No evidence of canopy-scale leaf thermoregulation to cool leaves below air temperature across a range of forest ecosystems.

Understanding and predicting the relationship between leaf temperature (Tleaf) and air temperature (Tair) is essential for projecting responses to a warming climate, as studies suggest that many forests are near thermal thresholds for carbon uptake. Based on leaf measurements, the limited leaf homeothermy hypothesis argues that daytime Tleaf is maintained near photosynthetic temperature optima and below damaging temperature thresholds. Specifically, leaves should cool below Tair at higher temperatures (i.e., > ∼25-30°C) leading to slopes <1 in Tleaf/Tair relationships and substantial carbon uptake when leaves are cooler than air. This hypothesis implies that climate warming will be mitigated by a compensatory leaf cooling response. A key uncertainty is understanding whether such thermoregulatory behavior occurs in natural forest canopies. We present an unprecedented set of growing season canopy-level leaf temperature (Tcan) data measured with thermal imaging at multiple well-instrumented forest sites in North and Central America. Our data do not support the limited homeothermy hypothesis: canopy leaves are warmer than air during most of the day and only cool below air in mid to late afternoon, leading to Tcan/Tair slopes >1 and hysteretic behavior. We find that the majority of ecosystem photosynthesis occurs when canopy leaves are warmer than air. Using energy balance and physiological modeling, we show that key leaf traits influence leaf-air coupling and ultimately the Tcan/Tair relationship. Canopy structure also plays an important role in Tcan dynamics. Future climate warming is likely to lead to even greater Tcan, with attendant impacts on forest carbon cycling and mortality risk.

Evolutionary lineage explains trait variation among 75 coexisting grass species.

Evolutionary history plays a key role driving patterns of trait variation across plant species. For scaling and modeling purposes, grass species are typically organized into C3 vs C4 plant functional types (PFTs). Plant functional type groupings may obscure important functional differences among species. Rather, grouping grasses by evolutionary lineage may better represent grass functional diversity. We measured 11 structural and physiological traits in situ from 75 grass species within the North American tallgrass prairie. We tested whether traits differed significantly among photosynthetic pathways or lineages (tribe) in annual and perennial grass species. Critically, we found evidence that grass traits varied among lineages, including independent origins of C4 photosynthesis. Using a rigorous model selection approach, tribe was included in the top models for five of nine traits for perennial species. Tribes were separable in a multivariate and phylogenetically controlled analysis of traits, owing to coordination of important structural and ecophysiological characteristics. Our findings suggest grouping grass species by photosynthetic pathway overlooks variation in several functional traits, particularly for C4 species. These results indicate that further assessment of lineage-based differences at other sites and across other grass species distributions may improve representation of C4 species in trait comparison analyses and modeling investigations.

Absence of canopy temperature variation despite stomatal adjustment in Pinus sylvestris under multidecadal soil moisture manipulation.

Global warming and droughts push forests closer to their thermal limits, altering tree carbon uptake and growth. To prevent critical overheating, trees can adjust their thermotolerance (Tcrit ), temperature and photosynthetic optima (Topt and Aopt ), and canopy temperature (Tcan ) to stay below damaging thresholds. However, we lack an understanding of how soil droughts affect photosynthetic thermal plasticity and Tcan regulation. In this study, we measured the effect of soil moisture on the seasonal and diurnal dynamics of net photosynthesis (A), stomatal conductance (gs ), and Tcan , as well as the thermal plasticity of photosynthesis (Tcrit , Topt , and Aopt ), over the course of 1 yr using a long-term irrigation experiment in a drought-prone Pinus sylvestris forest in Switzerland. Irrigation resulted in higher needle-level A, gs , Topt , and Aopt compared with naturally drought-exposed trees. No daily or seasonal differences in Tcan were observed between treatments. Trees operated below their thermal thresholds (Tcrit ), independently of soil moisture content. Despite strong Tcan and Tair coupling, we provide evidence that drought reduces trees' temperature optimum due to a substantial reduction of gs during warm and dry periods of the year. These findings provide important insights regarding the effects of soil drought on the thermal tolerance of P. sylvestris.

