Stan D. Wullschleger

Photosynthetic acclimation in trees to rising atmospheric CO2: A broader perspective.

Analysis of leaf-level photosynthetic responses of 39 tree species grown in elevated concentrations of atmospheric CO2 indicated an average photosynthetic enhancement of 44% when measured at the growth [CO2]. When photosynthesis was measured at a common ambient [CO2], photosynthesis of plants grown at elevated [CO2] was reduced, on average, 21% relative to ambient-grown trees, but variability was high. The evidence linking photosynthetic acclimation in trees with changes at the biochemical level is examined, along with anatomical and morphological changes in trees that impact leaf- and canopy-level photosynthetic response to CO2 enrichment. Nutrient limitations and variations in sink strength appear to influence photosynthetic acclimation, but the evidence in trees for one predominant factor controlling acclimation is lacking. Regardless of the mechanisms that underlie photosynthetic acclimation, it is doubtful that this response will be complete. A new focus on adjustments to rising [CO2] at canopy, stand, and forest scales is needed to predict ecosystem response to a changing environment.

NET PRIMARY PRODUCTIVITY OF A CO2‐ENRICHED DECIDUOUS FOREST AND THE IMPLICATIONS FOR CARBON STORAGE

A central question concerning the response of terrestrial ecosystems to a changing atmosphere is whether increased uptake of carbon in response to increasing at- mospheric carbon dioxide concentration results in greater plant biomass and carbon storage or, alternatively, faster cycling of C through the ecosystem. Net primary productivity (NPP) of a closed-canopy Liquidambar styraciflua (sweetgum) forest stand was assessed for three years in a free-air CO2-enrichment (FACE) experiment. NPP increased 21% in stands ex- posed to elevated CO2, and there was no loss of response over time. Wood increment increased significantly during the first year of exposure, but subsequently most of the extra C was allocated to production of leaves and fine roots. These pools turn over more rapidly than wood, thereby reducing the potential of the forest stand to sequester additional C in response to atmospheric CO2 enrichment. Hence, while this experiment provides the first evidence that CO2 enrichment can increase productivity in a closed-canopy deciduous forest, the implications of this result must be tempered because the increase in productivity resulted in faster cycling of C through the system rather than increased C storage in wood. The fate of the additional C entering the soil system and the environmental interactions that influence allocation need further investigation.

Oak forest carbon and water simulations: model intercomparisons and evaluations against independent data

Models represent our primary method for integration of small-scale, process- level phenomena into a comprehensive description of forest-stand or ecosystem function. They also represent a key method for testing hypotheses about the response of forest ecosystems to multiple changing environmental conditions. This paper describes the eval- uation of 13 stand-level models varying in their spatial, mechanistic, and temporal com- plexity for their ability to capture intra- and interannual components of the water and carbon cycle for an upland, oak-dominated forest of eastern Tennessee. Comparisons between model simulations and observations were conducted for hourly, daily, and annual time steps. Data for the comparisons were obtained from a wide range of methods including: eddy covariance, sapflow, chamber-based soil respiration, biometric estimates of stand-level net primary production and growth, and soil water content by time or frequency domain reflectometry. Response surfaces of carbon and water flux as a function of environmental drivers, and a variety of goodness-of-fit statistics (bias, absolute bias, and model efficiency) were used to judge model performance. A single model did not consistently perform the best at all time steps or for all variables considered. Intermodel comparisons showed good agreement for water cycle fluxes, but considerable disagreement among models for predicted carbon fluxes. The mean of all model outputs, however, was nearly always the best fit to the observations. Not surprisingly, models missing key forest components or processes, such as roots or modeled soil water content, were unable to provide accurate predictions of ecosystem responses to short-term drought phenomenon. Nevertheless, an inability to correctly capture short-term physiolog- ical processes under drought was not necessarily an indicator of poor annual water and carbon budget simulations. This is possible because droughts in the subject ecosystem were of short duration and therefore had a small cumulative impact. Models using hourly time steps and detailed mechanistic processes, and having a realistic spatial representation of the forest ecosystem provided the best predictions of observed data. Predictive ability of all models deteriorated under drought conditions, suggesting that further work is needed to evaluate and improve ecosystem model performance under unusual conditions, such as drought, that are a common focus of environmental change discussions.

