High exposure of global tree diversity to human pressure.

Safeguarding Earth's tree diversity is a conservation priority due to the importance of trees for biodiversity and ecosystem functions and services such as carbon sequestration. Here, we improve the foundation for effective conservation of global tree diversity by analyzing a recently developed database of tree species covering 46,752 species. We quantify range protection and anthropogenic pressures for each species and develop conservation priorities across taxonomic, phylogenetic, and functional diversity dimensions. We also assess the effectiveness of several influential proposed conservation prioritization frameworks to protect the top 17% and top 50% of tree priority areas. We find that an average of 50.2% of a tree species' range occurs in 110-km grid cells without any protected areas (PAs), with 6,377 small-range tree species fully unprotected, and that 83% of tree species experience nonnegligible human pressure across their range on average. Protecting high-priority areas for the top 17% and 50% priority thresholds would increase the average protected proportion of each tree species' range to 65.5% and 82.6%, respectively, leaving many fewer species (2,151 and 2,010) completely unprotected. The priority areas identified for trees match well to the Global 200 Ecoregions framework, revealing that priority areas for trees would in large part also optimize protection for terrestrial biodiversity overall. Based on range estimates for >46,000 tree species, our findings show that a large proportion of tree species receive limited protection by current PAs and are under substantial human pressure. Improved protection of biodiversity overall would also strongly benefit global tree diversity.

The acquisitive-conservative axis of leaf trait variation emerges even in homogeneous environments.

BACKGROUND AND AIMS: The acquisitive-conservative axis of plant ecological strategies results in a pattern of leaf trait covariation that captures the balance between leaf construction costs and plant growth potential. Studies evaluating trait covariation within species are scarcer, and have mostly dealt with variation in response to environmental gradients. Little work has been published on intraspecific patterns of leaf trait covariation in the absence of strong environmental variation. METHODS: We analysed covariation of four leaf functional traits [specific leaf area (SLA) leaf dry matter content (LDMC), force to tear (Ft) and leaf nitrogen content (Nm)] in six Poaceae and four Fabaceae species common in the dry Chaco forest of Central Argentina, growing in the field and in a common garden. We compared intraspecific covariation patterns (slopes, correlation and effect size) of leaf functional traits with global interspecific covariation patterns. Additionally, we checked for possible climatic and edaphic factors that could affect the intraspecific covariation pattern. KEY RESULTS: We found negative correlations for the LDMC-SLA, Ft-SLA, LDMC-Nm and Ft-Nm trait pairs. This intraspecific covariation pattern found both in the field and in the common garden and not explained by climatic or edaphic variation in the field follows the expected acquisitive-conservative axis. At the same time, we found quantitative differences in slopes among different species, and between these intraspecific patterns and the interspecific ones. Many of these differences seem to be idiosyncratic, but some appear consistent among species (e.g. all the intraspecific LDMC-SLA and LDMC-Nm slopes tend to be shallower than the global pattern). CONCLUSIONS: Our study indicates that the acquisitive-conservative leaf functional trait covariation pattern occurs at the intraspecific level even in the absence of relevant environmental variation in the field. This suggests a high degree of variation-covariation in leaf functional traits not driven by environmental variables.

Digging into the roots: understanding direct and indirect drivers of ecosystem service trade-offs in coastal grasslands via plant functional traits.

Recent empirical and theoretical approaches have called for an understanding of the processes underpinning ecosystem service provision. Environmental gradients have shown effects on key plant functional traits that subsequently explain ecosystem properties of several systems. However, little is known concerning how associations between plant functional traits, including both below- and aboveground plant components, predict ecosystem properties and independently measured final ecosystem services. Here, we modeled (1) the responses of the leaf and plant economics spectrum, Plant size axis, and root growth to environmental gradients and (2) how associations between plant functional traits explain trade-offs and synergies between multiple ecosystem properties and final services. Forty-four plots were studied in a coastal marsh landscape of the German North Sea Coast. We used a partial least square structural equation model approach to test the hypothesized model. We found (1) a negative covariation between plant traits pertaining to a size axis and traits explaining both plant growth (roots and stems) and the leaf economics spectrum; (2) this trade-off responded significantly to the land use gradient and nutrient availability, which were both strongly driven by the groundwater gradient; (3) this trade-off explained an initial major trade-off between carbon stocks, at one extreme of the axis, and both the habitat value to conserve endangered plants and forage production for meat and dairy products at the other extreme. However, a secondary trade-off between nature conservation value and forage production, explained by a trade-off between leaf economics spectrum and plant growth in response to the land use intensity gradient, was also found.

Does the leaf economic spectrum hold within plant functional types? A Bayesian multivariate trait meta-analysis.