Does plant ecosystem thermoregulation occur? An extratropical assessment at different spatial and temporal scales.

To what degree plant ecosystems thermoregulate their canopy temperature (Tc ) is critical to assess ecosystems' metabolisms and resilience with climate change, but remains controversial, with opinions from no to moderate thermoregulation capability. With global datasets of Tc , air temperature (Ta ), and other environmental and biotic variables from FLUXNET and satellites, we tested the 'limited homeothermy' hypothesis (indicated by Tc & Ta regression slope < 1 or Tc < Ta around midday) across global extratropics, including temporal and spatial dimensions. Across daily to weekly and monthly timescales, over 80% of sites/ecosystems have slopes ≥1 or Tc > Ta around midday, rejecting the above hypothesis. For those sites unsupporting the hypothesis, their Tc -Ta difference (ΔT) exhibits considerable seasonality that shows negative, partial correlations with leaf area index, implying a certain degree of thermoregulation capability. Spatially, site-mean ΔT exhibits larger variations than the slope indicator, suggesting ΔT is a more sensitive indicator for detecting thermoregulatory differences across biomes. Furthermore, this large spatial-wide ΔT variation (0-6°C) is primarily explained by environmental variables (38%) and secondarily by biotic factors (15%). These results demonstrate diverse thermoregulation patterns across global extratropics, with most ecosystems negating the 'limited homeothermy' hypothesis, but their thermoregulation still occurs, implying that slope < 1 or Tc < Ta are not necessary conditions for plant thermoregulation.

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.

Changes in tree drought sensitivity provided early warning signals to the California drought and forest mortality event.

Climate warming in recent decades has negatively impacted forest health in the western United States. Here, we report on potential early warning signals (EWS) for drought-related mortality derived from measurements of tree-ring growth (ring width index; RWI) and carbon isotope discrimination (∆13 C), primarily focused on ponderosa pine (Pinus ponderosa). Sampling was conducted in the southern Sierra Nevada Mountains, near the epicenter of drought severity and mortality associated with the 2012-2015 California drought and concurrent outbreak of western pine beetle (Dendroctonus brevicomis). At this site, we found that widespread mortality was presaged by five decades of increasing sensitivity (i.e., increased explained variation) of both tree growth and ∆13 C to Palmer Drought Severity Index (PDSI). We hypothesized that increasing sensitivity of tree growth and ∆13 C to hydroclimate constitute EWS that indicate an increased likelihood of widespread forest mortality caused by direct and indirect effects of drought. We then tested these EWS in additional ponderosa pine-dominated forests that experienced varying mortality rates associated with the same California drought event. In general, drier sites showed increasing sensitivity of RWI to PDSI over the last century, as well as higher mortality following the California drought event compared to wetter sites. Two sites displayed evidence that thinning or fire events that reduced stand basal area effectively reversed the trend of increasing hydroclimate sensitivity. These comparisons indicate that reducing competition for soil water and/or decreasing bark beetle host tree density via forest management-particularly in drier regions-may buffer these forests against drought stress and associated mortality risk. EWS such as these could provide land managers more time to mitigate the extent or severity of forest mortality in advance of droughts. Substantial efforts at deploying additional dendrochronological research in concert with remote sensing and forest modeling will aid in forecasting of forest responses to continued climate warming.

Imaging canopy temperature: shedding (thermal) light on ecosystem processes.

Canopy temperature Tcan is a key driver of plant function that emerges as a result of interacting biotic and abiotic processes and properties. However, understanding controls on Tcan and forecasting canopy responses to weather extremes and climate change are difficult due to sparse measurements of Tcan at appropriate spatial and temporal scales. Burgeoning observations of Tcan from thermal cameras enable evaluation of energy budget theory and better understanding of how environmental controls, leaf traits and canopy structure influence temperature patterns. The canopy scale is relevant for connecting to remote sensing and testing biosphere model predictions. We anticipate that future breakthroughs in understanding of ecosystem responses to climate change will result from multiscale observations of Tcan across a range of ecosystems.