The potential response of terrestrial carbon storage to changes in climate and atmospheric CO2

We use a georeferenced model of ecosystem carbon dynamics to explore the sensitivity of global terrestrial carbon storage to changes in atmospheric CO2 and climate. We model changes in ecosystem carbon density, but we do not model shifts in vegetation type. A model of annual NPP is coupled with a model of carbon allocation in vegetation and a model of decomposition and soil carbon dynamics. NPP is a function of climate and atmospheric CO2 concentration. The CO2 response is derived from a biochemical model of photosynthesis. With no change in climate, a doubling of atmospheric CO2 from 280 ppm to 560 ppm enhances equilibrium global NPP by 16.9%; equilibrium global terrestrial ecosystem carbon (TEC) increases by 14.9%. Simulations with no change in atmospheric CO2 concentration but changes in climate from five atmospheric general circulation models yield increases in global NPP of 10.0–14.8%. The changes in NPP are very nearly balanced by changes in decomposition, and the resulting changes in TEC range from an increase of 1.1% to a decrease of 1.1%. These results are similar to those from analyses using bioclimatic biome models that simulate shifts in ecosystem distribution but do not model changes in carbon density within vegetation types. With changes in both climate and a doubling of atmospheric CO2, our model generates increases in NPP of 30.2–36.5%. The increases in NPP and litter inputs to the soil more than compensate for any climate stimulation of decomposition and lead to increases in global TEC of 15.4–18.2%.

Quantifying and relating land-surface and subsurface variability in permafrost environments using LiDAR and surface geophysical datasets

