be used as a plant trait. To exemplify our method, we assessed the differential impacts of AMxa0:xa0EM ratio and EM shrub encroachment on carbon stocks in sub-arctic tundra. AM and EM affect tundra carbon stocks at different magnitudes, and via partly distinct dominant pathways: via extraradical mycelium (both EM and AM) and via mycorrhizal impacts on above- and belowground biomass carbon (mostly AM). Our method provides a powerful tool for the quantitative assessment of mycorrhizal impact on local and global carbon cycling processes, paving the way towards an improved understanding of the role of mycorrhizas in the Earths carbon cycle.

A global Fine-Root Ecology Database to address below-ground challenges in plant ecology

Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. While fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes >xa070xa0000 observations encompassing a broad range of root traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. Continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time.

A global method for calculating plant CSR ecological strategies applied across biomes world‐wide

Summary nCompetitor, stress-tolerator, ruderal (CSR) theory is a prominent plant functional strategy scheme previously applied to local floras. Globally, the wide geographic and phylogenetic coverage of available values of leaf area (LA), leaf dry matter content (LDMC) and specific leaf area (SLA) (representing, respectively, interspecific variation in plant size and conservative vs. acquisitive resource economics) promises the general application of CSR strategies across biomes, including the tropical forests hosting a large proportion of Earths diversity. nWe used trait variation for 3068 tracheophytes (representing 198 families, six continents and 14 biomes) to create a globally calibrated CSR strategy calculator tool and investigate strategy–environment relationships across biomes world-wide. nDue to disparity in trait availability globally, co-inertia analysis was used to check correspondence between a ‘wide geographic coverage, few traits’ data set and a ‘restricted coverage, many traits’ subset of 371 species for which 14 whole-plant, flowering, seed and leaf traits (including leaf nitrogen content) were available. CSR strategy/environment relationships within biomes were investigated using fourth-corner and RLQ analyses to determine strategy/climate specializations. nStrong, significant concordance (RVxa0=xa00·597; Pxa0<xa00·0001) was evident between the 14 trait multivariate space and when only LA, LDMC and SLA were used. nBiomes such as tropical moist broadleaf forests exhibited strategy convergence (i.e. clustered around a CS/CSR median; C:S:Rxa0=xa043:42:15%), with CS-selection associated with warm, stable situations (lesser temperature seasonality), with greater annual precipitation and potential evapotranspiration. Other biomes were characterized by strategy divergence: for example, deserts varied between xeromorphic perennials such as Larrea divaricata, classified as S-selected (C:S:Rxa0=xa01:99:0%) and broadly R-selected annual herbs (e.g. Claytonia perfoliata; R/CR-selected; C:S:Rxa0=xa021:0:79%). Strategy convergence was evident for several growth habits (e.g. trees) but not others (forbs). nThe CSR strategies of vascular plants can now be compared quantitatively within and between biomes at the global scale. Through known linkages between underlying leaf traits and growth rates, herbivory and decomposition rates, this method and the strategy–environment relationships it elucidates will help to predict which kinds of species may assemble in response to changes in biogeochemical cycles, climate and land use.

Burn or rot: leaf traits explain why flammability and decomposability are decoupled across species

