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A Multi-Scale Sampling Strategy for Detecting Physiologically Significant Signals in AVIRIS Imagery

Models of photosynthetic production at ecosystem and global scales require multiple input parameters specifying physical and physiological surface features. While certain physical parameters (e.g., absorbed photosynthetically active radiation) can be derived from current satellite sensors, other physiologically relevant measures (e.g., vegetation type, water status, carboxylation capacity, or photosynthetic light-use efficiency), are not generally directly available from current satellite sensors at the appropriate geographic scale. Consequently, many model parameters must be assumed or derived from independent sources, often at an inappropriate scale. An abundance of ecophysiological studies at the leaf and canopy scales suggests strong physiological control of vegetation-atmosphere CO2 and water vapor fluxes, particularly in evergreen vegetation subjected to diurnal or seasonal stresses. For example hot, dry conditions can lead to stomatal closure, and associated "downregulation" of photosynthetic biochemical processes, a phenomenon often manifested as a "midday photosynthetic depression". A recent study with the revised simple biosphere (SiB2) model demonstrated that photosynthetic downregulation can significantly impact global climate. However, at the global scale, the exact significance of downregulation remains unclear, largely because appropriate physiological measures are generally unavailable at this scale. Clearly, there is a need to develop reliable ways of extracting physiologically relevant information from remote sensing. Narrow-band spectrometers offer many opportunities for deriving physiological parameters needed for ecosystem and global scale photosynthetic models. Experimental studies on the ground at the leaf- to stand-scale have indicated that several narrow-band features can be used to detect plant physiological status. One physiological signal is caused by xanthophyll cycle pigment activity, and is often expressed as the Photochemical Reflectance Index (PRI). Because the xanthophyll cycle pigments are photoregulatory pigments closely linked to photosynthetic function, this index can be used to derive relative photosynthetic rates. An additional signal with physiological significance is the 970 nm water absorption band, which provides a measure of liquid water content. This feature has been quantified both using a simple 2-band ratio (900/970 nm, here referred to as the "Water Band Index" or WBI;), and using the "continuum removal" method. Current atmospheric correction methods for AVIRIS imagery also obtain quantitative expressions of surface liquid water absorption based on the 970 nm water band and may be comparable to ground-based estimates of water content using this feature. However, physiological interpretations of both the PRI and the WBI are best understood at the leaf and canopy scales, where complications of atmospheric interference and complex stand and landscape features can be minimized, and where experimental manipulations can be readily applied. Currently it is not known whether these physiological indices can be used to derive meaningful physiological information from AVIRIS imagery. In addition to the problem of atmospheric interference, another challenge is that any simple physiological index can be confounded by multiple factors unrelated to physiology, and this problem can become more severe at progressively larger spatial scales. For example, previous work has suggested that both the PRI and the WBI, are strongly correlated with other optical measures of canopy structure (e.g., the Normalized Difference Vegetation Index or green vegetation fraction), indicating a confounding effect of structure on physiological signals at the larger, landscape scale. Furthermore, the normal operating mode of most imaging spectrometers does not allow simultaneous, ground truthing at a level of detail needed for physiological sampling. Additionally, manipulative experiments of physiology are difficult to apply at a geographic scale suitable for comparison with remote imagery, which often works at spatial scales that are several orders of magnitude larger than those typically used for physiological studies. These limitations require the consideration of alternative approaches to validating physiological information derived from AVIRIS data. In this report, we present a multi-scale sampling approach to detecting physiologically significant signals in narrow-band spectra. This approach explores the multi-dimensional data space provided by narrow-band spectrometry, and combines AVIRIS imagery at a large scale, with ground spectral sampling at an intermediate scale, and detailed ecophysiological measurements at a fine scale, to examine seasonally and spatially changing relationships between multiple structural and physiological variables. Examples of this approach are provided by simultaneous sampling of the Normalized Difference Vegetation Index (NDVI), an index of fractional PAR interception and green vegetation cover, the Water Band Index (WBI, an index of liquid water absorption, and the Photochemical Reflectance Index (PRI, an index of xanthophyll cycle pigment activity and photosynthetic light-use efficiency. By directly linking changing optical properties sampled on the ground with measurable physiological states, we hope to develop a basis for interpreting similar signals in AVIRIS imagery.

