Concurrent Climate Research Articles

Changing risks of simultaneous global breadbasket failure

The risk of extreme climatic conditions leading to unusually low global agricultural production is exacerbated if more than one global ‘breadbasket’ is exposed at the same time. Such shocks can pose a risk to the global food system, amplifying threats to food security, and could potentially trigger other systemic risks1,2. While the possibility of climatic extremes hitting more than one breadbasket has been postulated3,4, little is known about the actual risk. Here we combine region-specific data on agricultural production with spatial statistics of climatic extremes to quantify the changing risk of low production for the major food-producing regions (breadbaskets) over time. We show an increasing risk of simultaneous failure of wheat, maize and soybean crops across the breadbaskets analysed. For rice, risks of simultaneous adverse climate conditions have decreased in the recent past, mostly owing to solar radiation changes favouring rice growth. Depending on the correlation structure between the breadbaskets, spatial dependence between climatic extremes globally can mitigate or aggravate the risks for the global food production. Our analysis can provide the basis for more efficient allocation of resources to contingency plans and/or strategic crop reserves that would enhance the resilience of the global food system. The risk of concurrent climate extremes affecting breadbasket regions is increasing with climate change, with wheat, maize and soybean crops at risk of simultaneous failure. Correlation between the regions and climate extremes should be considered to ensure food security in the future.

What happens to the ocean surface gravity waves when ENSO and MJO phases combine during the extended boreal winter?

The safety of vulnerable coastal and offshore infrastructures requires an in-depth understanding of wave variability and climate drivers. We investigate the association of significant wave height (Hs) and peak wave period (Tp) with the co-occurrence of El Nino–Southern Oscillation (ENSO) and the Madden–Julian Oscillation (MJO) at the global scale. We calculate composites of daily anomalies in modelled Hs, Tp, and surface wind for periods of ENSO–MJO phase combinations. Calculations spanned November–March seasons over the period 1979–2018. Wave anomalies are widespread across the world’s oceans, with remarkable strength during several ENSO–MJO phase combinations, demonstrating strong tropic–tropic and tropic-extratropic teleconnections. Positive Hs anomalies are strongest in the Pacific Ocean during El Nino–MJO phase 8, in the Atlantic Ocean during ENSO-neutral-MJO phase 3, and in the Indian Ocean during ENSO-neutral-MJO phase 4. Positive Tp anomalies are strongest in the Pacific Ocean during La Nina–MJO phase 8, in the Atlantic Ocean during El Nino–MJO phase 1, and in the Indian Ocean during El Nino–MJO phase 8. In the Southern Ocean, the strongest Hs anomalies occur during El Nino–MJO phase 8, whereas in the Maritime Continent, they appear during ENSO-neutral-MJO phases 5–6. Despite previous studies finding low correlations of ENSO indices with wave parameters in the North Atlantic, our results suggest that ENSO-related conditions play a significant role in the area when combined with certain MJO-related conditions. This study also reveals that the wave anomalies associated with ENSO–MJO phase combinations can be twice as strong as those found in previous work, related only to the MJO. Therefore, considering multiple concurrent climate patterns in the analysis of wave anomalies is essential to developing more reliable coastal management plans.

Climate change and land use induce functional shifts in soil nematode communities.

Land-use intensification represents one major threat to the diversity and functioning of terrestrial ecosystems. In the face of concurrent climate change, concerns are growing about the ability of intensively managed agroecosystems to ensure stable food provisioning, as they may be particularly vulnerable to climate extreme-induced harvest losses and pest outbreaks. Extensively managed systems, in contrast, were shown to mitigate climate change based on plant diversity-mediated effects, such as higher functional redundancy or asynchrony of species. In this context, the maintenance of soils is essential to sustain key ecosystem functions such as nutrient cycling, pest control, and crop yield. Within the highly diverse soil fauna, nematodes represent an important group as their trophic spectrum ranges from detritivores to predators and they allow inferences to the overall state of the ecosystem (bioindicators). Here, we investigated the effects of simulated climate change and land-use intensity on the diversity and abundance of soil nematode functional groups and functional indices in two consecutive years. We revealed that especially landuseinduced complex shifts in the nematode community with strong seasonal dynamics, while future climate led to weaker effects. Strikingly, the high nematode densities associated with altered climatic conditions and intensive land use were a consequence of increased densities of opportunists and potential pest species (i.e., plant feeders). This coincided with a less diverse and less structured community with presumably reduced capabilities to withstand environmental stress. These degraded soil food web conditions represent a potential threat to ecosystem functioning and underline the importance of management practices that preserve belowground organisms.

