Impacts of climate timescale on the stability of trait-environment relationships.

Predictive relationships between plant traits and environmental factors can be derived at global and regional scales, informing efforts to reorient ecological models around functional traits. However, in a changing climate, the environmental variables used as predictors in such relationships are far from stationary. This could yield errors in trait-environment model predictions if timescale is not accounted for. Here, the timescale dependence of trait-environment relationships is investigated by regressing in situ trait measurements of specific leaf area, leaf nitrogen content, and wood density on local climate characteristics summarized across several increasingly long timescales. We identify contrasting responses of leaf and wood traits to climate timescale. Leaf traits are best predicted by recent climate timescales, while wood density is a longer term memory trait. The use of sub-optimal climate timescales reduces the accuracy of the resulting trait-environment relationships. This study concludes that plant traits respond to climate conditions on the timescale of tissue lifespans rather than long-term climate normals, even at large spatial scales where multiple ecological and physiological mechanisms drive trait change. Thus, determining trait-environment relationships with temporally relevant climate variables may be critical for predicting trait change in a nonstationary climate system.

Leaf trait coordination and variation of blue oak across topo-environmental scales.

Trees are arguably the most diverse and complex macro-organisms on Earth. The equally diverse functions of trees directly impact fluxes of carbon, water and energy from the land surface. A number of recent studies have shed light on the substantial within-species variability across plant traits, including aspects of leaf morphology and plant allocation of photosynthates to leaf biomass. Yet, within-tree variability in leaf traits due to microclimatic variations, leaf hydraulic coordination across traits at different physiological scales and variations in leaf traits over a growing season remain poorly studied. This knowledge gap is stymieing the fundamental understanding of what drives trait variation and covariation from tissues to trees to landscapes. Here, we present an extensive dataset measuring within-tree heterogeneity in leaf traits in California's blue oak (Quercus douglasii) across an edaphic gradient and over the course of a growing season at an oak-grass savanna in Southern CA, USA. We found a high level of within-tree crown leaf area:sapwood area variation that was not attributable to sample height or aspect. We also found a higher level of trait integration at the tree level, rather than branch level, suggesting that trees optimize water use at the organismal level. Despite the large variance in traits within a tree crown and across trees, we did not find strong evidence for adaptive plasticity or acclimation in leaf morphological traits (e.g., changes to phenotype which increased fitness) across temporal and spatial water availability gradients. Collectively, our results highlight strong variation in drought-related physiology, but limited evidence for adaptive trait plasticity over shorter time scales.

Capturing patterns of evolutionary relatedness with reflectance spectra to model and monitor biodiversity.

Biogeographic history can set initial conditions for vegetation community assemblages that determine their climate responses at broad extents that land surface models attempt to forecast. Numerous studies have indicated that evolutionarily conserved biochemical, structural, and other functional attributes of plant species are captured in visible-to-short wavelength infrared, 400 to 2,500 nm, reflectance properties of vegetation. Here, we present a remotely sensed phylogenetic clustering and an evolutionary framework to accommodate spectra, distributions, and traits. Spectral properties evolutionarily conserved in plants provide the opportunity to spatially aggregate species into lineages (interpreted as "lineage functional types" or LFT) with improved classification accuracy. In this study, we use Airborne Visible/Infrared Imaging Spectrometer data from the 2013 Hyperspectral Infrared Imager campaign over the southern Sierra Nevada, California flight box, to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from 1372 surveys and a phylogeny representing 1,572 species. Despite temporal and spatial differences in our training data, we classified plant lineages with moderate reliability (Kappa = 0.76) and overall classification accuracy of 80.9%. We present an assessment of classification error and detail study limitations to facilitate future LFT development. This work demonstrates that lineage-based methods may be a promising way to leverage the new-generation high-resolution and high return-interval hyperspectral data planned for the forthcoming satellite missions with sparsely sampled existing ground-based ecological data.

Why can't we predict traits from the environment?

Plant functional traits are powerful ecological tools, but the relationships between plant traits and climate (or environmental variables more broadly) are often remarkably weak. This presents a paradox: Plant traits govern plant interactions with their environment, but the environment does not strongly predict the traits of plants living there. Unpacking this paradox requires differentiating the mechanisms of trait variation and potential confounds of trait-environment relationships at different evolutionary and ecological scales ranging from within species to among communities. It also necessitates a more integrated understanding of physiological and evolutionary equifinality among many traits and plant strategies, and challenges us to understand how supposedly 'functional' traits integrate into a whole-organism phenotype in ways that may be largely orthogonal to environmental tolerances.