Gamon, John A.↗

The first Earth Resources Technology Satellite - Nearly two years of operation

A brief status report is given of the ERTS-1 satellite system as of June, 1974, and some applications of the ERTS-1 images are discussed. The multispectral images make it possible to identify or measure the quality and composition of water, the potential water content of snow, the moisture and possible composition of soils, the types and state of vegetation cover, and factors relating to stresses on the environment. The orthographic view of the earth provided by the satellite makes it possible to rapidly produce thematic maps, on a scale of 1:250,000, of most areas of the world. The regular, repetitive coverage provided by ERTS-1 every 18 days is important in areas such as water-supply and flood-damage studies. The use of ERTS-1 imagery for land-use planning, wetlands surveying, assessing marine resources, and observing processes such as desertification in the African Sahel is discussed.

Nordberg, W.↗

Remote sensing for exploration - An overview

The use of remote sensing in resource exploration is reviewed, with emphasis placed on new developments in high spectral resolution remote-sensing techniques for mineralogic and vegetation mapping. Topics discussed include aerial photography and satellite remote sensing, concepts and principles of spectral data collection, spectral properties of rocks and minerals, spectral properties of vegetation, and botanical aspects of geochemical stress. The discussion also covers applications of Landsat multispectral scanner data to lithologic and geobotanic studies and the future development of data acquisition and data interpretation techniques.

Goetz, A. F. H.↗

The application of remote sensing in geobotanical exploration for metal sulfides

A field study was conducted in Mineral, VA in 1980-82 to test the suitability of remote sensing techniques for geobotanical exploration. It was found that on trees growing over lead sulfide deposits, buds opened later and leaves were smaller than on trees growing on soils with background levels of lead and copper. This difference in leaf growth could be detected in remotely sensed data. In the spring, the smaller leaf size of metal-stressed trees resulted in a greater contribution from the soil and bark to the total reflectance imaged by the sensor. In the fall, the leaves of metal-stressed oaks sensed earlier than surrounding vegetation, which was also detected in remotely sensed data. It is concluded that vegetation growing on lead sulfide deposits has a shorter growing season than surrounding vegetation on unmineralized soil and that remotely sensed data collected at either end of the growing season can be used to locate geobotanical anomalies associated with these deposits.

Masuoka, E. J.↗

Land surface interaction

The topics covered include the following: land and climate modeling; sensitivity studies; the process of a land model; model-specific parameterizations; water stress; within-canopy resistances; partial vegetation; canopy temperature; and present experience with a land model coupled to a general circulation model.

Dickinson, Robert E.↗

Larch (Larix dahurica Turcz) growth response to climate change in the Siberian permafrost zone

Larch-dominant communities are the most extensive high-latitude forests in Eurasia and are experiencing the strongest impacts from warming temperatures. We analyzed larch (Larix dahurica Turcz) growth index (GI) response to climate change. The studied larch-dominant communities are located within the permafrost zone of Northern Siberia at the northern tree limit (ca. N 67° 38′, E 99° 07′). Methods included dendrochronology, analysis of climate variables, root zone moisture content, and satellitederived gross (GPP) and net (NPP) primary productivity. It was found that larch response to warming included a period of increased annual growth increment (GI) (from the 1970s to ca. 1995) with a follow on GI decline. Increase in GI correlated with summer air temperature, whereas an observed decrease in GI was caused by water stress (vapor pressure deficit and drought increase). Water stress impact on larch growth in permafrost was not observed before the onset of warming (ca. 1970). Water limitation was also indicated by GI dependence on soil moisture stored during the previous year. Water stress was especially pronounced for stands growing on rocky soils with low water-holding capacity. GPP of larch communities showed an increasing trend, whereas NPP stagnated. A similar pattern of GI response to climate warming has also been observed for Larix sibirica Ledeb, Pinus sibirica Du Tour, and Abies sibirica Ledeb in the forests of southern Siberia. Thus, warming in northern Siberia permafrost zone resulted in an initial increase in larch growth from the 1970s to the mid-1990s. After that time, larch growth increment has decreased. Since ca. 1990, water stress at the beginning of the vegetative period became, along with air temperature, a main factor affecting larch growth within the permafrost zone.