Summary nIn fireprone ecosystems, two important alternative fates for leaves are burning in a wildfire (when alive or as litter) or they get consumed (as litter) by decomposers. The influence of leaf traits on litter decomposition rate is reasonably well understood. In contrast, less is known about the influence of leaf traits on leaf and litter flammability. The aim of this study was twofold: (i) to determine which morphological and chemical leaf traits drive flammability and (ii) to determine whether different (combinations of) morphological and chemical leaf traits drive interspecific variation in decomposition and litter flammability and, in turn, help us understand the relationship between decomposability and flammability. nTo explore the relationships between leaf traits and flammability of individual leaves, we used 32 evergreen perennial plant species from eastern Australia in standardized experimental burns on three types of leaf material (i.e. fresh, dried and senesced). Next, we compared these trait–flammability relationships to trait–decomposability relationships as obtained from a previous decomposition experiment (focusing on senesced leaves only). nWithin the three parameters of leaf flammability that we measured, interspecific variation in time to ignition was mainly explained by specific leaf area and moisture content. Flame duration and smoulder duration were mostly explained by leaf dry mass and to a lesser degree by leaf chemistry, namely, nitrogen, phosphorus and tannin concentrations. nThe variation in the decomposition constant across species was unrelated to our measures of flammability. Moreover, different combinations of morphological and chemical leaf properties underpinned the interspecific variation in decomposability and flammability. In contrast to litter flammability, decomposability was driven by lignin and phosphorus concentrations. nThe decoupling of flammability and decomposability leads to three possible scenarios for species’ influence on litter fates: (i) fast-decomposing species for which flammability is irrelevant because there will not be enough litter to support a fire; (ii) species with slow-decomposing leaves and a high flammability; and (iii) species with slow-decomposing leaves and a low flammability. We see potential for making use of the decoupled trait–decomposition–flammability relationships when modelling carbon and nutrient fluxes. Including information on leaf traits in models can improve the prediction of fire behaviour. We note that herbivory is another key fate for leaves, but this study was focused on fire and decomposition.

Invasive species’ leaf traits and dissimilarity from natives shape their impact on nitrogen cycling: a meta-analysis

Many exotic species have little apparent impact on ecosystem processes, whereas others have dramatic consequences for human and ecosystem health. There is growing evidence that invasions foster eutrophication. We need to identify species that are harmful and systems that are vulnerable to anticipate these consequences. Species traits may provide the necessary insights. We conducted a global meta-analysis to determine whether plant leaf and litter functional traits, and particularly leaf and litter nitrogen (N) content and carbon: nitrogen (Cxa0:xa0N) ratio, explain variation in invasive species impacts on soil N cycling. Dissimilarity in leaf and litter traits among invaded and noninvaded plant communities control the magnitude and direction of invasion impacts on N cycling. Invasions that caused the greatest increases in soil inorganic N and mineralization rates had a much greater litter N content and lower litter Cxa0:xa0N in the invaded than the reference community. Trait dissimilarities were better predictors than the trait values of invasive species alone. Quantifying baseline community tissue traits, in addition to those of the invasive species, is critical to understanding the impacts of invasion on soil N cycling.

Variation in trait trade‐offs allows differentiation among predefined plant functional types: implications for predictive ecology

Plant functional types (PFTs) aggregate the variety of plant species into a small number of functionally different classes. We examined to what extent plant traits, which reflect species functional adaptations, can capture functional differences between predefined PFTs and which traits optimally describe these differences. We applied Gaussian kernel density estimation to determine probability density functions for individual PFTs in an n-dimensional trait space and compared predicted PFTs with observed PFTs. All possible combinations of 1-6 traits from a database with 18 different traits (total of 18 287 species) were tested. A variety of trait sets had approximately similar performance, and 4-5 traits were sufficient to classify up to 85% of the species into PFTs correctly, whereas this was 80% for a bioclimatically defined tree PFT classification. Well-performing trait sets included combinations of correlated traits that are considered functionally redundant within a single plant strategy. This analysis quantitatively demonstrates how structural differences between PFTs are reflected in functional differences described by particular traits. Differentiation between PFTs is possible despite large overlap in plant strategies and traits, showing that PFTs are differently positioned in multidimensional trait space. This study therefore provides the foundation for important applications for predictive ecology.

The imprint of plants on ecosystem functioning: A data-driven approach

Abstract Terrestrial ecosystems strongly determine the exchange of carbon, water and energy between the biosphere and atmosphere. These exchanges are influenced by environmental conditions (e.g., local meteorology, soils), but generally mediated by organisms. Often, mathematical descriptions of these processes are implemented in terrestrial biosphere models. Model implementations of this kind should be evaluated by empirical analyses of relationships between observed patterns of ecosystem functioning, vegetation structure, plant traits, and environmental conditions. However, the question of how to describe the imprint of plants on ecosystem functioning based on observations has not yet been systematically investigated. One approach might be to identify and quantify functional attributes or responsiveness of ecosystems (often very short-term in nature) that contribute to the long-term (i.e., annual but also seasonal or daily) metrics commonly in use. Here we define these patterns as “ecosystem functional properties”, or EFPs. Such as the ecosystem capacity of carbon assimilation or the maximum light use efficiency of an ecosystem. While EFPs should be directly derivable from flux measurements at the ecosystem level, we posit that these inherently include the influence of specific plant traits and their local heterogeneity. We present different options of upscaling in situ measured plant traits to the ecosystem level (ecosystem vegetation properties – EVPs) and provide examples of empirical analyses on plants’ imprint on ecosystem functioning by combining in situ measured plant traits and ecosystem flux measurements. Finally, we discuss how recent advances in remote sensing contribute to this framework.