Representing plant diversity in land models: An evolutionary approach to make "Functional Types" more functional.

Plants are critical mediators of terrestrial mass and energy fluxes, and their structural and functional traits have profound impacts on local and global climate, biogeochemistry, biodiversity, and hydrology. Yet, Earth System Models (ESMs), our most powerful tools for predicting the effects of humans on the coupled biosphere-atmosphere system, simplify the incredible diversity of land plants into a handful of coarse categories of "Plant Functional Types" (PFTs) that often fail to capture ecological dynamics such as biome distributions. The inclusion of more realistic functional diversity is a recognized goal for ESMs, yet there is currently no consistent, widely accepted way to add diversity to models, that is, to determine what new PFTs to add and with what data to constrain their parameters. We review approaches to representing plant diversity in ESMs and draw on recent ecological and evolutionary findings to present an evolution-based functional type approach for further disaggregating functional diversity. Specifically, the prevalence of niche conservatism, or the tendency of closely related taxa to retain similar ecological and functional attributes through evolutionary time, reveals that evolutionary relatedness is a powerful framework for summarizing functional similarities and differences among plant types. We advocate that Plant Functional Types based on dominant evolutionary lineages ("Lineage Functional Types") will provide an ecologically defensible, tractable, and scalable framework for representing plant diversity in next-generation ESMs, with the potential to improve parameterization, process representation, and model benchmarking. We highlight how the importance of evolutionary history for plant function can unify the work of disparate fields to improve predictive modeling of the Earth system.

Keep your friends close: Host compartmentalisation of microbial communities facilitates decoupling from effects of habitat fragmentation.

Root-associated fungal communities modify the climatic niches and even the competitive ability of their hosts, yet how the different components of the root microbiome are modified by habitat loss remains a key knowledge gap. Using principles of landscape ecology, we tested how free-living versus host-associated microbes differ in their response to landscape heterogeneity. Further, we explore how compartmentalisation of microbes into specialised root structures filters for key fungal symbionts. Our study demonstrates that free-living fungal community structure correlates with landscape heterogeneity, but that host-associated fungal communities depart from these patterns. Specifically, biotic filtering in roots, especially via compartmentalisation within specialised root structures, decouples the biogeographic patterns of host-associated fungal communities from the soil community. In this way, even as habitat loss and fragmentation threaten fungal diversity in the soils, plant hosts exert biotic controls to ensure associations with critical mutualists, helping to preserve the root mycobiome.

Why is Tree Drought Mortality so Hard to Predict?

Widespread tree mortality following droughts has emerged as an environmentally and economically devastating 'ecological surprise'. It is well established that tree physiology is important in understanding drought-driven mortality; however, the accuracy of predictions based on physiology alone has been limited. We propose that complicating factors at two levels stymie predictions of drought-driven mortality: (i) organismal-level physiological and site factors that obscure understanding of drought exposure and vulnerability and (ii) community-level ecological interactions, particularly with biotic agents whose effects on tree mortality may reverse expectations based on stress physiology. We conclude with a path forward that emphasizes the need for an integrative approach to stress physiology and biotic agent dynamics when assessing forest risk to drought-driven morality in a changing climate.

Evolutionary relationships between drought-related traits and climate shape large hydraulic safety margins in western North American oaks.

Quantitative knowledge of xylem physical tolerance limits to dehydration is essential to understanding plant drought tolerance but is lacking in many long-vessel angiosperms. We examine the hypothesis that a fundamental association between sustained xylem water transport and downstream tissue function should select for xylem that avoids embolism in long-vessel trees by quantifying xylem capacity to withstand air entry of western North American oaks (Quercus spp.). Optical visualization showed that 50% of embolism occurs at water potentials below -2.7 MPa in all 19 species, and -6.6 MPa in the most resistant species. By mapping the evolution of xylem vulnerability to embolism onto a fossil-dated phylogeny of the western North American oaks, we found large differences between clades (sections) while closely related species within each clade vary little in their capacity to withstand air entry. Phylogenetic conservatism in xylem physical tolerance, together with a significant correlation between species distributions along rainfall gradients and their dehydration tolerance, suggests that closely related species occupy similar climatic niches and that species' geographic ranges may have shifted along aridity gradients in accordance with their physical tolerance. Such trends, coupled with evolutionary associations between capacity to withstand xylem embolism and other hydraulic-related traits, yield wide margins of safety against embolism in oaks from diverse habitats. Evolved responses of the vascular system to aridity support the embolism avoidance hypothesis and reveal the importance of quantifying plant capacity to withstand xylem embolism for understanding function and biogeography of some of the Northern Hemisphere's most ecologically and economically important plants.