Larix dahurica↗

Vegetation responses to air dryness amplify future land surface warming

Temperature exerts a first-order control on vegetation photosynthesis and transpiration. Yet most studies investigating temperature impacts on plants rely on near-surface air temperature, rather than canopy temperature—the temperature plants actually experience. Because canopy temperature directly regulates ecosystem function, it provides a more accurate measure of vegetation–climate interactions. Combining Earth System Model (ESM) simulations and satellite observations in a dual emergent constraint, here we show that canopy temperature is projected to increase substantially more than air temperature (~0.11-degrees more or a 16% increase in their difference) over the 21st century. The ESM ensemble median fails to capture these stronger increases in the majority of vegetated regions. We find that the largest projected increases in the difference between canopy and air temperature are predicted to occur in regions where elevating moisture stress—particularly rising vapor pressure deficit—increasingly constrains vegetation growth and transpiration. This implies that future warming will impose stronger constraints on plant function than currently estimated. Relying on air temperature alone will therefore lead to systematic underestimation of temperature effects on photosynthesis, vegetation growth, and the land carbon sink. Accurate representation of canopy temperature in ESMs is thus essential to improve projections of ecosystem responses and feedbacks to climate change.

Green, Julia K↗

Chaparral vegetation reflectance and its potential utility for assessment of fire hazard

Current methods for assessment of ignition potential often fail to alert wildland managers to the severity of drought-induced fire hazard at remote locations and over large geographic areas. After the severe fires of 1988 in the western United States, the need was heightened for improved fire hazard assessment techniques. Chaparral vegetation is particularly receptive to recurring drought-related episodes of extreme fire hazard and was thus chosen for study here. Demonstrated herein is that chaparral vegetation has considerably different reflecting properties at different levels of drought stress. As such, remote sensing may have utility for fire hazard assessment in this vegetation type.

Cohen, Warren B.↗

Robust inference of ecosystem soil water stress from eddy covariance data

Eddy covariance data are invaluable for determining ecosystem water use strategies under soil water stress. However, existing stress inference methods require numerous subjective data processing and model specification assumptions whose effect on the inferred soil water stress signal is rarely quantified. These uncertainties may confound the stress inference and the generalization of ecosystem water use strategies across multiple sites and studies. In this research, we quantify the sensitivity of soil water stress signals inferred from eddy covariance data to the prevailing data and modeling assumptions (i.e., their robustness) to compile a comprehensive list of sites with robust soil water stress signals and assess the performance of current stress inference methods. To accomplish this, we identify the most prevalent assumptions from the literature and perform a digital factorial experiment to extract probability distributions of plausible soil water stress signals and model performance at 151 FLUXNET2015 and AmeriFlux-FLUXNET sites. Here, we develop a new framework that summarizes these probability distributions to classify and rank the robustness of each site’s soil water stress signal, which we display with a user-friendly heat map. We estimate that only 5%–36% of sites exhibit a robust soil water stress signal due to deficient model performance and poorly constrained ecosystem water use parameters. We also find that the lack of robustness is site-specific, which undermines grouping stress signals by broad ecosystem categories or comparing results across studies with differing assumptions. Lastly, existing stress inference methods appear better suited for eddy covariance sites with grass/annual vegetation. Our findings call for more careful and consistent inference of ecosystem water stress from eddy covariance data.

