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Measurements of atmospheric O2 and CO2 concentrations serve as a widely used means to partition global land and ocean carbon sinks. Interpretation of these measurements has assumed that the terrestrial biosphere contributes to changing O2 levels by either expanding or contracting in size, and thus serving as either a carbon sink or source (and conversely as either an oxygen source or sink). Here, we show how changes in atmospheric O2 can also occur if carbon within the terrestrial biosphere becomes more reduced or more oxidized, even with a constant carbon pool. At a global scale, we hypothesize that increasing levels of disturbance within many biomes has favored plant functional types with lower oxidative ratios and that this has caused carbon within the terrestrial biosphere to become increasingly more oxidized over a period of decades. Accounting for this mechanism in the global atmospheric O2 budget may require a small increase in the size of the land carbon sink. In a scenario based on the Carnegie-Ames-Stanford Approach model, a cumulative decrease in the oxidative ratio of net primary production (NPP) (moles of O2 produced per mole of CO2 fixed in NPP) by 0.01 over a period of 100 years would create an O2 disequilibrium of 0.0017 and require an increased land carbon sink of 0.1 PgCyr1 to balance global atmospheric O2 and CO2 budgets. At present, however, it is challenging to directly measure the oxidative ratio of terrestrial ecosystem exchange and even more difficult to detect a disequilibrium caused by a changing oxidative ratio of NPP. Information on plant and soil chemical composition complement gas exchange approaches for measuring the oxidative ratio, particularly for understanding how this quantity may respond to various global change processes over annual to decadal timescales. © 2006 Blackwell Publishing Ltd.

In this review, we discuss current research on forest carbon risk from natural disturbance under climate change for the United States, with emphasis on advancements in analytical mapping and modeling tools that have potential to drive research for managing future long-term stability of forest carbon. As a natural mechanism for carbon storage, forests are a critical component of meeting climate mitigation strategies designed to combat anthropogenic emissions. Forests consist of long-lived organisms (trees) that can store carbon for centuries or more. However, trees have finite lifespans, and disturbances such as wildfire, insect and disease outbreaks, and drought can hasten tree mortality or reduce tree growth, thereby slowing carbon sequestration, driving carbon emissions, and reducing forest carbon storage in stable pools, particularly the live and standing dead portions that are counted in many carbon offset programs. Many forests have natural disturbance regimes, but climate change and human activities disrupt the frequency and severity of disturbances in ways that are likely to have consequences for the long-term stability of forest carbon. To minimize negative effects and maximize resilience of forest carbon, disturbance risks must be accounted for in carbon offset protocols, carbon management practices, and carbon mapping and modeling techniques. This requires detailed mapping and modeling of the quantities and distribution of forest carbon across the United States and hopefully one day globally; the frequency, severity, and timing of disturbances; the mechanisms by which disturbances affect carbon storage; and how climate change may alter each of these elements. Several tools (e.g. fire spread models, imputed forest inventory models, and forest growth simulators) exist to address one or more of the aforementioned items and can help inform management strategies that reduce forest carbon risk, maintain long-term stability of forest carbon, and further explore challenges, uncertainties, and opportunities for evaluating the continued potential of, and threats to, forests as viable mechanisms for forest carbon storage, including carbon offsets. A growing collective body of research and technological improvements have advanced the science, but we highlight and discuss key limitations, uncertainties, and gaps that remain., (© 2024. The Author(s).)

Plants with the C 4 photosynthesis pathway typically respond to climate change differently from more common C 3 -type plants, due to their distinct anatomical and biochemical characteristics. These different responses are expected to drive changes in global C 4 and C 3 vegetation distributions. However, current C 4 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 C 4 vegetation. We find that global C 4 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 C 4 natural grass cover due to elevated CO 2 favoring C 3 -type photosynthesis, and an increase in C 4 crop cover, mainly from corn (maize) expansion. Using an emergent constraint approach, we estimated that C 4 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 C 4 plants in the contemporary global carbon cycle., (© 2024. The Author(s).)

