Mapping the Leaf Economic Spectrum across West African Tropical Forests Using UAV-Acquired Hyperspectral Imagery

The leaf economic spectrum (LES) describes a set of universal trade-offs between leaf mass per area (LMA), leaf nitrogen (N), leaf phosphorus (P) and leaf photosynthesis that influence patterns of primary productivity and nutrient cycling. Many questions regarding vegetation-climate feedbacks can be addressed with a better understanding of LES traits and their controls. Remote sensing offers enormous potential for generating large-scale LES trait data. Yet so far, canopy studies have been limited to imaging spectrometers onboard aircraft, which are rare, expensive to deploy and lack fine-scale resolution. In this study, we measured VNIR (visible-near infrared (400–1050 nm)) reflectance of individual sun and shade leaves in 7 one-ha tropical forest plots located along a 1200–2000 mm precipitation gradient in West Africa. We collected hyperspectral imaging data from 3 of the 7 plots, using an octocopter-based unmanned aerial vehicle (UAV), mounted with a hyperspectral mapping system (450–950 nm, 9 nm FWHM). Using partial least squares regression (PLSR), we found that the spectra of individual sun leaves demonstrated significant (p < 0.01) correlations with LMA and leaf chemical traits: r2 = 0.42 (LMA), r2 = 0.43 (N), r2 = 0.21 (P), r2 = 0.20 (leaf potassium (K)), r2 = 0.23 (leaf calcium (Ca)) and r2 = 0.14 (leaf magnesium (Mg)). Shade leaf spectra displayed stronger relationships with all leaf traits. At the airborne level, four of the six leaf traits demonstrated weak (p < 0.10) correlations with the UAV-collected spectra of 58 tree crowns: r2 = 0.25 (LMA), r2 = 0.22 (N), r2 = 0.22 (P), and r2 = 0.25 (Ca). From the airborne imaging data, we used LMA, N and P values to map the LES across the three plots, revealing precipitation and substrate as co-dominant drivers of trait distributions and relationships. Positive N-P correlations and LMA-P anticorrelations followed typical LES theory, but we found no classic trade-offs between LMA and N. Overall, this study demonstrates the application of UAVs to generating LES information and advancing the study and monitoring tropical forest functional diversity.

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Linking hydraulic traits to tropical forest function in a size-structured and trait-driven model (TFS v.1-Hydro)

Geoscientific Model Development ◽

10.5194/gmd-9-4227-2016 ◽

2016 ◽

Vol 9 (11) ◽

pp. 4227-4255 ◽

Cited By ~ 86

Author(s):

Bradley O. Christoffersen ◽

Manuel Gloor ◽

Sophie Fauset ◽

Nikolaos M. Fyllas ◽

David R. Galbraith ◽

...

Keyword(s):

Tropical Forest ◽

Water Potential ◽

Plant Traits ◽

Coupled Model ◽

Leaf Traits ◽

Tree Size ◽

Leaf Mass Per Area ◽

Stem Water Potential ◽

Plant Hydraulics ◽

Individual Trees

Abstract. Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g., turgor loss point πtlp, bulk elastic modulus ε, hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50 % loss of conductivity for both xylem (P50,x) and stomata (P50,gs), and the leaf : sapwood area ratio Al : As). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity (Amax), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait–trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. Remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted.

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The deep Chandra survey in the SDSS J1030+0524 field

Astronomy and Astrophysics ◽

10.1051/0004-6361/202037914 ◽

2020 ◽

Vol 637 ◽

pp. A52 ◽

Cited By ~ 2

Author(s):

R. Nanni ◽

R. Gilli ◽

C. Vignali ◽

M. Mignoli ◽

A. Peca ◽

...