Detecting the State of the Climate System via Artificial Intelligence to Improve Seasonal Forecasts and Inform Reservoir Operations

AbstractIncreasingly variable hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide. These trends emphasize the need of accurate medium‐ to long‐term predictions to timely prompt anticipatory operations. Despite in some locations global climate oscillations and particularly the El Niño Southern Oscillation (ENSO) may contribute to extending forecast lead times, in other regions there is no consensus on how ENSO can be detected, and used as local conditions are also influenced by other concurrent climate signals. In this work, we introduce the Climate State Intelligence framework to capture the state of multiple global climate signals via artificial intelligence and improve seasonal forecasts. These forecasts are used as additional inputs for informing water system operations and their value is quantified as the corresponding gain in system performance. We apply the framework to the Lake Como basin, a regulated lake in northern Italy mainly operated for flood control and irrigation supply. Numerical results show the existence of notable teleconnection patterns dependent on both ENSO and the North Atlantic Oscillation over the Alpine region, which contribute in generating skilful seasonal precipitation and hydrologic forecasts. The use of this information for conditioning the lake operations produces an average 44% improvement in system performance with respect to a baseline solution not informed by any forecast, with this gain that further increases during extreme drought episodes. Our results also suggest that observed preseason sea surface temperature anomalies appear more valuable than hydrologic‐based seasonal forecasts, producing an average 59% improvement in system performance.

Concurrent climate extremes in the key wheat producing regions of the world

Climate extremes have profound impacts on key socio-economic sectors such as agriculture. In a changing climate context, characterised by an intensification of these extremes and where the population is expected to grow, exposure and vulnerability must be accurately assessed. However, most risk assessments analyse extremes independently, thus potentially being overconfident in the resilience of the socio-economic sectors. Here, we propose a novel approach to defining and characterising concurrent climate extremes (i.e. extremes occurring within a specific temporal lag), which is able to identify spatio-temporal dependences without making any strict assumptions. The method is applied to large-scale heat stress and drought events in the key wheat producing regions of the world, as these extremes can cause serious yield losses and thus trigger market shocks. Wheat regions likely to have concurrent extremes (heat stress and drought events) are identified, as well as regions independent of each other or inhibiting each other in terms of these extreme events. This tool may be integrated in all risk assessments but could also be used to explore global climate teleconnections.

Application of hydroclimatic drought indicators in the transboundary Prut River basin

The transboundary Prut River basin (PRB) is one of the most drought vulnerable areas in the Republic of Moldova, Romania, and Ukraine. The main objective of this study was to identify the response of hydrological drought to climatic conditions and cropping practice in a region with insufficient water resources. The presented work takes advantage of the development of statistical tools to analyze existing data, as well as the collection of qualitative and quantitative hydroclimatic datasets for each sub-basin region. The study also provides survey results of the impacts of climate change on agricultural water management, including agricultural water requirements and water availability, and the transition of these impacts to cropping practice. The multi-dimensional attributes of hydrological drought are defined according to the standardized streamflow index (SSI) and water-level standardized anomaly index (SWI). The standardized precipitation evapotranspiration index (SPEI) was selected for the assessment of the impact of climate drought control on hydrological drought. The streamflow/water river level is determined more by the climatic water balance deficit of the previous 6 months than over longer periods. The lag times between climatic and hydrological drought are short, which can cause a hydrological drought to occur in the same season as the climatic drought that caused it. Summer streamflow droughts are most closely linked to SPEI in the same month. Summer streamflow drought in upstream areas can impact streamflow at the outlet within the same month. Winter streamflow droughts are related to longer SPEI accumulation periods resulting from snow cover. The synthesis of findings from the river basin shown that concurrent compound climate events have much more severe impact on crop failures compared to their individual occurrence. Adjustments to sowing time (15%), the introduction of more drought resistant cultivars (11%), the use of crop protection measures (9%), and shifting to new crops (8%) seem to be minor and moderate adaptation practices employed by farmers.