54 ENVIRONMENTAL SCIENCES↗

Interactive Biogenic Emissions and Drought Stress Effects on Atmospheric Composition in NASA GISS ModelE

Drought is a hydroclimatic extreme that causes perturbations to the terrestrial biosphere and acts as a stressor on vegetation, affecting emissions patterns. During severe drought, isoprene emissions are reduced. In this paper, we focus on capturing this reduction signal by implementing a new percentile isoprene drought stress (y d ) algorithm in NASA GISS ModelE based on the MEGAN3 (Model of Emissions of Gases and Aerosols from Nature Version 3) approach as a function of a photosynthetic parameter (V c,max ) and water stress (β). Four global transient simulations from 2003–2013 are used to demonstrate the effect without y d (Default_ModelE) and with online y d (DroughtStress_ModelE). DroughtStress_ModelE is evaluated against the observed isoprene measurements at the Missouri Ozarks AmeriFlux (MOFLUX) site during the 2012 severe drought where improvements in the correlation coefficient indicate it is a suitable drought stress parameterization to capture the reduction signal during severe drought. The application of y d globally leads to a decadal average reduction of ∼ 2.7 %, which is equivalent to ∼14.6 Tg yr -1 of isoprene. The changes have larger impacts in regions such as the southeastern US. DroughtStress_ModelE is validated using the satellite ΩHCHO column from the Ozone Monitoring Instrument (OMI) and surface O 3 observations across regions of the US to examine the effect of drought on atmospheric composition. It was found that the inclusion of isoprene drought stress reduced the overestimation of ΩHCHO in Default_ModelE during the 2007 and 2011 southeastern US droughts and led to improvements in simulated O 3 during drought periods. We conclude that isoprene drought stress should be tuned on a model-by-model basis because the variables used in the parameterization responses are relative to the land surface model hydrology scheme (LSM) and the effects of y d application could be larger than seen here due to ModelE not having large biases of isoprene during severe drought.

drought stress effects↗

Using Hyperspectral Imagery to Identify Turfgrass Stresses

The use of a form of remote sensing to aid in the management of large turfgrass fields (e.g. golf courses) has been proposed. A turfgrass field of interest would be surveyed in sunlight by use of an airborne hyperspectral imaging system, then the raw observational data would be preprocessed into hyperspectral reflectance image data. These data would be further processed to identify turfgrass stresses, to determine the spatial distributions of those stresses, and to generate maps showing the spatial distributions. Until now, chemicals and water have often been applied, variously, (1) indiscriminately to an entire turfgrass field without regard to localization of specific stresses or (2) to visible and possibly localized signs of stress for example, browning, damage from traffic, or conspicuous growth of weeds. Indiscriminate application is uneconomical and environmentally unsound; the amounts of water and chemicals consumed could be insufficient in some areas and excessive in most areas, and excess chemicals can leak into the environment. In cases in which developing stresses do not show visible signs at first, it could be more economical and effective to take corrective action before visible signs appear. By enabling early identification of specific stresses and their locations, the proposed method would provide guidance for planning more effective, more economical, and more environmentally sound turfgrass-management practices, including application of chemicals and water, aeration, and mowing. The underlying concept of using hyperspectral imagery to generate stress maps as guides to efficient management of vegetation in large fields is not new; it has been applied in the growth of crops to be harvested. What is new here is the effort to develop an algorithm that processes hyperspectral reflectance data into spectral indices specific to stresses in turfgrass. The development effort has included a study in which small turfgrass plots that were, variously, healthy or subjected to a variety of controlled stresses were observed by use of a hand-held spectroradiometer. The spectroradiometer readings in the wavelength range from 350 to 1,000 nm were processed to extract hyperspectral reflectance data, which, in turn, were analyzed to find correlations with the controlled stresses. Several indices were found to be correlated with drought stress and to be potentially useful for identifying drought stress before visible symptoms appear.

Hutto, Kendall↗

Seismic stress responses of soybean to different photosynthetic photon flux

Physical agitation applied as periodic seismic stress (shaking) reduced stem elongation, leaf expansion, and biomass accumulation by vegetative soybeans. Level of photon flux (PPF) influenced the type and extent of plant response to mechanical stress. Plant parts responded differently as PPF varied between 135 and 592 micromoles m-2 s-1. Stem length was significantly reduced by seismic stress at 135 micromoles m-2 s-1 but this effect was insignificant at higher PPFs. Reduced stem length resulted from an inhibition of internode elongation. Stem diameter was unaffected by stress at the PPFs tested. In contrast to effects on stem elongation, leaf area was insensitive to stress treatments at 135 micromoles m-2 s-1 but was progressively inhibited by stress as PPF increased. Statistically significant reductions in shoot f. wt and d. wt by seismic stress occurred only at 295 micromoles m-2 s-1. Root biomass accumulation was not affected by seismic stress at any PPF used in this study.