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 (T crit ), temperature and photosynthetic optima (T opt and A opt ), and canopy temperature (T can ) to stay below damaging thresholds. However, we lack an understanding of how soil droughts affect photosynthetic thermal plasticity and T can regulation. In this study, we measured the effect of soil moisture on the seasonal and diurnal dynamics of net photosynthesis (A), stomatal conductance (g s ), and T can , as well as the thermal plasticity of photosynthesis (T crit , T opt , and A opt ), 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, g s , T opt , and A opt compared with naturally drought-exposed trees. No daily or seasonal differences in T can were observed between treatments. Trees operated below their thermal thresholds (T crit ), independently of soil moisture content. Despite strong T can and T air coupling, we provide evidence that drought reduces trees' temperature optimum due to a substantial reduction of g s 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., (© 2023 The Authors New Phytologist © 2023 New Phytologist Foundation.)

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 C 3 vs C 4 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 C 4 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 C 4 species. These results indicate that further assessment of lineage-based differences at other sites and across other grass species distributions may improve representation of C 4 species in trait comparison analyses and modeling investigations., (© 2023 The Authors. New Phytologist © 2023 New Phytologist Foundation.)

To what degree plant ecosystems thermoregulate their canopy temperature (T c ) 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 T c , air temperature (T a ), and other environmental and biotic variables from FLUXNET and satellites, we tested the 'limited homeothermy' hypothesis (indicated by T c & T a regression slope < 1 or T c  < T a 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 T c  > T a around midday, rejecting the above hypothesis. For those sites unsupporting the hypothesis, their T c -T a 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 T c  < T a are not necessary conditions for plant thermoregulation., (© 2022 The Authors New Phytologist © 2022 New Phytologist Foundation.)

Understanding and predicting the relationship between leaf temperature ( T leaf ) and air temperature ( T air ) 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 T leaf is maintained near photosynthetic temperature optima and below damaging temperature thresholds. Specifically, leaves should cool below T air at higher temperatures (i.e., > ∼25-30°C) leading to slopes <1 in T leaf / T air 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 ( T can ) 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 T can / T air 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 T can / T air relationship. Canopy structure also plays an important role in T can dynamics. Future climate warming is likely to lead to even greater T can , with attendant impacts on forest carbon cycling and mortality risk.

The National Ecological Observatory Network (NEON) provides open-access measurements of stable isotope ratios in atmospheric water vapor (δ 2 H, δ 18 O) and carbon dioxide (δ 13 C) at different tower heights, as well as aggregated biweekly precipitation samples (δ 2 H, δ 18 O) across the United States. These measurements were used to create the NEON Daily Isotopic Composition of Environmental Exchanges (NEON-DICEE) dataset estimating precipitation (P; δ 2 H, δ 18 O), evapotranspiration (ET; δ 2 H, δ 18 O), and net ecosystem exchange (NEE; δ 13 C) 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 δ 2 H, δ 18 O, and δ 13 C flux data., (© 2022. The Author(s).)

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., (© 2022 John Wiley & Sons Ltd.)

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 R 2 of more than 0.25. For all vegetation traits, validation R 2 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., (© 2021 The Ecological Society of America.)

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., (© 2021 John Wiley & Sons Ltd. This article has been contributed to by US Government employees and their work is in the public domain in the USA.)

Canopy temperature T can is a key driver of plant function that emerges as a result of interacting biotic and abiotic processes and properties. However, understanding controls on T can and forecasting canopy responses to weather extremes and climate change are difficult due to sparse measurements of T can at appropriate spatial and temporal scales. Burgeoning observations of T can 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 T can across a range of ecosystems., (© 2021 The Authors New Phytologist © 2021 New Phytologist Foundation.)

Extant conifer species may be susceptible to rapid environmental change owing to their long generation times, but could also be resilient due to high levels of standing genetic diversity. Hybridisation between closely related species can increase genetic diversity and generate novel allelic combinations capable of fuelling adaptive evolution. Our study unravelled the genetic architecture of adaptive evolution in a conifer hybrid zone formed between Pinus strobiformis and P. flexilis. Using a multifaceted approach emphasising the spatial and environmental patterns of linkage disequilibrium and ancestry enrichment, we identified recently introgressed and background genetic variants to be driving adaptive evolution along different environmental gradients. Specifically, recently introgressed variants from P. flexilis were favoured along freeze-related environmental gradients, while background variants were favoured along water availability-related gradients. We posit that such mosaics of allelic variants within conifer hybrid zones will confer upon them greater resilience to ongoing and future environmental change and can be a key resource for conservation efforts.