The sensitivity of fire activity to interannual climate variability in Victoria, Australia

Climate change is expected to have an impact on fire activity in many regions around the globe.The extent of this can only be determined by first establishing the relationship between climate and fire activity. This study relates observed changes in fire activity in Victoria to observed changes in antecedent and concurrent climate parameters – maximum temperature, rainfall and vapour pressure, using data for 1972–2014. A first-difference approach was adopted to estimate the amount by which the observed changes in the climate parameters would have altered the fire activity in the absence of other confounding effects. This study provides a method for examining the sensitivity of fire activity to changes in climate parameters without the need to consider the complex response of fuel dynamics to future climates and changes in fire regime or fire management. We used stepwise multiple-regression to determine the months whose climate parameters explained much of the variance in the total number of fires (TNF) and area burned in a fire season. The best performing fire–climate models explained almost two-thirds of the variation in year-to-year variability of fire activity. The significant explanatory ability of the fire–climate models established in this study reveals the combination of climate parameters that closely relates to the observed year-to-year changes in fire activity, and this may provide an additional valuable resource for fire management planning. Further, we explored the role changes in climate have had on the trend in fire activity. Natural logarithm of area burned and mean fire size have not significantly increased over the study period, but the TNF has significantly increased. We find that the observed increase in maximum temperatures and decrease in rainfall account for 26% of the observed increase in TNF for the 1972–2014 period. Therefore, most of the upward trend found in fire numbers must be due to factors other than climate (i.e. changes in fire occurrence, reporting/recording, land and fire-management changes). Additionally, this study concludes that total area burned should have also increased significantly due to the observed changes in climate and that improved fire-management practicesmay be offsetting this expected increase in the area burned. Finally, using the relationship established in this study between fire numbers and climate parameters, we estimate that a 2°C increase in mean monthly maximum temperatures could be expected to lead to a 38% increase in fire numbers.

Climate impacts and Arctic precursors of changing storm track activity in the Atlantic-Eurasian region

Midlatitude storm tracks are preferred regions of intense activity of synoptic eddies shaping the day-to-day weather and several aspects of surface climate. Here statistical analyses of observationally-based atmospheric data and observed Arctic sea ice concentration (SIC) in the period 1979–2017 are used to identify linkages of a dominant mode of interannual variability in wintertime upper-tropospheric storm track activity over Eurasia (STAEA mode) to the concurrent surface climate anomalies and pre-winter Arctic SIC variations. This mode explains an exceptionally large fraction (about 70% of the variance) of the North Atlantic Oscillation (NAO) and of a dominant mode of Eurasian surface air temperature variations. As more than 50% of the variance of the STAEA mode and NAO is found to be accounted for by October SIC anomalies in the Barents/Kara Sea, it is concluded that wintertime Eurasian climate variability is to some extent predictable and that this predictability might have increased after an acceleration of the sea ice cover decline in the mid 2000s. These conclusions are supported by results from leave-1-yr-out cross-validated forecast experiments.

Structural Performance and Network Dependability of Bridge Materials in the US

ABSTRACT This paper presents a comprehensive study of the US National Bridge Inventory analyzing the operational structural performance aspects of bridge materials in separate states. The study analyzes concrete, steel, and prestressed/post-tensioned concrete (PC) that constitute 96.1% of bridges. The analysis determines the material structural performance aspects that need relative improvement. Proportional performance need-based resource allocation for maintenance and intervention enables to prioritize the comparative improvement of network dependability. Maps of structural performance aspects indicate that materials correlate differently with climate. Condition performances correlate with cold-moist climate, while life cycle performances correlate with hot, Pacific marine, and cold-dry climate. Cross-correlations around the eastern North reveal potential structural complications for steel and PC bridges due to concurrent prevalence, older age, higher usage, and cold-moist climate affecting their structural performance aspects.