Anthropogenic climate change is worsening North American pollen seasons.

Airborne pollen has major respiratory health impacts and anthropogenic climate change may increase pollen concentrations and extend pollen seasons. While greenhouse and field studies indicate that pollen concentrations are correlated with temperature, a formal detection and attribution of the role of anthropogenic climate change in continental pollen seasons is urgently needed. Here, we use long-term pollen data from 60 North American stations from 1990 to 2018, spanning 821 site-years of data, and Earth system model simulations to quantify the role of human-caused climate change in continental patterns in pollen concentrations. We find widespread advances and lengthening of pollen seasons (+20 d) and increases in pollen concentrations (+21%) across North America, which are strongly coupled to observed warming. Human forcing of the climate system contributed ∼50% (interquartile range: 19-84%) of the trend in pollen seasons and ∼8% (4-14%) of the trend in pollen concentrations. Our results reveal that anthropogenic climate change has already exacerbated pollen seasons in the past three decades with attendant deleterious effects on respiratory health.

Aridity drives coordinated trait shifts but not decreased trait variance across the geographic range of eight Australian trees.

Large intraspecific functional trait variation strongly impacts many aspects of communities and ecosystems, and is the medium upon which evolution works. Yet intraspecific trait variation is inconsistent and hard to predict across traits, species and locations. We measured within-species variation in leaf mass per area (LMA), leaf dry matter content (LDMC), branch wood density (WD), and allocation to stem area vs leaf area in branches (branch Huber value (HV)) across the aridity range of seven Australian eucalypts and a co-occurring Acacia species to explore how traits and their variances change with aridity. Within species, we found consistent increases in LMA, LDMC and WD and HV with increasing aridity, resulting in consistent trait coordination across leaves and branches. However, this coordination only emerged across sites with large climate differences. Unlike trait means, patterns of trait variance with aridity were mixed across populations and species. Only LDMC showed constrained trait variation in more xeric species and drier populations that could indicate limits to plasticity or heritable trait variation. Our results highlight that climate can drive consistent within-species trait patterns, but that patterns might often be obscured by the complex nature of morphological traits, sampling incomplete species ranges or sampling confounded stress gradients.

Continental-scale tree-ring-based projection of Douglas-fir growth: Testing the limits of space-for-time substitution.

A central challenge in global change research is the projection of the future behavior of a system based upon past observations. Tree-ring data have been used increasingly over the last decade to project tree growth and forest ecosystem vulnerability under future climate conditions. But how can the response of tree growth to past climate variation predict the future, when the future does not look like the past? Space-for-time substitution (SFTS) is one way to overcome the problem of extrapolation: the response at a given location in a warmer future is assumed to follow the response at a warmer location today. Here we evaluated an SFTS approach to projecting future growth of Douglas-fir (Pseudotsuga menziesii), a species that occupies an exceptionally large environmental space in North America. We fit a hierarchical mixed-effects model to capture ring-width variability in response to spatial and temporal variation in climate. We found opposing gradients for productivity and climate sensitivity with highest growth rates and weakest response to interannual climate variation in the mesic coastal part of Douglas-fir's range; narrower rings and stronger climate sensitivity occurred across the semi-arid interior. Ring-width response to spatial versus temporal temperature variation was opposite in sign, suggesting that spatial variation in productivity, caused by local adaptation and other slow processes, cannot be used to anticipate changes in productivity caused by rapid climate change. We thus substituted only climate sensitivities when projecting future tree growth. Growth declines were projected across much of Douglas-fir's distribution, with largest relative decreases in the semiarid U.S. Interior West and smallest in the mesic Pacific Northwest. We further highlight the strengths of mixed-effects modeling for reviving a conceptual cornerstone of dendroecology, Cook's 1987 aggregate growth model, and the great potential to use tree-ring networks and results as a calibration target for next-generation vegetation models.

Critical transition to woody plant dominance through microclimate feedbacks in North American coastal ecosystems.