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 C 3 grasses and (sub)tropical C 4 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., (No claim to US Government works New Phytologist © 2020 New Phytologist Trust.)

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., (©2020. The Authors.)

The ratio of leaf internal (c i ) to ambient (c a ) partial pressure of CO 2 , 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, c a 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., (© 2019 The Authors. New Phytologist © 2019 New Phytologist Trust.)

Bastin et al 's estimate (Reports, 5 July 2019, p. 76) that tree planting for climate change mitigation could sequester 205 gigatonnes of carbon is approximately five times too large. Their analysis inflated soil organic carbon gains, failed to safeguard against warming from trees at high latitudes and elevations, and considered afforestation of savannas, grasslands, and shrublands to be restoration., (Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

In natural grasslands, C 4 plant dominance increases with growing season temperatures and reflects distinct differences in plant growth rates and water use efficiencies of C 3 vs. C 4 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 (δ 13 C, index of C 3 /C 4 relative abundance) and C 4 cover in residential lawns across seven U.S. cities to determine how climate, lawn plant management, or interactions between climate and plant management influenced C 4 lawn cover. We also calculated theoretical C 4 carbon gain predicted by a plant physiological model as an index of expected C 4 cover due to growing season climatic conditions in each city. Contrary to theoretical predictions, plant δ 13 C and C 4 cover in urban lawns were more strongly related to mean annual temperature than to growing season temperature. Wintertime temperatures influenced the distribution of C 4 lawn turf plants, contrary to natural ecosystems where growing season temperatures primarily drive C 4 distributions. C 4 cover in lawns was greatest in the three warmest cities, due to an interaction between climate and homeowner plant management (e.g., planting C 4 turf species) in these cities. The proportion of C 4 lawn species was similar to the proportion of C 4 species in the regional grass flora. However, the majority of C 4 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, C 4 plants were predominantly imported and cultivated. Elevated CO 2 and temperature in cities can influence C 3 /C 4 competitive outcomes; however, this study provides evidence that climate and plant management dynamics influence biogeography and ecology of C 3 /C 4 plants in lawns. Their differing water and nutrient use efficiency may have substantial impacts on carbon, water, energy, and nutrient budgets across cities., (© 2019 by the Ecological Society of America.)

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 (Δ 13 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 Δ 13 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 m 2 /ha in 1910, as indicated by negative temporal Δ 13 C trends, whereas stands with basal area ≤25 m 2 /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, [CO 2 ], as demonstrated by positive temporal Δ 13 C trends. Furthermore, the average Δ 13 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 [CO 2 ]. 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., (Published 2018. This article is a U.S. Government work and is in the public domain in the USA.)

Tree-ring carbon isotope discrimination (Δ 13 C) and oxygen isotopes (δ 18 O) collected from white pine (Pinus strobus) trees adjacent to Lake Superior show potential to produce the first winter-specific paleoclimate reconstruction with inter-annual resolution for this region. Isotopic signatures from 1976 to 2015 were strongly linked to antecedent winter minimum temperatures (T min ), Lake Superior peak ice cover, and regional to continental-scale atmospheric winter pressure variability including the North American Dipole. The immense thermal inertia of Lake Superior underlies the unique connection between winter conditions and tree-ring Δ 13 C and δ 18 O signals from the following growing season in trees located near the lake. By combining these signals, we demonstrate feasibility to reconstruct variability in T min , ice cover, and continental-scale atmospheric circulation patterns (r ≥ 0.65, P < 0.001).

This corrects the article DOI: 10.1038/sdata.2018.16.

Statistically downscaled climate data have been widely used to explore possible impacts of climate change in various fields of study. Although many studies have focused on characterizing differences in the downscaling methods, few studies have evaluated actual downscaled datasets being distributed publicly. Spatially focusing on the Pacific Northwest, we compare five statistically downscaled climate datasets distributed publicly in the US: ClimateNA, NASA NEX-DCP30, MACAv2-METDATA, MACAv2-LIVNEH and WorldClim. We compare the downscaled projections of climate change, and the associated observational data used as training data for downscaling. We map and quantify the variability among the datasets and characterize the spatio-temporal patterns of agreement and disagreement among the datasets. Pair-wise comparisons of datasets identify the coast and high-elevation areas as areas of disagreement for temperature. For precipitation, high-elevation areas, rainshadows and the dry, eastern portion of the study area have high dissimilarity among the datasets. By spatially aggregating the variability measures into watersheds, we develop guidance for selecting datasets within the Pacific Northwest climate change impact studies.