Geothermal ecosystems as natural climate change experiments : The ForHot research site in Iceland as a case study

This article describes how natural geothermal soil temperature gradients in Iceland have been used to study terrestrial ecosystem responses to soil warming. The experimental approach was evaluated at three study sites in southern Iceland; one grassland site that has been warm for at least 50 years (GO), and another comparable grassland site (GN) and a Sitka spruce plantation (FN) site that have both been warmed since an earthquake took place in 2008. Within each site type, five ca. 50 m long transects, with six permanent study plots each, were established across the soil warming gradients, spanning from unwarmed control conditions to gradually warmer soils. It was attempted to select the plots so the annual warming levels would be ca. +1, +3, +5, +10 and +20 °C within each transect. Results of continuous measurements of soil temperature (Ts) from 2013-2015 revealed that the soil warming was relatively constant and followed the seasonal Ts cycle of the unwarmed control plots. Volumetric water content in the top 5 cm of soil was repeatedly surveyed during 2013-2016. The grassland soils were wetter than the FN soils, but they had sometimes some significant warming-induced drying in the surface layer of the warmest plots, in contrast to FN. Soil chemistry did not show any indications that geothermal water had reached the root zone, but soil pH did increase somewhat with warming, which was probably linked to vegetation changes. As expected, the potential decomposition rate of organic matter increased significantly with warming. It was concluded that the natural geothermal gradients at the ForHot sites in Iceland offered realistic conditions for studying terrestrial ecosystem responses to warming with minimal artefacts.

Mapping local and global variability in plant trait distributions

Significance Currently, Earth system models (ESMs) represent variation in plant life through the presence of a small set of plant functional types (PFTs), each of which accounts for hundreds or thousands of species across thousands of vegetated grid cells on land. By expanding plant traits from a single mean value per PFT to a full distribution per PFT that varies among grid cells, the trait variation present in nature is restored and may be propagated to estimates of ecosystem processes. Indeed, critical ecosystem processes tend to depend on the full trait distribution, which therefore needs to be represented accurately. These maps reintroduce substantial local variation and will allow for a more accurate representation of the land surface in ESMs. Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration—specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ∼50×50-km cells across the entire vegetated land surface. We do this in several ways—without defining the PFT of each grid cell and using 4 or 14 PFTs; each model’s predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.

Drivers of Bacterial Maintenance and Minimal Energy Requirements

Microbes maintain themselves through a variety of processes. Several of these processes can be reduced or shut down entirely when resource availability declines. In pure culture conditions with ample substrate supply, a relationship between the maximum growth rate and the energy invested in maintenance has been reported widely. However, at the other end of the resources spectrum, bacteria are so extremely limited by energy that no growth occurs and metabolism is constrained to the most essential functions only. These minimum energy requirements have been called the basal power requirement. While seemingly different from each other, both aspects are likely components of a continuum of regulated maintenance processes. Here, we analyze cross-species tradeoffs in cellular physiology over the range of bacterial size and energy expenditure and determine the contributions to maintenance metabolism at each point along the size-energy spectrum. Furthermore, by exploring the simplest bacteria within this framework– which are most affected by maintenance constraints– we uncover which processes become most limiting. For the smallest species, maintenance metabolism converges on total metabolism, where we predict that maintenance is dominated by the repair of proteins. For larger species the relative costs of protein repair decrease and maintenance metabolism is predicted to be dominated by the repair of RNA components. These results provide new insights into which processes are likely to be regulated in environments that are extremely limited by energy.