Investigating the Relationship Between Climate and Valley Fever (Coccidioidomycosis)

Valley fever (coccidioidomycosis) is a disease caused by inhalation of spores from the soil-dwelling Coccidioides fungal species. The disease is endemic to semiarid areas in the western USA and parts of Central and South America. The region of interest for this study, Kern County, California, accounts for approximately 14% of the reported valley fever cases in the USA each year. It is hypothesized that the weather conditions that foster the growth and dispersal of the fungus influence the number of cases in the endemic area. This study uses regression-based analysis to model and assess the seasonal relationships between valley fever incidence and climatic variables including concurrent and lagged precipitation, temperature, Palmer Drought Severity Index, wind speed, and PM10 using data from 2000 to 2015. We find statistically significant links between disease incidence and climate conditions in Kern County, California. The best performing seasonal model explains up to 76% of the variability in fall valley fever incidence based on concurrent and antecedent climate conditions. Findings are consistent with previous studies, suggesting that antecedent precipitation is an important predictor of disease. The significant relationships found support the "grow and blow" hypothesis for climate-related coccidioidomycosis incidence risk that was originally developed for Arizona.

Response of Tropical Terrestrial Gross Primary Production to the Super El Niño Event in 2015

AbstractThe gross primary production (GPP) in tropical terrestrial ecosystems plays a critical role in the global carbon cycle and climate change. The strong 2015–2016 El Niño event offers a unique opportunity to investigate how GPP in the tropical terrestrial ecosystems responds to climatic forcing. This study uses two GPP products and concurrent climate data to investigate the GPP anomalies and their underlying causes. We find that both GPP products show an enhanced GPP in 2015 for the tropical terrestrial ecosystem as a whole relative to the multiyear mean of 2001–2015, and this enhancement is the net result of GPP increase in tropical forests and decrease in nonforests. We show that the increased GPP in tropical forests during the El Nino event is consistent with increased photosynthesis active radiation as a result of a reduction in clouds, while the decreased GPP in nonforests is consistent with increased water stress as a result of a reduction of precipitation and an increase of temperature. These results reveal the strong coupling of ecosystem and climate that is different in forest and nonforest ecosystems and provide a test case for carbon cycle parameterization and carbon‐climate feedback simulation in models.

Likelihood of concurrent climate extremes and variations over China

Extreme climate events such as droughts and heat waves exert strong impacts on ecosystems and human well-being. Estimations of the risks of climate extremes typically focus on one variable in isolation. In this study, we present a method to examine the likelihood of concurrent extreme temperature and precipitation modes at the interannual scale, including compound cool/dry and cool/wet events during the cold season as well as compound hot/dry and hot/wet events during the warm season. A comparison of changes in the likelihood of such joint climate extremes was then conducted between the first (1961–1987) and second (1988–2014) halves of the full observed records. Our findings indicate a decrease in the occurrence probability for most concurrent modes over much of China, despite positive shifts found over southwestern and northeastern parts of China for the compound hot/dry events in the warm season. We further examined changes in likelihood related to these four compound climate extremes between the historical observed period (1961–2014) and the future period (2021–2080) based on climate model simulations with the RCP8.5 scenario. Our results show widespread increases in the occurrence probability for wintertime cool/dry and summertime hot/dry and hot/wet events over most parts of China but with different magnitudes, while much of China may experience declining likelihood of the wintertime cool/wet extremes in the future.

Enhancement of the relationship between boreal summer precipitation over eastern China and Australia since the early 1980s

The relationship between the boreal summer (June–August, JJA) precipitation over eastern China and Australia is investigated in this study. The relationship exhibits a decadal enhancement with correlation coefficients increasing from 0.07 before the early 1980s to 0.60 thereafter. A mechanistic analysis suggests that the variability in sea surface temperature (SST) over the central tropical Pacific could play an important role in enhancing the precipitation relationship between the two regions. Over the past half century, the central Pacific SST has shown a warming trend with a significant decadal change that occurred around the early 1980s. Such changes in the central Pacific SST have resulted in stronger convective activity over the tropics, as well as eastern China and Australia since the early 1980s. In addition, since the early 1980s, the central Pacific SST stimulated anomalous twin anticyclones located on opposite sides of the equator, which changed the transportation of water vapour to eastern China and Australia. These changes in the atmospheric circulation related to central tropical Pacific SST have enhanced the impact on the precipitation variability over eastern China and Australia. Consequently, this has contributed to the covariability in the boreal summer precipitation over the two regions since the early 1980s. The result indicates that concurrent climate anomalies can provide simultaneously occurring natural disasters over Asia and Australia, which creates a challenge for international disaster prevention and mitigation.