Bastin et al (Reports, 12 May 2017, p. 635) infer forest as more globally extensive than previously estimated using tree cover data. However, their forest definition does not reflect ecosystem function or biotic composition. These structural and climatic definitions inflate forest estimates across the tropics and undermine conservation goals, leading to inappropriate management policies and practices in tropical grassy ecosystems., (Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Fog-drip to the soil is the most obvious contribution of fog to the water budget of an ecosystem, but several studies provide convincing evidence that foliar absorption of fog water through leaf wetting events is also possible. The focus of our research was to assess the relative importance of fog drip and fog immersion (foliar wetting) on leaf gas-exchange rates and photosynthetic capacity of a coastal pine species, Bishop pine (Pinus muricata D.Don), a drought-sensitive species restricted to the fog belt of coastal California and offshore islands. In a controlled experiment, we manipulated fog water inputs to potted Bishop pine saplings during a 3 week dry-down period. Ten saplings were randomly assigned one of two fog treatments: (1) fog drip to the soil and canopy fog immersion, or (2) fog immersion alone. Five saplings were assigned the 'control' group and received no fog water inputs. We found that fog immersion alone significantly increased carbon assimilation rates and photosynthetic capacity of saplings as soil moisture declined compared with those that received no fog at all. The highest carbon assimilation rates were observed in saplings that also received fog drip. Soil moisture was 40% higher in the fog immersion compared with the control group during the dry-down, indicating a reduced demand for soil water in saplings that had only leaves wetted by canopy interception of fog. Leaf-level physiology is more strongly enhanced by fog drip compared with fog immersion, although the results of this study provide evidence that foliar absorption is a viable mechanism by which Bishop pines use fog water and that it can enhance instantaneous plant carbon gain and potentially whole plant productivity.

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.

The spread of C4 grasses in the late Neogene is one of the most important ecological transitions of the Cenozoic, but the primary driver of this global expansion is widely debated. We use the stable carbon isotopic composition (δ(13)C) of bison and mammoth tissues as a proxy for the relative abundance of C3 and C4 vegetation in their grazing habitat to determine climatic and atmospheric CO2 controls on C4 grass distributions from the Last Glacial Maximum (LGM) to the present. We predict the spatial variability of grass δ(13)C in North America using a mean of three different methods of classification and regression tree (CART) machine learning techniques and nine climatic variables. We show that growing season precipitation and temperature are the strongest predictors of all single climate variables. We apply this CART analysis to high-resolution gridded climate data and Coupled Model Intercomparison Project (CMIP5) mean paleoclimate model outputs to produce predictive isotope landscape models ("isoscapes") for the current, mid-Holocene, and LGM average δ(13)C of grass-dominated areas across North America. From the LGM to the present, C4 grass abundances substantially increased in the Great Plains despite concurrent increases in atmospheric CO2. These results suggest that changes in growing season precipitation rather than atmospheric CO2 were critically important in the Neogene expansion of C4 grasses.

Budburst is a key adaptive trait that can help us understand how plants respond to a changing climate from the molecular to landscape scale. Despite this, acquisition of budburst data is constrained by a lack of information at the plant scale on the environmental stimuli associated with the release of bud dormancy. Additionally, to date, little effort has been devoted to phenotyping plants in natural populations due to the challenge of accounting for the effect of environmental variation. Nonetheless, natural selection operates on natural populations, and investigation of adaptive phenotypes in situ is warranted and can validate results from controlled laboratory experiments. To identify genomic effects on individual plant phenotypes in nature, environmental drivers must be concurrently measured, and characterized. Here, we designed and evaluated a sensor to meet these requirements for temperate woody plants. It was designed for use on a tree branch to measure the timing of budburst together with its key environmental drivers; temperature, and photoperiod. Specifically, we evaluated the sensor through independent corroboration with time-lapse photography and a suite of environmental sampling instruments. We also tested whether the presence of the device on a branch influenced the timing of budburst. Our results indicated the following: the temperatures measured by the budburst sensor's digital thermometer closely approximated the temperatures measured using a thermocouple touching plant tissue; the photoperiod detector measured ambient light with the same accuracy as did time lapse photography; the budburst sensor accurately detected the timing of budburst; and the sensor itself did not influence the budburst timing of Populus clones. Among other potential applications, future use of the sensor may provide plant phenotyping at the landscape level for integration with landscape genomics.