The leaf economic spectrum is a widely studied axis of plant trait variability that defines a trade-off between leaf longevity and productivity. While this has been investigated at the global scale, where it is robust, and at local scales, where deviations from it are common, it has received less attention at the intermediate scale of plant functional types (PFTs). We investigated whether global leaf economic relationships are also present within the scale of plant functional types (PFTs) commonly used by Earth System models, and the extent to which this global-PFT hierarchy can be used to constrain trait estimates. We developed a hierarchical multivariate Bayesian model that assumes separate means and covariance structures within and across PFTs and fit this model to seven leaf traits from the TRY database related to leaf longevity, morphology, biochemistry, and photosynthetic metabolism. Although patterns of trait covariation were generally consistent with the leaf economic spectrum, we found three approximate tiers to this consistency. Relationships among morphological and biochemical traits (specific leaf area [SLA], N, P) were the most robust within and across PFTs, suggesting that covariation in these traits is driven by universal leaf construction trade-offs and stoichiometry. Relationships among metabolic traits (dark respiration [Rd ], maximum RuBisCo carboxylation rate [Vc,max ], maximum electron transport rate [Jmax ]) were slightly less consistent, reflecting in part their much sparser sampling (especially for high-latitude PFTs), but also pointing to more flexible plasticity in plant metabolistm. Finally, relationships involving leaf lifespan were the least consistent, indicating that leaf economic relationships related to leaf lifespan are dominated by across-PFT differences and that within-PFT variation in leaf lifespan is more complex and idiosyncratic. Across all traits, this covariance was an important source of information, as evidenced by the improved imputation accuracy and reduced predictive uncertainty in multivariate models compared to univariate models. Ultimately, our study reaffirms the value of studying not just individual traits but the multivariate trait space and the utility of hierarchical modeling for studying the scale dependence of trait relationships.

Mapping local and global variability in plant trait distributions.

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 ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-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.

Adaptive plasticity and fitness costs of endangered, nonendangered, and invasive plants in response to variation in nitrogen and phosphorus availabilities.

Global change drivers such as eutrophication and plant invasions will create novel environments for many plant species. Through adaptive trait plasticity plants may maintain their performance under these novel conditions and may outcompete those showing low-adaptive trait plasticity. In a greenhouse study, we determined if plasticity in traits is adaptive or maladaptive in endangered, nonendangered, and invasive plant species in response to variation of nitrogen (N) and phosphorus (P) availability (N:P ratios 1.7, 15, and 135) and whether plastic trait responses are adaptive and/or costly for fitness (i.e., biomass). Species choice comprised 17 species from three functional groups (legumes, nonlegume forbs, and grasses), either classified as endangered, nonendangered, or invasive. After 2 months, plants were harvested and nine traits related to carbon assimilation and nutrient uptake were measured (leaf area, SLA, LDMC, SPAD, RMR, root length, SRL, root surface area, and PME activity). We found more traits responding plastically to variation in P than in N. Plasticity only created costs when P was varied. Plasticity in traits was mostly adaptively neutral toward fitness, with plasticity in three traits being similarly adaptive across all species groups: SPAD (as a measure of chlorophyll content, adaptive to N and P limitation), leaf area, and root surface area (adaptive to P limitation). We found little differences in trait plasticity between endangered, nonendangered, and invasive species. Synthesis. Along a gradient from N limitation, balanced N:P supply, and P limitation, we found that the type of fluctuating nutrient (i.e., if N or P is varied) is decisive for the adaptive value of a trait. Variation in P availability (from balanced supply to P limitation) created both a stronger reduction in fitness as well as created plasticity costs in more traits than variation in N availability (from balanced supply to N limitation). However, the patterns observed in our study may change if nutrient availability is altered, either by nutrient inputs or by a shift in nutrient availabilities, for example, by decreasing N input as foreseen by European Legislation, but without simultaneously decreasing P input.

Leaf-level coordination principles propagate to the ecosystem scale.

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.

Global beta-diversity of angiosperm trees is shaped by Quaternary climate change.

As Earth's climate has varied strongly through geological time, studying the impacts of past climate change on biodiversity helps to understand the risks from future climate change. However, it remains unclear how paleoclimate shapes spatial variation in biodiversity. Here, we assessed the influence of Quaternary climate change on spatial dissimilarity in taxonomic, phylogenetic, and functional composition among neighboring 200-kilometer cells (beta-diversity) for angiosperm trees worldwide. We found that larger glacial-interglacial temperature change was strongly associated with lower spatial turnover (species replacements) and higher nestedness (richness changes) components of beta-diversity across all three biodiversity facets. Moreover, phylogenetic and functional turnover was lower and nestedness higher than random expectations based on taxonomic beta-diversity in regions that experienced large temperature change, reflecting phylogenetically and functionally selective processes in species replacement, extinction, and colonization during glacial-interglacial oscillations. Our results suggest that future human-driven climate change could cause local homogenization and reduction in taxonomic, phylogenetic, and functional diversity of angiosperm trees worldwide.

Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation.

Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land-climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles.

Negative bottom-up effects of sulfadiazine, but not penicillin and tetracycline, in soil substitute on plants and higher trophic levels.

Veterinary antibiotics are widely used in livestock production and can be released to the environment via manure, affecting non-target organisms. Recent studies provide evidence that antibiotics can adversely affect both plants and insects but whether antibiotics in soil also affect trophic interactions is unknown. We tested whether antibiotics grown in sand as soil substitute with environmentally relevant concentrations of penicillin, sulfadiazine and tetracycline affect the survival of aphids feeding on plants (two crop and one non-crop plant species). Apera spica-venti, Brassica napus, and Triticum aestivum individuals were infested with aphids that were monitored over four weeks. We did not observe effects of penicillin or tetracycline on plants or aphids. However, sulfadiazine treatments reduced plant growth and increased mortality in the two tested grass species, but not in B. napus. Sulfadiazine subsequently decreased aphid density indirectly through reduced host plant biomass. We thus show that an antibiotic at realistic concentrations in a soil substitute can affect several trophic levels, i.e. plants and herbivores. This study contributes to the environmental risk assessment of veterinary antibiotics as it implies that their use potentially affects plant-insect interactions at environmentally relevant concentrations.

Antibiotic-induced effects on scaling relationships and on plant element contents in herbs and grasses.

Plant performance is correlated with element concentrations in plant tissue, which may be impacted by adverse chemical soil conditions. Antibiotics of veterinary origin can adversely affect plant performance. They are released to agricultural fields via grazing animals or manure, taken up by plants and may be stored, transformed or sequestered by plant metabolic processes. We studied the potential effects of three antibiotics (penicillin, sulfadiazine, and tetracycline) on plant element contents (macro- and microelements). Plant species included two herb species (Brassica napus and Capsella bursa-pastoris) and two grass species (Triticum aestivum and Apera spica-venti), representing two crop species and two noncrop species commonly found in field margins, respectively. Antibiotic concentrations were chosen as to reflect in vivo situations, that is, relatively low concentrations similar to those detected in soils. In a greenhouse experiment, plants were raised in soil spiked with antibiotics. After harvest, macro- and microelements in plant leaves, stems, and roots were determined (mg/g). Results indicate that antibiotics can affect element contents in plants. Penicillin exerted the greatest effect both on element contents and on scaling relationships of elements between plant organs. Roots responded strongest to antibiotics compared to stems and leaves. We conclude that antibiotics in the soil, even in low concentrations, lead to low-element homeostasis, altering the scaling relationships between roots and other plant organs, which may affect metabolic processes and ultimately the performance of a plant.

Social bees are fitter in more biodiverse environments.

Bee population declines are often linked to human impacts, especially habitat and biodiversity loss, but empirical evidence is lacking. To clarify the link between biodiversity loss and bee decline, we examined how floral diversity affects (reproductive) fitness and population growth of a social stingless bee. For the first time, we related available resource diversity and abundance to resource (quality and quantity) intake and colony reproduction, over more than two years. Our results reveal plant diversity as key driver of bee fitness. Social bee colonies were fitter and their populations grew faster in more florally diverse environments due to a continuous supply of food resources. Colonies responded to high plant diversity with increased resource intake and colony food stores. Our findings thus point to biodiversity loss as main reason for the observed bee decline.

Phylogenetic patterns and phenotypic profiles of the species of plants and mammals farmed for food.

The origins of agriculture were key events in human history, during which people came to depend for their food on small numbers of animal and plant species. However, the biological traits determining which species were domesticated for food provision, and which were not, are unclear. Here, we investigate the phylogenetic distribution of livestock and crops, and compare their phenotypic traits with those of wild species. Our results indicate that phylogenetic clustering is modest for crop species but more intense for livestock. Domesticated species explore a reduced portion of the phenotypic space occupied by their wild counterparts and have particular traits in common. For example, herbaceous crops are globally characterized by traits including high leaf nitrogen concentration and tall canopies, which make them fast-growing species and proficient competitors. Livestock species are relatively large mammals with low basal metabolic rates, which indicate moderate to slow life histories. Our study therefore reveals ecological differences in domestication potential between plants and mammals. Domesticated plants belong to clades with traits that are advantageous in intensively managed high-resource habitats, whereas domesticated mammals are from clades adapted to moderately productive environments. Combining comparative phylogenetic methods with ecologically relevant traits has proven useful to unravel the causes and consequences of domestication.

Multiple facets of biodiversity drive the diversity-stability relationship.