Climate warming is facilitating the expansion of many cold-sensitive woody species in woodland-grassland ecotones worldwide. Recent research has demonstrated that this range expansion can be further enhanced by positive vegetation-microclimate feedbacks whereby woody canopies induce local nocturnal warming, which reduces freeze-induced damage and favors the establishment of woody plants. However, this local positive feedback can be counteracted by biotic drivers such as browsing and the associated consumption of shrub biomass. The joint effects of large-scale climate warming and local-scale microclimate feedbacks on woody vegetation dynamics in these ecotones remain poorly understood. Here, we used a combination of experimental and modeling approaches to investigate the effects of woody cover on microclimate and the consequent implications on ecological stability in North American coastal ecosystems. We found greater browsing pressure and significant warming (~2°C) beneath shrub canopies compared to adjacent grasslands, which reduces shrub seedlings' exposure to cold damage. Cold sensitivity is evidenced by the significant decline in xylem hydraulic conductivity in shrub seedlings when temperatures dropped below -2°C. Despite the negative browsing-vegetation feedback, a small increase in minimum temperature can induce critical transitions from grass to woody plant dominance. Our framework also predicts the threshold temperature of -7°C for mangrove-salt marsh ecotones on the Atlantic coast of Florida. Above this reference temperature a critical transition may occur from salt marsh to mangrove vegetation, in agreement with empirical studies. Thus, the interaction between ongoing global warming trends and microclimate feedbacks may significantly alter woody vegetation dynamics and ecological stability in coastal ecosystems where woody plant expansion is primarily constrained by extreme low temperature events.

Trait velocities reveal that mortality has driven widespread coordinated shifts in forest hydraulic trait composition.

Understanding the driving mechanisms behind existing patterns of vegetation hydraulic traits and community trait diversity is critical for advancing predictions of the terrestrial carbon cycle because hydraulic traits affect both ecosystem and Earth system responses to changing water availability. Here, we leverage an extensive trait database and a long-term continental forest plot network to map changes in community trait distributions and quantify "trait velocities" (the rate of change in community-weighted traits) for different regions and different forest types across the United States from 2000 to the present. We show that diversity in hydraulic traits and photosynthetic characteristics is more related to local water availability than overall species diversity. Finally, we find evidence for coordinated shifts toward communities with more drought-tolerant traits driven by tree mortality, but the magnitude of responses differs depending on forest type. The hydraulic trait distribution maps provide a publicly available platform to fundamentally advance understanding of community trait change in response to climate change and predictive abilities of mechanistic vegetation models.

Urinary Stone Disease in Pregnancy: A Claims Based Analysis of 1.4 Million Patients.

PURPOSE: Urinary stone disease during pregnancy is poorly understood but is thought to be associated with increased maternal and fetal morbidity. We determined the prevalence of urinary stone disease in pregnancy and whether it is associated with adverse pregnancy outcomes. MATERIALS AND METHODS: We identified all pregnant women from 2003 through 2017 in the Optum® national insurance claims database. We used diagnosis claims to identify urinary stone disease and assess medical comorbidity. We established the prevalence of urinary stone disease during pregnancy stratified by week of pregnancy. We further evaluated associations among urinary stone disease, maternal complications and pregnancy outcomes in univariable and multivariable analyses. RESULTS: Urinary stone disease affects 8 per 1,000 pregnancies and is more common in white women and women with more comorbid conditions. In fully adjusted models pregnancies complicated by urinary stone disease had higher rates of adverse fetal outcomes including prematurity and spontaneous abortions. This analysis is limited by its retrospective, administrative claims design. CONCLUSIONS: The rate of urinary stone disease during pregnancy is higher than previously reported. Urinary stone disease is associated with adverse pregnancy outcomes.

Leveraging plant hydraulics to yield predictive and dynamic plant leaf allocation in vegetation models with climate change.

Plant functional traits provide a link in process-based vegetation models between plant-level physiology and ecosystem-level responses. Recent advances in physiological understanding and computational efficiency have allowed for the incorporation of plant hydraulic processes in large-scale vegetation models. However, a more mechanistic representation of water limitation that determines ecosystem responses to plant water stress necessitates a re-evaluation of trait-based constraints for plant carbon allocation, particularly allocation to leaf area. In this review, we examine model representations of plant allocation to leaves, which is often empirically set by plant functional type-specific allometric relationships. We analyze the evolution of the representation of leaf allocation in models of different scales and complexities. We show the impacts of leaf allocation strategy on plant carbon uptake in the context of recent advancements in modeling hydraulic processes. Finally, we posit that deriving allometry from first principles using mechanistic hydraulic processes is possible and should become standard practice, rather than using prescribed allometries. The representation of allocation as an emergent property of scarce resource constraints is likely to be critical to representing how global change processes impact future ecosystem dynamics and carbon fluxes and may reduce the number of poorly constrained parameters in vegetation models.

Widespread drought-induced tree mortality at dry range edges indicates that climate stress exceeds species' compensating mechanisms.