Grasslands account for a large proportion of global terrestrial productivity and play a critical role in carbon and water cycling. Within grasslands, photosynthetic pathway is an important functional trait yielding different rates of productivity along environmental gradients. Recently, C3-C4 sorting along spatial environmental gradients has been reassessed by controlling for confounding traits in phylogenetically structured comparisons. C3 and C4 grasses should sort along temporal environmental gradients as well, resulting in differing phenologies and growing season lengths. Here we use 10 years of satellite data (NDVI) to examine the phenology and greenness (as a proxy for productivity) of C3 and C4 grass habitats, which reflect differences in both environment and plant physiology. We perform phylogenetically structured comparisons based on 3,595 digitized herbarium collections of 152 grass species across the Hawaiian Islands. Our results show that the clade identity of grasses captures differences in their habitats better than photosynthetic pathway. Growing season length (GSL) and associated productivity (GSP) were not significantly different when considering photosynthetic type alone, but were indeed different when considering photosynthetic type nested within clade. The relationship between GSL and GSP differed most strongly between C3 clade habitats, and not between C3-C4 habitats. Our results suggest that accounting for the interaction between phylogeny and photosynthetic pathway can help improve predictions of productivity, as commonly used C3-C4 classifications are very broad and appear to mask important diversity in grassland ecosystem functions.

Assessing the ecological importance of clouds has substantial implications for our basic understanding of ecosystems and for predicting how they will respond to a changing climate. This study was conducted in a coastal Bishop pine forest ecosystem that experiences regular cycles of stratus cloud cover and inundation in summer. Our objective was to understand how these clouds impact ecosystem metabolism by contrasting two sites along a gradient of summer stratus cover. The site that was under cloud cover ~15% more of the summer daytime hours had lower air temperatures and evaporation rates, higher soil moisture content, and received more frequent fog drip inputs than the site with less cloud cover. These cloud-driven differences in environmental conditions translated into large differences in plant and microbial activity. Pine trees at the site with greater cloud cover exhibited less water stress in summer, larger basal area growth, and greater rates of sap velocity. The difference in basal area growth between the two sites was largely due to summer growth. Microbial metabolism was highly responsive to fog drip, illustrated by an observed ~3-fold increase in microbial biomass C with increasing summer fog drip. In addition, the site with more cloud cover had greater total soil respiration and a larger fractional contribution from heterotrophic sources. We conclude that clouds are important to the ecological functioning of these coastal forests, providing summer shading and cooling that relieve pine and microbial drought stress as well as regular moisture inputs that elevate plant and microbial metabolism. These findings are important for understanding how these and other seasonally dry coastal ecosystems will respond to predicted changes in stratus cover, rainfall, and temperature., (© 2012 Blackwell Publishing Ltd.)

A number of studies have demonstrated the ecological sorting of C3 and C4 grasses along temperature and moisture gradients. However, previous studies of C3 and C4 grass biogeography have often inadvertently compared species in different and relatively unrelated lineages, which are associated with different environmental settings and distinct adaptive traits. Such confounded comparisons of C3 and C4 grasses may bias our understanding of ecological sorting imposed strictly by photosynthetic pathway. Here, we used MaxEnt species distribution modeling in combination with satellite data to understand the functional diversity of C3 and C4 grasses by comparing both large clades and closely related sister taxa. Similar to previous work, we found that C4 grasses showed a preference for regions with higher temperatures and lower precipitation compared with grasses using the C3 pathway. However, air temperature differences were smaller (2 °C vs. 4 °C) and precipitation and % tree cover differences were larger (1783 mm vs. 755 mm, 21.3% vs. 7.7%, respectively) when comparing C3 and C4 grasses within the same clade vs. comparing all C4 and all C3 grasses (i.e., ignoring phylogenetic structure). These results were due to important differences in the environmental preferences of C3 BEP and PACMAD clades (the two main grass clades). Winter precipitation was found to be more important for understanding the distribution and environmental niche of C3 PACMADs in comparison with both C3 BEPs and C4 taxa, for which temperature was much more important. Results comparing closely related C3 -C4 sister taxa supported the patterns derived from our modeling of the larger clade groupings. Our findings, which are novel in comparing the distribution and niches of clades, demonstrate that the evolutionary history of taxa is important for understanding the functional diversity of C3 and C4 grasses, and should have implications for how grasslands will respond to global change., (© 2012 Blackwell Publishing Ltd.)