Lineage-based functional types: characterising functional diversity to enhance the representation of ecological behaviour in Land Surface Models.

Process-based vegetation models attempt to represent the wide range of trait variation in biomes by grouping ecologically similar species into plant functional types (PFTs). This approach has been successful in representing many aspects of plant physiology and biophysics but struggles to capture biogeographic history and ecological dynamics that determine biome boundaries and plant distributions. Grass-dominated ecosystems are broadly distributed across all vegetated continents and harbour large functional diversity, yet most Land Surface Models (LSMs) summarise grasses into two generic PFTs based primarily on differences between temperate C3 grasses and (sub)tropical C4 grasses. Incorporation of species-level trait variation is an active area of research to enhance the ecological realism of PFTs, which form the basis for vegetation processes and dynamics in LSMs. Using reported measurements, we developed grass functional trait values (physiological, structural, biochemical, anatomical, phenological, and disturbance-related) of dominant lineages to improve LSM representations. Our method is fundamentally different from previous efforts, as it uses phylogenetic relatedness to create lineage-based functional types (LFTs), situated between species-level trait data and PFT-level abstractions, thus providing a realistic representation of functional diversity and opening the door to the development of new vegetation models.

Historical changes in the stomatal limitation of photosynthesis: empirical support for an optimality principle.

The ratio of leaf internal (ci ) to ambient (ca ) partial pressure of CO2 , defined here as χ, is an index of adjustments in both leaf stomatal conductance and photosynthetic rate to environmental conditions. Measurements and proxies of this ratio can be used to constrain vegetation model uncertainties for predicting terrestrial carbon uptake and water use. We test a theory based on the least-cost optimality hypothesis for modelling historical changes in χ over the 1951-2014 period, across different tree species and environmental conditions, as reconstructed from stable carbon isotopic measurements across a global network of 103 absolutely dated tree-ring chronologies. The theory predicts optimal χ as a function of air temperature, vapour pressure deficit, ca and atmospheric pressure. The theoretical model predicts 39% of the variance in χ values across sites and years, but underestimates the intersite variability in the reconstructed χ trends, resulting in only 8% of the variance in χ trends across years explained by the model. Overall, our results support theoretical predictions that variations in χ are tightly regulated by the four environmental drivers. They also suggest that explicitly accounting for the effects of plant-available soil water and other site-specific characteristics might improve the predictions.

Spatial Patterns and Trends of Summertime Low Cloudiness for the Pacific Northwest, 1996-2017.

Summertime low clouds are common in the Pacific Northwest (PNW), but spatiotemporal patterns have not been characterized. We show the first maps of low cloudiness for the western PNW and North Pacific Ocean using a 22-year satellite-derived record of monthly mean low cloudiness frequency for May through September and supplemented by airport cloud base height observations. Domain-wide cloudiness peaks in midsummer and is strongest over the Pacific. Empirical orthogonal function (EOF) analysis identified four distinct PNW spatiotemporal modes: oceanic, terrestrial highlands, coastal, and northern coastal. There is a statistically significant trend over the 22-year record toward reduced low cloudiness in the terrestrial highlands mode, with strongest declines in May and June; however, this decline is not matched in the corresponding airport records. The coastal mode is partly constrained from moving inland by topographic relief and migrates southward in late summer, retaining higher late-season low cloud frequency than the other areas.

Fire deficits have increased drought sensitivity in dry conifer forests: Fire frequency and tree-ring carbon isotope evidence from Central Oregon.