Keyword(s):

Large Scale ◽

Near Infrared ◽

Infrared Imaging ◽

Cumulative Number ◽

Imaging Data ◽

X Ray ◽

Large Scale Structures ◽

Multi Wavelength ◽

Deep Fields ◽

Initial Source

We present the X-ray source catalog for the ∼479 ks Chandra exposure of the SDSS J1030+0524 field, which is centered on a region that shows the best evidence to date of an overdensity around a z > 6 quasar, and also includes a galaxy overdensity around a Compton-thick Fanaroff-Riley type II (FRII) radio galaxy at z = 1.7. Using wavdetect for initial source detection and ACIS Extract for source photometry and significance assessment, we create preliminary catalogs of sources that are detected in the full (0.5−7.0 keV), soft (0.5−2.0 keV), and hard (2−7 keV) bands, respectively. We produce X-ray simulations that mirror our Chandra observation to filter our preliminary catalogs and achieve a completeness level of > 91% and a reliability level of ∼95% in each band. The catalogs in the three bands are then matched into a final main catalog of 256 unique sources. Among them, 244, 193, and 208 are detected in the full, soft, and hard bands, respectively. The Chandra observation covers a total area of 335 arcmin2 and reaches flux limits over the central few square arcmins of ∼3 × 10−16, 6 × 10−17, and 2 × 10−16 erg cm−2 s−1 in the full, soft, and hard bands, respectively This makes J1030 field the fifth deepest extragalactic X-ray survey to date. The field is part of the Multiwavelength Survey by Yale-Chile (MUSYC), and is also covered by optical imaging data from the Large Binocular Camera (LBC) at the Large Binocular Telescope (LBT), near-infrared imaging data from the Canada France Hawaii Telescope WIRCam (CFHT/WIRCam), and Spitzer IRAC. Thanks to its dense multi-wavelength coverage, J1030 represents a legacy field for the study of large-scale structures around distant accreting supermassive black holes. Using a likelihood ratio analysis, we associate multi-band (r, z, J, and 4.5 μm) counterparts for 252 (98.4%) of the 256 Chandra sources, with an estimated reliability of 95%. Finally, we compute the cumulative number of sources in each X-ray band, finding that they are in general agreement with the results from the Chandra Deep Fields.

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Leaf Photosynthetic Capacity of Sunlit and Shaded Mature Leaves in a Deciduous Forest

Forests ◽

10.3390/f11030318 ◽

2020 ◽

Vol 11 (3) ◽

pp. 318

Author(s):

Guangman Song ◽

Quan Wang ◽

Jia Jin

Keyword(s):

Close Relationships ◽

Deciduous Forest ◽

Photosynthetic Capacity ◽

Leaf Gas Exchange ◽

Nitrogen Concentration ◽

Leaf Traits ◽

Leaf Nitrogen ◽

Leaf Mass Per Area ◽

Clear Understanding ◽

Equivalent Water Thickness

A clear understanding of the dynamics of photosynthetic capacity is crucial for accurate modeling of ecosystem carbon uptake. However, such dynamical information is hardly available and has dramatically impeded our understanding of carbon cycles. Although tremendous efforts have been made in coupling the dynamic information of photosynthetic capacity into models, using “proxies” rooted from the close relationships between photosynthetic capacity and other available leaf parameters remains the popular selection. Unfortunately, no consensus has yet been reached on such “proxies”, leading them only applicable to limited cases. In this study, we aim to identify if there are close relationships between the photosynthetic capacity (represented by the maximum carboxylation rate, Vcmax) and leaf traits for mature broadleaves within a cold temperature deciduous forest. This is based on a long-term in situ dataset including leaf chlorophyll content (Chl), leaf nitrogen concentration (Narea, Nmass), leaf carbon concentration (Carea, Cmass), equivalent water thickness (EWT), leaf mass per area (LMA), and leaf gas exchange measurements from which Vcmax was derived, for both sunlit and shaded leaves during leaf mature periods from 2014 to 2019. The results show that the Vcmax values of sunlit and shaded leaves were relatively stable during these periods, and no statistically significant interannual variations occurred (p > 0.05). However, this is not applicable to specific species. Path analysis revealed that Narea was the major contributor to Vcmax for sunlit leaves (0.502), while LMA had the greatest direct relationship with Vcmax for shaded leaves (0.625). The LMA has further been confirmed as a primary proxy if no leaf type information is available. These findings provide a promising way to better understand photosynthesis and to predict carbon and water cycles in temperate deciduous forests.