Long-term dataset on aquatic responses to concurrent climate change and recovery from acidification

Concurrent regional and global environmental changes are affecting freshwater ecosystems. Decadal-scale data on lake ecosystems that can describe processes affected by these changes are important as multiple stressors often interact to alter the trajectory of key ecological phenomena in complex ways. Due to the practical challenges associated with long-term data collections, the majority of existing long-term data sets focus on only a small number of lakes or few response variables. Here we present physical, chemical, and biological data from 28 lakes in the Adirondack Mountains of northern New York State. These data span the period from 1994–2012 and harmonize multiple open and as-yet unpublished data sources. The dataset creation is reproducible and transparent; R code and all original files used to create the dataset are provided in an appendix. This dataset will be useful for examining ecological change in lakes undergoing multiple stressors.

Increasing concurrent drought and heat during the summer maize season in Huang–Huai–Hai Plain, China

Although an individual climate event may not be severe, the concurrence of climate events could have a significant impact on crop production. Investigating concurrent climate extremes during crop growth is important to formulate corresponding strategies for crop production. To assess the occurrence risk of concurrent drought and heat events in the Huang–Huai–Hai Plain (HHHP), China during the summer maize season, we analysed the temporal and spatial patterns of precipitation, standardized precipitation evapotranspiration index (SPEI), drought frequency, and extreme degree days (EDD) during the critical growth period. We used daily data from 41 meteorological stations in the region from 1980 to 2015. We determined that concurrent drought and heat events increased from northeast to southwest. The combined events mainly occurred during the vegetative period, and they significantly increased in 2006–2015 relative to 1981–1990. The spatial distribution of precipitation increased from northwest to southeast, while drought displayed no significant trends. The EDD displayed a rising trend and was intensified after 2000 in different growth periods. Its spatial distribution increased from east to west during the vegetative period and from northeast to southwest during the reproductive period. Although we focused on the combined extreme events for maize in HHHP, similar phenomenon should receive more attention in globally important crop areas and other ecosystems.

Trends in wheat yields under representative climate futures: Implications for climate adaptation

Underestimating the impacts of climate change on agricultural production could lead to complacency about the potential adaptation challenges. This study used a Representative Climate Futures (RCF) approach to model projected wheat yields under climate change in Australia. It simulated the range of impacts, resulting from a subset of individual Global Climate Models (GCMs), on wheat production in the major wheat regions of Australia. The study used RCFs that represented ‘most-likely’, ‘best’ and ‘worst’ cases across multiple Representative Concentration pathways (RCPs). Median wheat yields modelled for the South West Australia projected declines between 26% and 38%, under a ‘most-likely’ case for RCP 4.5 by 2090, and between 41% and 49%, under a ‘most-likely’ case for RCP 8.5. Median wheat yields declined under RCP 8.5 for the ‘most-likely’ case across the majority of wheat producing regions, with a range of 1% to 49%. Greater declines were projected under the ‘worst’ cases of hottest and driest climates. However, the ‘best’ cases of least warm and wetter climates projected an increase in median wheat yield, a range of 2% to 87%. Variability also changed from the baseline under all projected RCFs and across all regions, with a standard deviation of up to 2.46t/ha under the ‘most likely’ case at a site in south-eastern Australia. These likely shifts in the size and reliability of yields, combined with concurrent climate change impacts on other factors, mean that agriculture faces significant adaptation challenges, particularly under some of the ‘most-likely’ scenarios and all of the ‘worst’ case scenarios. Further work is required to explore how scenarios in one region relate to those in other regions and thus the overall outcome at the continental scale.

Carbon nanotube wools made directly from CO2 by molten electrolysis: Value driven pathways to carbon dioxide greenhouse gas mitigation

A climate mitigation comprehensive solution is presented through the first high yield, low energy synthesis of macroscopic length carbon nanotube (“CNT”) wool from CO2 by molten carbonate electrolysis. The CNT wool is of length suitable for weaving into carbon composites and textiles. Growing CO2 concentrations, and the concurrent climate change and species extinction, can be addressed if CO2 becomes a sought resource rather than a greenhouse pollutant. Inexpensive carbon composites formed from carbon wool as a lighter metal, textiles or cement replacement comprise major market sinks to compactly store transformed anthropogenic CO2. 100×-longer CNTs grow on Monel versus steel. Monel, electrolyte equilibration, and a mixed metal nucleation facilitate the synthesis. CO2, the sole reactant in this transformation, is directly extractable from dilute (atmospheric) or concentrated sources, and the analyzed production cost of $660 per ton CNT is cost constrained only by the (low) cost of electricity. Today's market valuation of >$100,000 per ton CNT incentivizes CO2 removal.