A century of fire suppression across the Western United States has led to more crowded forests and increased competition for resources. Studies of forest thinning or stand conditions after mortality events have provided indirect evidence for how competition can promote drought stress and predispose forests to severe fire and/or bark beetle outbreaks. Here, we demonstrate linkages between fire deficits and increasing drought stress through analyses of annually resolved tree-ring growth, fire scars, and carbon isotope discrimination (Δ13 C) across a dry mixed-conifer forest landscape. Fire deficits across the study area have increased the sensitivity of leaf gas exchange to drought stress over the past >100 years. Since 1910, stand basal area in these forests has more than doubled and fire-return intervals have increased from 25 to 140 years. Meanwhile, the portion of interannual variation in tree-ring Δ13 C explained by the Palmer Drought Severity Index has more than doubled in ca. 300-500-year-old Pinus ponderosa as well as in fire-intolerant, ca. 90-190-year-old Abies grandis. Drought stress has increased in stands with a basal area of ≥25 m2 /ha in 1910, as indicated by negative temporal Δ13 C trends, whereas stands with basal area ≤25 m2 /ha in 1910, due to frequent or intense wildfire activity in decades beforehand, were initially buffered from increased drought stress and have benefited more from rising ambient carbon dioxide concentrations, [CO2 ], as demonstrated by positive temporal Δ13 C trends. Furthermore, the average Δ13 C response across all P. ponderosa since 1830 indicates that photosynthetic assimilation rates and stomatal conductance have been reduced by ~10% and ~20%, respectively, compared to expected trends due to increasing [CO2 ]. Although disturbance legacies contribute to local-scale intensity of drought stress, fire deficits have reduced drought resistance of mixed-conifer forests and made them more susceptible to challenges by pests and pathogens and other disturbances.

Climate and lawn management interact to control C4 plant distribution in residential lawns across seven U.S. cities.

In natural grasslands, C4 plant dominance increases with growing season temperatures and reflects distinct differences in plant growth rates and water use efficiencies of C3 vs. C4 photosynthetic pathways. However, in lawns, management decisions influence interactions between planted turfgrass and weed species, leading to some uncertainty about the degree of human vs. climatic controls on lawn species distributions. We measured herbaceous plant carbon isotope ratios (δ13 C, index of C3 /C4 relative abundance) and C4 cover in residential lawns across seven U.S. cities to determine how climate, lawn plant management, or interactions between climate and plant management influenced C4 lawn cover. We also calculated theoretical C4 carbon gain predicted by a plant physiological model as an index of expected C4 cover due to growing season climatic conditions in each city. Contrary to theoretical predictions, plant δ13 C and C4 cover in urban lawns were more strongly related to mean annual temperature than to growing season temperature. Wintertime temperatures influenced the distribution of C4 lawn turf plants, contrary to natural ecosystems where growing season temperatures primarily drive C4 distributions. C4 cover in lawns was greatest in the three warmest cities, due to an interaction between climate and homeowner plant management (e.g., planting C4 turf species) in these cities. The proportion of C4 lawn species was similar to the proportion of C4 species in the regional grass flora. However, the majority of C4 species were nonnative turf grasses, and not of regional origin. While temperature was a strong control on lawn species composition across the United States, cities differed as to whether these patterns were driven by cultivated lawn grasses vs. weedy species. In some cities, biotic interactions with weedy plants appeared to dominate, while in other cities, C4 plants were predominantly imported and cultivated. Elevated CO2 and temperature in cities can influence C3 /C4 competitive outcomes; however, this study provides evidence that climate and plant management dynamics influence biogeography and ecology of C3 /C4 plants in lawns. Their differing water and nutrient use efficiency may have substantial impacts on carbon, water, energy, and nutrient budgets across cities.

Coastal fog during summer drought improves the water status of sapling trees more than adult trees in a California pine forest.