NASA Program Space Biology↗

Photosynthesis-dependent Isoprene Emission from Leaf to Planet in a Global Carbon-chemistry-climate Model

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the FarquharBallBerry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50 of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 6496) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr1 that increases by 30 in the artificial absence of plant water stress and by 55 for potential natural vegetation.

photosynthesis↗

A physiological signal derived from sun-induced chlorophyll fluorescence quantifies crop physiological response to environmental stresses in the U.S. Corn Belt

Sun-induced chlorophyll fluorescence (SIF) measurements have shown unique potential for quantifying plant physiological stress. However, recent investigations found canopy structure and radiation largely control SIF, and physiological relevance of SIF remains yet to be fully understood. This study aims to evaluate whether the SIF-derived physiological signal improves quantification of crop responses to environmental stresses, by analyzing data at three different spatial scales within the U.S. Corn Belt, i.e. experiment plot, field, and regional scales, where ground-based portable, stationary and space-borne hyperspectral sensing systems are used, respectively. We found that, when controlling for variations in incoming radiation and canopy structure, crop SIF signals can be decomposed into non-physiological (i.e. canopy structure and radiation, 60% ~ 82%) and physiological information (i.e. physiological SIF yield, Φ F , 17% ~ 31%), which confirms the contribution of physiological variation to SIF. We further evaluated whether Φ F indicated plant responses under high-temperature and high vapor pressure deficit (VPD) stresses. The plot-scale data showed that Φ F responded to the proxy for physiological stress (partial correlation coefficient, r p = 0.40, p < 0.001) while non-physiological signals of SIF did not respond ( p > 0.1). The field-scale Φ F data showed water deficit stress from the comparison between irrigated and rainfed fields, and Φ F was positively correlated with canopy-scale stomatal conductance, a reliable indicator of plant physiological condition (correlation coefficient r = 0.60 and 0.56 for an irrigated and rainfed sites, respectively). The regional-scale data showed Φ F was more strongly correlated spatially with air temperature and VPD ( r = 0.23 and 0.39) than SIF ( r = 0.11 and 0.34) for the U.S. Corn Belt. The lines of evidence suggested that Φ F reflects crop physiological responses to environmental stresses with greater sensitivity to stress factors than SIF, and the stress quantification capability of Φ F is spatially scalable. Utilizing Φ F for physiological investigations will contribute to improve our understanding of vegetation responses to high-temperature and high-VPD stresses.

54 ENVIRONMENTAL SCIENCES↗

Leaf turgor loss point shapes local and regional distributions of evergreen but not deciduous tropical trees

Summary The effects of climate change on tropical forests will depend on how diverse tropical tree species respond to drought. Current distributions of evergreen and deciduous tree species across local and regional moisture gradients reflect their ability to tolerate drought stress, and might be explained by functional traits. We measured leaf water potential at turgor loss (i.e. ‘wilting point’; π tlp ), wood density (WD) and leaf mass per area (LMA) on 50 of the most abundant tree species in central Panama. We then tested their ability to explain distributions of evergreen and deciduous species within a 50 ha plot on Barro Colorado Island and across a 70 km rainfall gradient spanning the Isthmus of Panama. Among evergreen trees, species with lower π tlp were associated with drier habitats, with π tlp explaining 28% and 32% of habitat association on local and regional scales, respectively, greatly exceeding the predictive power of WD and LMA. In contrast, π tlp did not predict habitat associations among deciduous species. Across spatial scales, π tlp is a useful indicator of habitat preference for tropical tree species that retain their leaves during periods of water stress, and holds the potential to predict vegetation responses to climate change.