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The Fingerprint of a Galactic Nucleus

Proceedings of the International Astronomical Union ◽

10.1017/s1743921316011959 ◽

2016 ◽

Vol 11 (S322) ◽

pp. 257-258

Author(s):

Francisco Nogueras-Lara ◽

Rainer Schödel

Keyword(s):

Large Scale ◽

Near Infrared ◽

Angular Resolution ◽

Galactic Center ◽

Fold Increase ◽

Galactic Centre ◽

High Angular Resolution ◽

Imaging Data ◽

First Results ◽

Multi Wavelength

AbstractBecause of the unique observational challenges -extreme crowding and extinction- any existing large-scale near-infrared (NIR) imaging data on the Galactic Center (GC) are limited by either one, or a combination, of the following: saturation, lack of sensitivity, too low angular resolution, or lack of multi-wavelength coverage. To overcome this situation, we are currently carrying out a sensitive, 0.2” resolution JHK imaging survey of the Galactic Centre with HAWK-I/VLT. Thanks to holographic imaging, we achieve a similar resolution than with HST/WFC, but can cover also the long NIR, beyond 2 micrometers, which is essential to deal with extinction. Our survey is supported by an ESO Large Programme and will provide photometrically accurate (few percent uncertainty for H < 18 stars), high-angular resolution, NIR data for an area of several 1000 pc2, a more than ten-fold increase compared to the current state of affairs. Here we present an overview and first results.

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Relationships among leaf traits of Australian arid zone plants: alternative modes of thermal protection

Australian Journal of Botany ◽

10.1071/bt11284 ◽

2012 ◽

Vol 60 (6) ◽

pp. 471 ◽

Cited By ~ 14

Author(s):

Ellen M. Curtis ◽

Andrea Leigh ◽

Scott Rayburg

Keyword(s):

Water Content ◽

Structural Damage ◽

Near Infrared ◽

Thermal Protection ◽

Arid Zone ◽

Leaf Traits ◽

Leaf Mass Per Area ◽

Leaf Economics Spectrum ◽

Leaf Trait ◽

Leaf Mass

Despite the importance of leaf traits that protect against critically high leaf temperatures, relationships among such traits have not been investigated. Further, while some leaf trait relationships are well documented across biomes, little is known about such associations within a biome. This study investigated relationships between nine leaf traits that protect leaves against excessively high temperatures in 95 Australian arid zone species. Seven morphological traits were measured: leaf area, length, width, thickness, leaf mass per area, water content, and an inverse measure of pendulousness. Two spectral properties were measured: reflectance of visible and near-infrared radiation. Three key findings emerged: (1) leaf pendulousness increased with leaf size and leaf mass per area, the former relationship suggesting that pendulousness affords thermal protection when leaves are large; (2) leaf mass per area increased with thickness and decreased with water content, indicating alternative means for protection through increasing thermal mass; (3) spectral reflectance increased with leaf mass per area and thickness and decreased with water content. The consistent co-variation of thermal protective traits with leaf mass per area, a trait not usually associated with thermal protection, suggests that these traits fall along the leaf economics spectrum, with leaf longevity increasing through protection not only against structural damage but also against heat stress.

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Consistency of demographic trade-offs across tropical forests

10.22541/au.163253541.10680169/v1 ◽

2021 ◽

Author(s):

Stephan Kambach ◽

Richard Condit ◽

Salomón Aguilar ◽

Helge Bruelheide ◽

Sarayudh Bunyavejchewin ◽

...

Keyword(s):

Tropical Forest ◽

Tropical Forests ◽

Large Scale ◽

Negative Relationship ◽

Trade Off ◽

Growth And Survival ◽

Trade Offs ◽

Tree Communities ◽

Demographic Processes ◽

Tropical Forest Dynamics

All species must balance their allocation to growth, survival and recruitment. Among trees, evolution has resulted in different strategies of partitioning resources to these key demographic processes, i.e. demographic trade-offs. It is unclear whether the same demographic trade-offs structure tropical forests worldwide. Here, we used data from 13 large-scale and long-term tropical forest plots to estimate the principal trade-offs in growth, survival, recruitment, and tree stature at each site. For ten sites, two trade-offs appeared repeatedly. One trade-off showed a negative relationship between growth and survival, i.e. the well-known fast−slow continuum. The second trade-off distinguished between tall-statured species and species with high recruitment rates, i.e. a stature−recruitment trade-off. Thus, the fast-slow continuum and tree stature are two independent dimensions structuring most tropical tree communities. Our discovery of the consistency of demographic trade-offs and strategies across forest types in three continents substantially improves our ability to predict tropical forest dynamics worldwide.