Fog water inputs can offset seasonal drought in the Mediterranean climate of coastal California and may be critical to the persistence of many endemic plant species. The ability to predict plant species response to potential changes in the fog regime hinges on understanding the ways that fog can impact plant physiological function across life stages. Our study uses a direct metric of water status, namely plant water potential, to understand differential responses of adult versus sapling trees to seasonal drought and fog water inputs. We place these measurements within a water balance framework that incorporates the varying climatic and soil property impacts on water budgets and deficit. We conducted our study at a coastal and an inland site within the largest stand of the regionally endemic bishop pine (Pinus muricata D. Don) on Santa Cruz Island. Our results show conclusively that summer drought negatively affects the water status of sapling more than adult trees and that sapling trees are also more responsive to changes in shallow soil moisture inputs from fog water deposition. Moreover, between the beginning and end of a large, late-season fog drip event, water status increased more for saplings than for adults. Relative to non-foggy conditions, we found that fog water reduces modeled peak water deficit by 80 and 70 % at the inland and coastal sites, respectively. Results from our study inform mechanistically based predictions of how population dynamics of this and other coastal species may be affected by a warmer, drier, and potentially less foggy future.

Mapping the global distribution of C4 vegetation using observations and optimality theory.

Plants with the C4 photosynthesis pathway typically respond to climate change differently from more common C3-type plants, due to their distinct anatomical and biochemical characteristics. These different responses are expected to drive changes in global C4 and C3 vegetation distributions. However, current C4 vegetation distribution models may not predict this response as they do not capture multiple interacting factors and often lack observational constraints. Here, we used global observations of plant photosynthetic pathways, satellite remote sensing, and photosynthetic optimality theory to produce an observation-constrained global map of C4 vegetation. We find that global C4 vegetation coverage decreased from 17.7% to 17.1% of the land surface during 2001 to 2019. This was the net result of a reduction in C4 natural grass cover due to elevated CO2 favoring C3-type photosynthesis, and an increase in C4 crop cover, mainly from corn (maize) expansion. Using an emergent constraint approach, we estimated that C4 vegetation contributed 19.5% of global photosynthetic carbon assimilation, a value within the range of previous estimates (18-23%) but higher than the ensemble mean of dynamic global vegetation models (14 ± 13%; mean ± one standard deviation). Our study sheds insight on the critical and underappreciated role of C4 plants in the contemporary global carbon cycle.

Forest responses to increasing aridity and warmth in the southwestern United States.

In recent decades, intense droughts, insect outbreaks, and wildfires have led to decreasing tree growth and increasing mortality in many temperate forests. We compared annual tree-ring width data from 1,097 populations in the coterminous United States to climate data and evaluated site-specific tree responses to climate variations throughout the 20th century. For each population, we developed a climate-driven growth equation by using climate records to predict annual ring widths. Forests within the southwestern United States appear particularly sensitive to drought and warmth. We input 21st century climate projections to the equations to predict growth responses. Our results suggest that if temperature and aridity rise as they are projected to, southwestern trees will experience substantially reduced growth during this century. As tree growth declines, mortality rates may increase at many sites. Increases in wildfires and bark-beetle outbreaks in the most recent decade are likely related to extreme drought and high temperatures during this period. Using satellite imagery and aerial survey data, we conservatively calculate that ≈ 2.7% of southwestern forest and woodland area experienced substantial mortality due to wildfires from 1984 to 2006, and ≈ 7.6% experienced mortality associated with bark beetles from 1997 to 2008. We estimate that up to ≈ 18% of southwestern forest area (excluding woodlands) experienced mortality due to bark beetles or wildfire during this period. Expected climatic changes will alter future forest productivity, disturbance regimes, and species ranges throughout the Southwest. Emerging knowledge of these impending transitions informs efforts to adaptively manage southwestern forests.

Widespread amphibian extinctions from epidemic disease driven by global warming.