Background: Barn Swallows (Hirundo rustica) breed almost exclusively in the Northern Hemisphere. However, since the early 1980's, a small disjunct breeding population has become established in eastern Argentina, presumably by birds previously derived from those breeding in North America. Currently, it is unknown where these individuals go following breeding and how they have adjusted to a reversal in phenology. Their austral wintering period corresponds to the breeding period of the northern ancestral population and so they can potentially return to these more traditional breeding sites or they may occupy other South American wintering regions left vacant by conspecifics returning to the Northern Hemisphere., Principal Findings: We used a three-isotope (δ(13)C, δ(15)N, δ(2)H) approach to investigate potential wintering areas in Central and South America of individuals breeding in Argentina. Feather isotope values differed from those expected and measured at local breeding sites in Argentina indicating molt after the austral breeding period and away from the breeding grounds. Potential molting origins were identified applying likelihood-based assignment methods to a δ(2)H isoscape for South America and dichotomous prior information on the distribution of C3 and C4 vegetation types based on modeled vegetation-δ(13)C values. Barn Swallows now breeding in Argentina have changed their migratory behavior but presumably use the same cues as those used by the ancestral population, molting their feathers during the austral winter, likely in north-eastern South America.

Moisture inputs drive soil respiration (SR) dynamics in semi-arid and arid ecosystems. However, determining the contributions of root and microbial respiration to SR, and their separate temporal responses to periodic drought and water pulses, remains poorly understood. This study was conducted in a pine forest ecosystem with a Mediterranean-type climate that receives seasonally varying precipitation inputs from both rainfall (in the winter) and fog-drip (primarily in the summer). We used automated SR measurements, radiocarbon SR source partitioning, and a water addition experiment to understand how SR, and its separate root and microbial sources, respond to seasonal and episodic changes in moisture. Seasonal changes in SR were driven by surface soil water content and large changes in root respiration contributions. Superimposed on these seasonal patterns were episodic pulses of precipitation that determined the short-term SR patterns. Warm season precipitation pulses derived from fog-drip, and rainfall following extended dry periods, stimulated the largest SR responses. Microbial respiration dominated these SR responses, increasing within hours, whereas root respiration responded more slowly over days. We conclude that root and microbial respiration sources respond differently in timing and magnitude to both seasonal and episodic moisture inputs. These findings have important implications for the mechanistic representation of SR in models and the response of dry ecosystems to changes in precipitation patterns.

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.

The evolution of grasses using C4 photosynthesis and their sudden rise to ecological dominance 3 to 8 million years ago is among the most dramatic examples of biome assembly in the geological record. A growing body of work suggests that the patterns and drivers of C4 grassland expansion were considerably more complex than originally assumed. Previous research has benefited substantially from dialog between geologists and ecologists, but current research must now integrate fully with phylogenetics. A synthesis of grass evolutionary biology with grassland ecosystem science will further our knowledge of the evolution of traits that promote dominance in grassland systems and will provide a new context in which to evaluate the relative importance of C4 photosynthesis in transforming ecosystems across large regions of Earth.