Drought-induced tree mortality is projected to increase due to climate change, which will have manifold ecological and societal impacts including the potential to weaken or reverse the terrestrial carbon sink. Predictions of tree mortality remain limited, in large part because within-species variations in ecophysiology due to plasticity or adaptation and ecosystem adjustments could buffer mortality in dry locations. Here, we conduct a meta-analysis of 50 studies spanning >100 woody plant species globally to quantify how populations within species vary in vulnerability to drought mortality and whether functional traits or climate mediate mortality patterns. We find that mortality predominantly occurs in drier populations and this pattern is more pronounced in species with xylem that can tolerate highly negative water potentials, typically considered to be an adaptive trait for dry regions, and species that experience higher variability in water stress. Our results indicate that climate stress has exceeded physiological and ecosystem-level tolerance or compensating mechanisms by triggering extensive mortality at dry range edges and provides a foundation for future mortality projections in empirical distribution and mechanistic vegetation models.

Terrestrial gross primary production: Using NIRV to scale from site to globe.

Terrestrial photosynthesis is the largest and one of the most uncertain fluxes in the global carbon cycle. We find that near-infrared reflectance of vegetation (NIRV ), a remotely sensed measure of canopy structure, accurately predicts photosynthesis at FLUXNET validation sites at monthly to annual timescales (R2  = 0.68), without the need for difficult to acquire information about environmental factors that constrain photosynthesis at short timescales. Scaling the relationship between gross primary production (GPP) and NIRV from FLUXNET eddy covariance sites, we estimate global annual terrestrial photosynthesis to be 147 Pg C/year (95% credible interval 131-163 Pg C/year), which falls between bottom-up GPP estimates and the top-down global constraint on GPP from oxygen isotopes. NIRV -derived estimates of GPP are systematically higher than existing bottom-up estimates, especially throughout the midlatitudes. Progress in improving estimated GPP from NIRV can come from improved cloud screening in satellite data and increased resolution of vegetation characteristics, especially details about plant photosynthetic pathway.

Climate and plant trait strategies determine tree carbon allocation to leaves and mediate future forest productivity.

Forest leaf area has enormous leverage on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Despite widespread evidence that trees are capable of adjusting to changes in environment across both space and time through modifying carbon allocation to leaves, many vegetation models use fixed carbon allocation schemes independent of environment, which introduces large uncertainties into predictions of future forest responses to atmospheric CO2 fertilization and anthropogenic climate change. Here, we develop an optimization-based model, whereby tree carbon allocation to leaves is an emergent property of environment and plant hydraulic traits. Using a combination of meta-analysis, observational datasets, and model predictions, we find strong evidence that optimal hydraulic-carbon coupling explains observed patterns in leaf allocation across large environmental and CO2 concentration gradients. Furthermore, testing the sensitivity of leaf allocation strategy to a diversity in hydraulic and economic spectrum physiological traits, we show that plant hydraulic traits in particular have an enormous impact on the global change response of forest leaf area. Our results provide a rigorous theoretical underpinning for improving carbon cycle predictions through advancing model predictions of leaf area, and underscore that tree-level carbon allocation to leaves should be derived from first principles using mechanistic plant hydraulic processes in the next generation of vegetation models.

No local adaptation in leaf or stem xylem vulnerability to embolism, but consistent vulnerability segmentation in a North American oak.

Vulnerability to embolism varies between con-generic species distributed along aridity gradients, yet little is known about intraspecific variation and its drivers. Even less is known about intraspecific variation in tissues other than stems, despite results suggesting that roots, stems and leaves can differ in vulnerability. We hypothesized that intraspecific variation in vulnerability in leaves and stems is adaptive and driven by aridity. We quantified leaf and stem vulnerability of Quercus douglasii using the optical technique. To assess contributions of genetic variation and phenotypic plasticity to within-species variation, we quantified the vulnerability of individuals growing in a common garden, but originating from populations along an aridity gradient, as well as individuals from the same wild populations. Intraspecific variation in water potential at which 50% of total embolism in a tissue is observed (P50 ) was explained mostly by differences between individuals (>66% of total variance) and tissues (16%). There was little between-population variation in leaf/stem P50 in the garden, which was not related to site of origin aridity. Unexpectedly, we observed a positive relationship between wild individual stem P50 and aridity. Although there is no local adaptation and only minor phenotypic plasticity in leaf/stem vulnerability in Q. douglasii, high levels of potentially heritable variation within populations or strong environmental selection could contribute to adaptive responses under future climate change.