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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Local range boundaries vs. large-scale trade-offs: climatic and competitive constraints on tree growth.

Species often respond to human-caused climate change by shifting where they occur on the landscape. To anticipate these shifts, we need to understand the forces that determine where species currently occur. We tested whether a long-hypothesised trade-off between climate and competitive constraints explains where tree species grow on mountain slopes. Using tree rings, we reconstructed growth sensitivity to climate and competition in range centre and range margin tree populations in three climatically distinct regions. We found that climate often constrains growth at environmentally harsh elevational range boundaries, and that climatic and competitive constraints trade-off at large spatial scales. However, there was less evidence that competition consistently constrained growth at benign elevational range boundaries; thus, local-scale climate-competition trade-offs were infrequent. Our work underscores the difficulty of predicting local-scale range dynamics, but suggests that the constraints on tree performance at a large-scale (e.g. latitudinal) may be predicted from ecological theory.

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.

Testing early warning metrics for drought-induced tree physiological stress and mortality.

Climate change-driven drought stress has triggered numerous large-scale tree mortality events in recent decades. Advances in mechanistic understanding and prediction are greatly limited by an inability to detect in situ where trees are likely to die in order to take timely measurements and actions. Thus, algorithms of early warning and detection of drought-induced tree stress and mortality could have major scientific and societal benefits. Here, we leverage two consecutive droughts in the southwestern United States to develop and test a set of early warning metrics. Using Landsat satellite data, we constructed early warning metrics from the first drought event. We then tested these metrics' ability to predict spatial patterns in tree physiological stress and mortality from the second drought. To test the broader applicability of these metrics, we also examined a separate drought in the Amazon rainforest. The early warning metrics successfully explained subsequent tree mortality in the second drought in the southwestern US, as well as mortality in the independent drought in tropical forests. The metrics also strongly correlated with spatial patterns in tree hydraulic stress underlying mortality, which provides a strong link between tree physiological stress and remote sensing during the severe drought and indicates that the loss of hydraulic function during drought likely mediated subsequent mortality. Thus, early warning metrics provide a critical foundation for elucidating the physiological mechanisms underpinning tree mortality in mature forests and guiding management responses to these climate-induced disturbances.

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.

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.

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.

Within-species patterns challenge our understanding of the leaf economics spectrum.

The utility of plant functional traits for predictive ecology relies on our ability to interpret trait variation across multiple taxonomic and ecological scales. Using extensive data sets of trait variation within species, across species and across communities, we analysed whether and at what scales leaf economics spectrum (LES) traits show predicted trait-trait covariation. We found that most variation in LES traits is often, but not universally, at high taxonomic levels (between families or genera in a family). However, we found that trait covariation shows distinct taxonomic scale dependence, with some trait correlations showing opposite signs within vs. across species. LES traits responded independently to environmental gradients within species, with few shared environmental responses across traits or across scales. We conclude that, at small taxonomic scales, plasticity may obscure or reverse the broad evolutionary linkages between leaf traits, meaning that variation in LES traits cannot always be interpreted as differences in resource use strategy.

Drought stress limits the geographic ranges of two tree species via different physiological mechanisms.

Range shifts are among the most ubiquitous ecological responses to anthropogenic climate change and have large consequences for ecosystems. Unfortunately, the ecophysiological forces that constrain range boundaries are poorly understood, making it difficult to mechanistically project range shifts. To explore the physiological mechanisms by which drought stress controls dry range boundaries in trees, we quantified elevational variation in drought tolerance and in drought avoidance-related functional traits of a widespread gymnosperm (ponderosa pine - Pinus ponderosa) and angiosperm (trembling aspen - Populus tremuloides) tree species in the southwestern USA. Specifically, we quantified tree-to-tree variation in growth, water stress (predawn and midday xylem tension), drought avoidance traits (branch conductivity, leaf/needle size, tree height, leaf area-to-sapwood area ratio), and drought tolerance traits (xylem resistance to embolism, hydraulic safety margin, wood density) at the range margins and range center of each species. Although water stress increased and growth declined strongly at lower range margins of both species, ponderosa pine and aspen showed contrasting patterns of clinal trait variation. Trembling aspen increased its drought tolerance at its dry range edge by growing stronger but more carbon dense branch and leaf tissues, implying an increased cost of growth at its range boundary. By contrast, ponderosa pine showed little elevational variation in drought-related traits but avoided drought stress at low elevations by limiting transpiration through stomatal closure, such that its dry range boundary is associated with limited carbon assimilation even in average climatic conditions. Thus, the same climatic factor (drought) may drive range boundaries through different physiological mechanisms - a result that has important implications for process-based modeling approaches to tree biogeography. Further, we show that comparing intraspecific patterns of trait variation across ranges, something rarely done in a range-limit context, helps elucidate a mechanistic understanding of range constraints.