The coast of California is home to numerous rare, endemic conifers and other plants that are limited in distribution by drought sensitivity and the summer-dry climate that prevails across most of the state. Ecologists have long assumed that some coastal plant populations survived the early Pleistocene transition to a warmer and drier environment because they benefit from frequent fog and stratus clouds that provide water and shade during the rainless summer. One such population is that of Torrey pine (Pinus torreyana ssp. Insularis) on Santa Rosa Island in Channel Islands National Park. Here we report that the tree-ring width record from this population indicates strong growth sensitivities to summer fog drip and cloud shading. We quantified the effects of summer cloud cover by comparing ring-width indices to coastal airport cloud-frequency records (1944-2004). For the first time observed, summertime cloud frequency correlated positively with ring-width indices, regardless of whether the effect of rainfall was first removed from the ring-width record. The effect of ground-level fog was strongest in July early mornings (03:00 PST, R(2) = 0.262, P < 0.0002). The effect of clouds high enough to provide shade but not fog water was also strongest in July, but climbed steadily throughout the day before becoming strongest in late afternoon (16:00-18:00 PST, R(2) = 0.148, P < 0.004). Correlations were substantially stronger in years with higher soil moisture, suggesting that growth response to summer clouds is strongly affected by pre-summer rainfall. A change in the height and/or timing of coastal cloud formation with climate change would likely affect this and other populations of California's coastal vegetation.

'C4 photosynthesis' refers to a suite of traits that increase photosynthesis in high light and high temperature environments. Most C4 plants are grasses, which dominate tropical and subtropical grasslands and savannas but are conspicuously absent from cold growing season climates. Physiological attributes of C4 photosynthesis have been invoked to explain C4 grass biogeography; however, the pathway evolved exclusively in grass lineages of tropical origin, suggesting that the prevalence of C4 grasses in warm climates could be due to other traits inherited from their non-C4 ancestors. Here we investigate the relative influences of phylogeny and photosynthetic pathway in determining the ecological distributions of C4 grasses in Hawaii. We find that the restriction of C4 grasses to warmer areas is due largely to their evolutionary history as members of a warm-climate grass clade, but that the pathway does appear to confer a competitive advantage to grasses in more arid environments.

Phylogenetic thinking has infiltrated many areas of biological research, but has had little impact on studies of global ecology or climate change. Here, we illustrate how phylogenetic information can be relevant to understanding vegetation-atmosphere dynamics at ecosystem or global scales by re-analyzing a data set of carbonic anhydrase (CA) activity in leaves that was used to estimate terrestrial gross primary productivity. The original calculations relied on what appeared to be low CA activity exclusively in C4 grasses, but our analyses indicate that such activity might instead characterize the PACCAD grass lineage, which includes many widespread C3 species. We outline how phylogenetics can guide better taxon sampling of key physiological traits, and discuss how the emerging field of phyloinformatics presents a promising new framework for scaling from organism physiology to global processes.

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 photosynthetic pathway composition (C(3):C(4) mixture) of an ecosystem is an important controller of carbon exchanges and surface energy flux partitioning, and therefore represents a fundamental ecophysiological distinction. To assess photosynthetic mixtures at a tallgrass prairie pasture in Oklahoma, we collected nighttime above-canopy air samples along concentration and isotopic gradients throughout the 1999 and 2000 growing seasons. We analyzed these samples for their CO(2) concentration and carbon isotopic composition and calculated C(3):C(4) proportions with a two-source mixing model. In 1999, the C(4) percentage increased from 38% in spring (late April) to 86% in early fall (mid-September). The C(4) percentages inferred from ecosystem respiration measurements in 2000 indicate a smaller shift, from 67% in spring (early May) to 77% in mid-summer (late July). We also sampled daytime CO(2 )concentration and carbon isotope gradients above the canopy to determine ecosystem discrimination against (13)CO(2) during net uptake. These discrimination values were always lower than corresponding nighttime ecosystem respiration isotopic signatures would suggest. After accounting for the isotopic disequilibria between respiration and photosynthesis resulting from seasonal variations in the C(3):C(4) mixture, we estimated canopy photosynthetic discrimination. The C(4) percentage calculated from this approach agrees with the percentage determined from nighttime respiration for sampling periods in both growing seasons. Isotopic imbalances between photosynthesis and respiration are likely to be common in mixed C(3):C(4 )ecosystems and must be considered when using daytime isotopic measurements to constrain ecosystem physiology. Given the global extent of such ecosystems, isotopic imbalances likely contribute to global variations in the carbon isotopic composition of atmospheric CO(2).