59 BASIC BIOLOGICAL SCIENCES↗

A Dominant Arabidopsis Thaliana ACTIN7 Mutant for Studies of Cytoskeletal-Mediated Root Gravity and Spaceflight Stress Responses

A forward genetic screen for Arabidopsis thaliana mutants that exhibited differential sensitivity to the actin-disrupting compound, latrunculin B (LatB), was conducted to uncover new players involved in actin-mediated root gravity responses. This to the isolation of a mutant that exhibited robust primary root growth at 100 nM LatB, which is a concentration that severely inhibits wild-type root elongation. Phenotypic analysis revealed that hypocotyl elongation in the dark and root hair tip growth in the mutant could tolerate LatB concentrations that impaired these processes in wild type. A cross between the mutant and wild type resulted in progeny resistance to LatB, which indicated that the mutant is dominant (hereafter referred to as LBR1 for LatB Resistant1). Filamentous-actin (F-actin) organization in LBR1 primary roots remained intact at 100 nM LatB, while that of wild type exhibited fragmented F-actin. Next generation sequencing revealed that LBR1 had a single nucleotide polymorphism (SNP) in the AT5G09810 gene that changed cytosine to a thiamine at the first exon. AT5G09810 encodes ACTIN7 (ACT7), which is one of three vegetative actin isoforms in A. thaliana. The SNP in the ACT7 gene led to a change in a single amino acid from proline at position 32 to a serine. Transgenic complementation of LBR1 plants with wild-type ACT7 under the control of the ACT7 promoter (pACT7:ACT7) and wild-type plants with LBR1, which contained the proline to serine mutation, also under the ACT7 promoter (pACT7:LBR1) confirmed that LBR1 is ACT7. The pACT7:LBR1 construct was also able to confer LatB resistance to the act7-5 and act2-3 vegetative ACT mutants. Moreover, LBR1 exhibited partial tolerance to salt and low phosphate, and enhanced root skewing on a clinostat, suggesting that site-directed engineering of vegetative ACT presents a strategy for generating stress-tolerant plants for spaceflight applications and studies of actin-mediated gravity responses.

Plant Space Biology↗

A Dominant Arabidopsis Thaliana ACTIN7 Mutant for Studies of Cytoskeletal-Mediated Root Gravity and Spaceflight Stress Responses

A forward genetic screen for Arabidopsis thaliana mutants that exhibited differential sensitivity to the actin-disrupting compound, latrunculin B (LatB), was conducted to uncover new players involved in actin-mediated root gravity responses. This led to the isolation of a mutant that exhibited robust primary root growth at 100 nM LatB, which is a concentration that severely inhibits wild-type root elongation. Phenotypic analysis revealed that hypocotyl elongation in the dark and root hair tip growth in the mutant could tolerate LatB concentrations that impaired these processes in wild type. A cross between the mutant and wild type resulted in progeny resistance to LatB, which indicated that the mutant is dominant (hereafter referred to as LBR1 for LatB Resistant1). Filamentous-actin (F-actin) organization in LBR1 primary roots remained intact at 100 nM LatB, while that of wild type exhibited fragmented F-actin. Next generation sequencing revealed that LBR1 had a single nucleotide polymorphism (SNP) in the AT5G09810 gene that changed cytosine to a thiamine at the first exon. AT5G09810 encodes ACTIN7 (ACT7), which is one of three vegetative actin isoforms in A. thaliana. The SNP in the ACT7 gene led to a change in a single amino acid from proline at position 32 to a serine. Transgenic complementation of LBR1 plants with wild-type ACT7 under the control of the ACT7 promoter (pACT7:ACT7) and wild-type plants with LBR1, which contained the proline to serine mutation, also under the ACT7 promoter (pACT7:LBR1) confirmed that LBR1 is ACT7. The pACT7:LBR1 construct was also able to confer LatB resistance to the act7-5 and act2-3 vegetative ACT mutants. Moreover, LBR1 exhibited partial tolerance to salt and low phosphate, and enhanced root skewing on a clinostat, suggesting that site-directed engineering of vegetative ACT presents a strategy for generating stress-tolerant plants for spaceflight applications and studies of actin-mediated gravity responses.

Plant Space Biology↗