As the Earth warms, many species are likely to disappear, often because of changing disease dynamics. Here we show that a recent mass extinction associated with pathogen outbreaks is tied to global warming. Seventeen years ago, in the mountains of Costa Rica, the Monteverde harlequin frog (Atelopus sp.) vanished along with the golden toad (Bufo periglenes). An estimated 67% of the 110 or so species of Atelopus, which are endemic to the American tropics, have met the same fate, and a pathogenic chytrid fungus (Batrachochytrium dendrobatidis) is implicated. Analysing the timing of losses in relation to changes in sea surface and air temperatures, we conclude with 'very high confidence' (> 99%, following the Intergovernmental Panel on Climate Change, IPCC) that large-scale warming is a key factor in the disappearances. We propose that temperatures at many highland localities are shifting towards the growth optimum of Batrachochytrium, thus encouraging outbreaks. With climate change promoting infectious disease and eroding biodiversity, the urgency of reducing greenhouse-gas concentrations is now undeniable.

The NEON Daily Isotopic Composition of Environmental Exchanges Dataset.

The National Ecological Observatory Network (NEON) provides open-access measurements of stable isotope ratios in atmospheric water vapor (δ2H, δ18O) and carbon dioxide (δ13C) at different tower heights, as well as aggregated biweekly precipitation samples (δ2H, δ18O) across the United States. These measurements were used to create the NEON Daily Isotopic Composition of Environmental Exchanges (NEON-DICEE) dataset estimating precipitation (P; δ2H, δ18O), evapotranspiration (ET; δ2H, δ18O), and net ecosystem exchange (NEE; δ13C) isotope ratios. Statistically downscaled precipitation datasets were generated to be consistent with the estimated covariance between isotope ratios and precipitation amounts at daily time scales. Isotope ratios in ET and NEE fluxes were estimated using a mixing-model approach with calibrated NEON tower measurements. NEON-DICEE is publicly available on HydroShare and can be reproduced or modified to fit user specific applications or include additional NEON data records as they become available. The NEON-DICEE dataset can facilitate understanding of terrestrial ecosystem processes through their incorporation into environmental investigations that require daily δ2H, δ18O, and δ13C flux data.

Poor relationships between NEON Airborne Observation Platform data and field-based vegetation traits at a mesic grassland.

Understanding spatial and temporal variation in plant traits is needed to accurately predict how communities and ecosystems will respond to global change. The National Ecological Observatory Network's (NEON's) Airborne Observation Platform (AOP) provides hyperspectral images and associated data products at numerous field sites at 1 m spatial resolution, potentially allowing high-resolution trait mapping. We tested the accuracy of readily available data products of NEON's AOP, such as Leaf Area Index (LAI), Total Biomass, Ecosystem Structure (Canopy height model [CHM]), and Canopy Nitrogen, by comparing them to spatially extensive field measurements from a mesic tallgrass prairie. Correlations with AOP data products exhibited generally weak or no relationships with corresponding field measurements. The strongest relationships were between AOP LAI and ground-measured LAI (r = 0.32) and AOP Total Biomass and ground-measured biomass (r = 0.23). We also examined how well the full reflectance spectra (380-2,500 nm), as opposed to derived products, could predict vegetation traits using partial least-squares regression (PLSR) models. Among all the eight traits examined, only Nitrogen had a validation R2 of more than 0.25. For all vegetation traits, validation R2 ranged from 0.08 to 0.29 and the range of the root mean square error of prediction (RMSEP) was 14-64%. Our results suggest that currently available AOP-derived data products should not be used without extensive ground-based validation. Relationships using the full reflectance spectra may be more promising, although careful consideration of field and AOP data mismatches in space and/or time, biases in field-based measurements or AOP algorithms, and model uncertainty are needed. Finally, grassland sites may be especially challenging for airborne spectroscopy because of their high species diversity within a small area, mixed functional types of plant communities, and heterogeneous mosaics of disturbance and resource availability. Remote sensing observations are one of the most promising approaches to understanding ecological patterns across space and time. But the opportunity to engage a diverse community of NEON data users will depend on establishing rigorous links with in-situ field measurements across a diversity of sites.