Low migratory connectivity is common in long-distance migrant birds.

Estimating how much long-distance migrant populations spread out and mix during the non-breeding season (migratory connectivity) is essential for understanding and predicting population dynamics in the face of global change. We quantify variation in population spread and inter-population mixing in long-distance, terrestrial migrant land-bird populations (712 individuals from 98 populations of 45 species, from tagging studies in the Neotropic and Afro-Palearctic flyways). We evaluate the Mantel test as a metric of migratory connectivity, and explore the extent to which variance in population spread can be explained simply by geography. The mean distance between two individuals from the same population during the non-breeding season was 743km, covering 10-20% of the maximum width of Africa/South America. Individuals from different breeding populations tended to mix during the non-breeding season, although spatial segregation was maintained in species with relatively large non-breeding ranges (and, to a lesser extent, those with low population-level spread). A substantial amount of between-population variation in population spread was predicted simply by geography, with populations using non-breeding zones with limited land availability (e.g. Central America compared to South America) showing lower population spread. The high levels of population spread suggest that deterministic migration tactics are not generally adaptive; this makes sense in the context of the recent evolution of the systems, and the spatial and temporal unpredictability of non-breeding habitat. The conservation implications of generally low connectivity are that the loss (or protection) of any non-breeding site will have a diffuse but widespread effect on many breeding populations. Although low connectivity should engender population resilience to shifts in habitat (e.g. due to climate change), we suggest it may increase susceptibility to habitat loss. We hypothesize that, because a migrant species cannot adapt to both simultaneously, migrants generally may be more susceptible to population declines in the face of concurrent anthropogenic habitat and climate change.

Seasonal divergence in the sensitivity of evapotranspiration to climate and vegetation growth in the Yellow River Basin, China

AbstractSeasonal variations in terrestrial evapotranspiration (ET) in the Yellow River Basin (YRB) have crucial impacts on the seasonal trajectories of the regional water cycle, vegetation growth, and local climate feedback. However, the possibly divergent roles of climate and vegetation growth variations in controlling seasonal ET patterns remain poorly quantified. This study therefore quantifies the interannual sensitivity and attribution of ET to climate and vegetation growth variations in different seasons and different biomes in the YRB in China between 1982 and 2011, using the satellite‐derived normalized difference vegetation index (NDVI), FLUXNET‐based upscaled ET, and concurrent climate data. The results reveal a clear seasonal divergence in the interannual sensitivity of ET to climate and vegetation growth variations in the YRB. Interannual precipitation and NDVI variations play a dominant role in controlling seasonal ET variations in the YRB, with temperature having a marginal effect. Interannual ET sensitivity to precipitation weakens with an increasing mean annual precipitation gradient in almost all seasons, especially in summer and autumn. More importantly, a seasonally varying role of vegetation growth in mediating seasonal ET was discovered, and a crucial role of late‐growing‐season vegetation growth in controlling the seasonal trajectory of regional ET was explicitly identified. These results suggest that ongoing intensive vegetation restoration has crucial impacts on seasonal water‐cycle patterns and consequent terrestrial‐atmospheric biogeochemical feedback in the YRB.

Ecophysiological Responses ofTsuga canadensis(Eastern Hemlock) to Projected Atmospheric CO2and Warming

Abstract Tsuga canadensis (Eastern Hemlock) is a keystone tree species currently experiencing high mortality in southeastern US forests due to Hemlock Woolly Adelgid (Adelges tsugae; HWA) invasion. Investigating the impacts of concurrent climate change on Eastern Hemlock is important given its potential direct effects on this species and possible interactions of climatic factors with the continued spread of HWA. We conducted a 2-factorial experiment in controlled-environment growth chambers to test for the main effects and interactions of projected atmospheric CO2 concentrations and transitional-season warming on gas-exchange traits of Eastern Hemlock saplings collected from a northern Georgia field site. We hypothesized that elevated CO2 would increase photosynthesis and that warming would not influence photosynthesis, given the demonstrated capacity for photosynthetic temperature-acclimation in this species. Saplings in elevated CO2 exhibited ∼30% greater leaf-level photosynthesis (A) and ∼35% greater m...