The value of remote sensing and surface geophysical data for characterizing the spatial variability and relationships between land-surface and subsurface properties was explored in an Alaska (USA) coastal plain ecosystem. At this site, a nested suite of measurements was collected within a region where the land surface was dominated by polygons, including: LiDAR data; ground-penetrating radar, electromagnetic, and electrical-resistance tomography data; active-layer depth, soil temperature, soil-moisture content, soil texture, soil carbon and nitrogen content; and pore-fluid cations. LiDAR data were used to extract geomorphic metrics, which potentially indicate drainage potential. Geophysical data were used to characterize active-layer depth, soil-moisture content, and permafrost variability. Cluster analysis of the LiDAR and geophysical attributes revealed the presence of three spatial zones, which had unique distributions of geomorphic, hydrological, thermal, and geochemical properties. The correspondence between the LiDAR-based geomorphic zonation and the geophysics-based active-layer and permafrost zonation highlights the significant linkage between these ecosystem compartments. This study suggests the potential of combining LiDAR and surface geophysical measurements for providing high-resolution information about land-surface and subsurface properties as well as their spatial variations and linkages, all of which are important for quantifying terrestrial-ecosystem evolution and feedbacks to climate.ResuméLa portée de la télédétection et des données géophysique de surface pour caractériser la variabilité spatiale et les relations entre la surface du terrain et les propriétés de la subsurface a été étudiée sous tous ses aspects dans l’écosystème de la plaine côtière d’Alaska (USA). Dans cette région, sur un site où la surface du sol est dominée par des polygones, une série de données se recoupant a été collectée, incluant : données LiDAR; géoradar, tomographie électromagnétique et résistivité; profondeur de la couche aquifère, température, teneur en humidité, texture, teneur en carbone et en azote du sol; et cations du fluide des pores. Les données Lidar ont été utilisées pour établir les cotes géomorphiques, qui peuvent indiquer un drainage potentiel. Des données géophysiques ont été utilisées pour déterminer la profondeur de la couche aquifère, la teneur en humidité du sol, et la variabilité du pergélisol. L’analyse par agglomérat des données LiDAR et des attributs géophysiques ont révélé la présence de trois zones spatiales ayant une distribution similaire des propriétés géomorphiques, hydrogéologiques, thermales et géochimiques. La correspondance entre la zonation géomorphique basée sur LiDAR, la couche aquifère selon la géophysique et la zonation permafrost, met en lumière la relation significative entre ces compartiments de l’écosystème. Cette étude montre le potentiel d’une combinaison des mesures LiDAR et des mesures géophysiques de surface pour fournir une information haute résolution sur les propriétés de surface et de subsurface du sol aussi bien que sur leur variations spatiales et liens, toutes étant importantes pour quantifier l’évolution de l’écosystème terrestre et les réponses au climat.ResumenSe exploró el valor de los sensores remotos y de los datos geofísicos de superficie para caracterizar la variabilidad espacial y las relaciones entre la superficie y las propiedades subsuperficiales en un ecosistema de planicie costera en Alaska (EEUU). En este sitio, un conjunto anidado de medidas fue colectado dentro de una región donde la superficie estaba dominada por polígonos, incluyendo: datos LiDAR; datos de radar, electromagnéticos, y tomografías de resistividad eléctrica; profundidad de la capa activa, temperatura del suelo, contenido de humedad del suelo, textura del suelo, contenido de carbono y nitrógeno en suelo; y cationes del fluido de poros. Los datos LiDAR fueron usados para extraer los indicadores geomórficos, que posiblemente indican un drenaje potencial. Los datos geofísicos fueron para caracterizar la profundidad de la capa activa, el contenido de humedad del suelo y la variabilidad del permafrost. En análisis de cluster de los LiDAR y los atributos geofísicos revelaron la presencia espacial de tres zonas, que tenían una única distribución de propiedades geomórficas, hidrológicas, térmicas y geoquímicas. La correspondencia entre la zonación geomórfica basada en LiDAR y la capa activa basada en geofísica y la zonación del permafrost destaca la vinculación significativa entre estos compartimentos del ecosistema. Este estudio sugiere el potencial de la combinación LiDAR y las mediciones geofísicas de superficie para proveer información de alta resolución acerca de las propiedades de la superficie y de la subsuperficie así como su variación espacial y su articulación, todos los cuales son importantes para cuantificar la evolución del ecosistema terrestre y las reacciones con el clima.摘要用来描述地表和地下性质的空间变异性和两者之间的关系的遥感和地面地球物理数据已在阿拉斯加(美国)的一个沿海平原生态系统进行了探讨。在本次研究场地的一个表面呈多边形的区域收集到了一套测量数据,包括激光雷达数据;探地雷达数据,电磁和电阻断层扫描数据;活性层深度,土壤温度,土壤水气含量,土壤质地,土壤碳和氮的含量;以及孔隙流体阳离子数据。激光雷达数据用来提取地貌指标,这可能指示出潜在的排泄。地球物理数据用来刻画活性层的深度,土壤水气含量和永久冻土的变化特征。通过对激光雷达和地球物理数据属性的聚类分析发现了三个在地形,水文,热和地球化学性质分布上存在异常的空间区域。基于激光雷达测量的地貌分区与基于地球物理数据的活性层和永久冻土分区之间的对应关系突出了这些生态系统分区间的紧密联系。本次研究表明可以通过结合激光雷达和地表地球物理测量来为地表和地下的性质以及它们在空间上的变化和关系提供高分辨率的信息,所有这些对于量化陆地生态系统的演化和对气候变化的反应都是非常重要的。ResumoNum ecossistema da planície costeira do Alaska (EUA) foi explorado o valor da deteção remota e de dados de geofísica de superfície para caracterizar a variabilidade espacial e as relações entre propriedades da superfície do terreno e da subsuperfície. Neste local, inserido numa região onde o terreno superficial é dominado por polígonos, foi recolhido um conjunto agregado de medições, incluindo: dados de LiDAR; dados de geoadar, eletromagnéticos e de tomografia de resistência elétrica; profundidade da camada ativa, temperatura do solo, teor de água no solo, textura do solo, teor de carbono e azoto no solo; e catiões no fluido poroso. Os dados LiDAR foram usados para extrair dimensões geomórficas que potencialmente indicam o potencial de drenagem. Os dados geofísicos foram usados para caracterizar a profundidade da camada ativa, o teor de humidade no solo e a variabilidade no permafrost. A análise grupal de atributos LiDAR e geofísicos revelou a presença de três zonas espaciais que tinham distribuições únicas de propriedades geomórficas, hidrológicas, térmicas e geoquímicas. A correspondência entre o zonamento geomórfico baseado no LiDAR e a zonação da camada activa baseada na geofísica e do permafrost, demonstra a significativa conexão entre estes compartimentos do ecossistema. Este estudo sugere o potencial da combinação de medições de LiDAR e de geofísica de superfície para fornecer informação de alta resolução acerca das propriedades da superfície do terreno e da subsuperfície, assim como sobre as variações espaciais e conexões, sendo todas elas importantes para a quantificação da evolução do ecossistema terrestre e as retroações com o clima.