A substantial body of evidence has demonstrated that biodiversity stabilizes ecosystem functioning over time in grassland ecosystems. However, the relative importance of different facets of biodiversity underlying the diversity-stability relationship remains unclear. Here we use data from 39 grassland biodiversity experiments and structural equation modelling to investigate the roles of species richness, phylogenetic diversity and both the diversity and community-weighted mean of functional traits representing the 'fast-slow' leaf economics spectrum in driving the diversity-stability relationship. We found that high species richness and phylogenetic diversity stabilize biomass production via enhanced asynchrony in the performance of co-occurring species. Contrary to expectations, low phylogenetic diversity enhances ecosystem stability directly, albeit weakly. While the diversity of fast-slow functional traits has a weak effect on ecosystem stability, communities dominated by slow species enhance ecosystem stability by increasing mean biomass production relative to the standard deviation of biomass over time. Our in-depth, integrative assessment of factors influencing the diversity-stability relationship demonstrates a more multicausal relationship than has been previously acknowledged.

Antibiotics impact plant traits, even at small concentrations.

Antibiotics of veterinary origin are released to agricultural fields via grazing animals or manure. Possible effects on human health through the consumption of antibiotic exposed crop plants have been intensively investigated. However, information is still lacking on the effects of antibiotics on plants themselves, particularly on non-crop species, although evidence suggests adverse effects of antibiotics on growth and performance of plants. This study evaluated the effects of three major antibiotics, penicillin, sulfadiazine and tetracycline, on the germination rates and post-germinative traits of four plant species during ontogenesis and at the time of full development. Antibiotic concentrations were chosen as to reflect in vivo situations, i.e. concentrations similar to those detected in soils. Plant species included two herb species and two grass species, and represent two crop-species and two non-crop species commonly found in field margins, respectively. Germination tests were performed in climate chambers and effects on the remaining plant traits were determined in greenhouse experiments. Results show that antibiotics, even in small concentrations, significantly affect plant traits. These effects include delayed germination and post-germinative development. Effects were species and functional group dependent, with herbs being more sensitive to antibiotics then grasses. Responses were either negative or positive, depending on plant species and antibiotic. Effects were generally stronger for penicillin and sulfadiazine than for tetracycline. Our study shows that cropland species respond to the use of different antibiotics in livestock industry, for example, with delayed germination and lower biomass allocation, indicating possible effects on yield in farmland fertilized with manure containing antibiotics. Also, antibiotics can alter the composition of plant species in natural field margins, due to different species-specific responses, with unknown consequences for higher trophic levels.

Consistent drivers of plant biodiversity across managed ecosystems.

Ecosystems managed for production of biomass are often characterized by low biodiversity because management aims to optimize single ecosystem functions (i.e. yield) involving deliberate selection of species or cultivars. In consequence, considerable differences in observed plant species richness and productivity remain across systems, and the drivers of these differences have remained poorly resolved so far. In addition, it has remained unclear if species richness feeds back on ecosystem functions such as yield in real-world systems. Here, we establish N = 360 experimental plots across a broad range of managed ecosystems in several European countries, and use structural equation models to unravel potential drivers of plant species richness. We hypothesize that the relationships between productivity, total biomass and observed species richness are affected by management intensity, and that these effects differ between habitat types (dry grasslands, grasslands, and wetlands). We found that local management was an important driver of species richness across systems. Management caused system disturbance, resulting in reduced productivity yet enhanced total biomass. Plant species richness was directly and positively driven by management, with consistently negative effects of total biomass. Productivity effects on richness were positive, negative or neutral. Our study shows that management and total biomass drive plant species richness across real-world managed systems.

The influence of balanced and imbalanced resource supply on biodiversity-functioning relationship across ecosystems.

Numerous studies show that increasing species richness leads to higher ecosystem productivity. This effect is often attributed to more efficient portioning of multiple resources in communities with higher numbers of competing species, indicating the role of resource supply and stoichiometry for biodiversity-ecosystem functioning relationships. Here, we merged theory on ecological stoichiometry with a framework of biodiversity-ecosystem functioning to understand how resource use transfers into primary production. We applied a structural equation model to define patterns of diversity-productivity relationships with respect to available resources. Meta-analysis was used to summarize the findings across ecosystem types ranging from aquatic ecosystems to grasslands and forests. As hypothesized, resource supply increased realized productivity and richness, but we found significant differences between ecosystems and study types. Increased richness was associated with increased productivity, although this effect was not seen in experiments. More even communities had lower productivity, indicating that biomass production is often maintained by a few dominant species, and reduced dominance generally reduced ecosystem productivity. This synthesis, which integrates observational and experimental studies in a variety of ecosystems and geographical regions, exposes common patterns and differences in biodiversity-functioning relationships, and increases the mechanistic understanding of changes in ecosystems productivity.