Elevated CO2 enhances leaf senescence during extreme drought in a temperate forest

In 2007, an extreme drought and acute heat wave impacted ecosystems across the southeastern USA, including a 19-year-old Liquidambar styraciflua L. (sweetgum) tree plantation exposed to long-term elevated (E(CO(2))) or ambient (A(CO(2))) CO(2) treatments. Stem sap velocities were analyzed to assess plant response to potential interactions between CO(2) and these weather extremes. Canopy conductance and net carbon assimilation (A(net)) were modeled based on patterns of sap velocity to estimate indirect impacts of observed reductions in transpiration under E(CO(2)) on premature leaf senescence. Elevated CO(2) reduced sap flow by 28% during early summer, and by up to 45% late in the drought during record-setting temperatures. Modeled canopy conductance declined more rapidly in E(CO(2)) plots during this period, thereby directly reducing carbon gain at a greater rate than in A(CO(2)) plots. Indeed, pre-drought canopy A(net) was similar across treatment plots, but declined to ∼40% less than A(net) in A(CO(2)) as the drought progressed, likely leading to negative net carbon balance. Consequently, premature leaf senescence and abscission increased rapidly during this period, and was 30% greater for E(CO(2)). While E(CO(2)) can reduce leaf-level water use under droughty conditions, acute drought may induce excessive stomatal closure that could offset benefits of E(CO(2)) to temperate forest species during extreme weather events.

Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems

BACKGROUND Earth system models describe the physical, chemical and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. SCOPE Plant functional types (PFTs) have been adopted by modellers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review, the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current and future distribution of vegetation. CONCLUSIONS Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration and shrub expansion. However, representation of above- and especially below-ground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology and remote sensing will be required if we are to overcome these and other shortcomings.

The unseen iceberg: plant roots in arctic tundra

Plant roots play a critical role in ecosystem function in arctic tundra, but root dynamics in these ecosystems are poorly understood. To address this knowledge gap, we synthesized available literature on tundra roots, including their distribution, dynamics and contribution to ecosystem carbon and nutrient fluxes, and highlighted key aspects of their representation in terrestrial biosphere models. Across all tundra ecosystems, belowground plant biomass exceeded aboveground biomass, with the exception of polar desert tundra. Roots were shallowly distributed in the thin layer of soil that thaws annually, and were often found in surface organic soil horizons. Root traits - including distribution, chemistry, anatomy and resource partitioning - play an important role in controlling plant species competition, and therefore ecosystem carbon and nutrient fluxes, under changing climatic conditions, but have only been quantified for a small fraction of tundra plants. Further, the annual production and mortality of fine roots are key components of ecosystem processes in tundra, but extant data are sparse. Tundra root traits and dynamics should be the focus of future research efforts. Better representation of the dynamics and characteristics of tundra roots will improve the utility of models for the evaluation of the responses of tundra ecosystems to changing environmental conditions.

Connecting genes, coexpression modules, and molecular signatures to environmental stress phenotypes in plants.

BackgroundOne of the eminent opportunities afforded by modern genomic technologies is the potential to provide a mechanistic understanding of the processes by which genetic change translates to phenotypic variation and the resultant appearance of distinct physiological traits. Indeed much progress has been made in this area, particularly in biomedicine where functional genomic information can be used to determine the physiological state (e.g., diagnosis) and predict phenotypic outcome (e.g., patient survival). Ecology currently lacks an analogous approach where genomic information can be used to diagnose the presence of a given physiological state (e.g., stress response) and then predict likely phenotypic outcomes (e.g., stress duration and tolerance, fitness).ResultsHere, we demonstrate that a compendium of genomic signatures can be used to classify the plant abiotic stress phenotype in Arabidopsis according to the architecture of the transcriptome, and then be linked with gene coexpression network analysis to determine the underlying genes governing the phenotypic response. Using this approach, we confirm the existence of known stress responsive pathways and marker genes, report a common abiotic stress responsive transcriptome and relate phenotypic classification to stress duration.ConclusionLinking genomic signatures to gene coexpression analysis provides a unique method of relating an observed plant phenotype to changes in gene expression that underlie that phenotype. Such information is critical to current and future investigations in plant biology and, in particular, to evolutionary ecology, where a mechanistic understanding of adaptive physiological responses to abiotic stress can provide researchers with a tool of great predictive value in understanding species and population level adaptation to climate change.

Phytosequestration: Carbon Biosequestration by Plants and the Prospects of Genetic Engineering

Photosynthetic assimilation of atmospheric carbon dioxide by land plants offers the underpinnings for terrestrial carbon (C) sequestration. A proportion of the C captured in plant biomass is partitioned to roots, where it enters the pools of soil organic C and soil inorganic C and can be sequestered for millennia. Bioenergy crops serve the dual role of providing biofuel that offsets fossil-fuel greenhouse gas (GHG) emissions and sequestering C in the soil through extensive root systems. Carbon captured in plant biomass can also contribute to C sequestration through the deliberate addition of biochar to soil, wood burial, or the use of durable plant products. Increasing our understanding of plant, microbial, and soil biology, and harnessing the benefits of traditional genetics and genetic engineering, will help us fully realize the GHG mitigation potential of phytosequestration.