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Phenology, seasonality and trait relationships in a New Zealand forest

10.26686/wgtn.17134760.v1 ◽

2021 ◽

Author(s):

◽

Sharada Paudel

Keyword(s):

New Zealand ◽

Leaf Traits ◽

Leaf Longevity ◽

Leaf Abscission ◽

Future Research ◽

Leaf Mass Per Area ◽

Fruit Traits ◽

Leaf Production ◽

Leaf Economic Spectrum ◽

The Relationship

<p>The phenologies of flowers, fruits and leaves can have profound implications for plant community structure and function. Despite this only a few studies have documented fruit and flower phenologies in New Zealand while there are even fewer studies on leaf production and abscission phenologies. To address this limitation, I measured phenological patterns in leaves, flowers and fruits in 12 common forest plant species in New Zealand over two years. All three phenologies showed significant and consistent seasonality with an increase in growth and reproduction around the onset of favourable climatic conditions; flowering peaked in early spring, leaf production peaked in mid-spring and fruit production peaked in mid-summer coincident with annual peaks in temperature and photoperiodicity. Leaf abscission, however, occurred in late autumn, coincident with the onset of less productive environmental conditions. I also investigated differences in leaf longevities and assessed how seasonal cycles in the timing of leaf production and leaf abscission times might interact with leaf mass per area (LMA) in determining leaf longevity. Leaf longevity was strongly associated with LMA but also with seasonal variation in climate. All 12 species produced leaves in spring and abscised leaves in autumn. Nevertheless, leaf longevity ranged from 6 months to 30 months among species, leading to several distinct leaf longevity categories (i.e. 6-7 months, 15-18 months and 27-30 months). Finally, I examined the relationship of leaf traits with flower and fruit traits and their relation to the global leaf economic spectrum (LES) that describes multivariate correlations between a combinations of key leaf traits. The results resonated with the patterns of leaf economic spectrum for New Zealand species and provided evidence for significant correlations between leaf and fruit traits, indicating that plants with long lived leaves and higher LMA produce fruits that take more time to develop, stay on the plant longer and have larger seed size. This study contributed to bridging the gap in our understanding of the relationship between vegetative and reproductive traits, it has increased our understanding of phenological patterns in New Zealand forests, and when viewed with earlier phenological studies, provides a first step towards understanding how New Zealand forest might respond to global climate change. In addition, the research illustrates how seasonality in climate can constrain the life times of leaves. In the context of global trait research culminating into the whole plant economics spectrum, this study provides clear evidence of leaf and fruit phenological and morphological trait associations. It helps to further our understanding of phenology, seasonality and plant trait relationships for some common tree species in New Zealand and presents some novel findings that provide a basis for future research.</p>

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379 ASAS-EAAP Talk: Precision Phenotyping using Infrared Spectroscopy to Improve the Quality of Animal Products

Journal of Animal Science ◽

10.1093/jas/skaa278.258 ◽

2020 ◽

Vol 98 (Supplement_4) ◽

pp. 140-140

Author(s):

Alessio Cecchinato ◽

Sara Pegolo ◽

Giovanni Bittante

Keyword(s):

Gold Standard ◽

Large Scale ◽

Near Infrared ◽

Prediction Models ◽

Quality Parameters ◽

Least Squares Regression ◽

Animal Products ◽

Precision Phenotyping ◽

Definition Of

Abstract There is an ever-growing interest in research oriented towards the improvement of quality of animal products. In this context, one major operational bottleneck is the possibility to collect quality indicators over the meat and dairy chains and for selective breeding purposes. The use of near-infrared (NIR) and the Fourier-transformed infrared (FTIR) spectroscopy techniques have been proven to be powerful precision phenotyping tools for high-throughput meat and milk quality assessment. Such technologies allow scoring large number of animals and/or derived-products for novel (predicted) phenotypes and indicator traits to set-up potential new payment systems and boost the genetic improvement. One important step in the use of NIR and FTIR tools is the definition of the “gold standard” as the infrared-based predictions could act only as indicators traits. Indeed, the definition of a robust calibration set, the assessment of repeatability and reproducibility of the reference (i.e., gold standard) as well as the detection of random and systematic errors are crucial steps. Once the reference phenotype has been defined, different statistical methodologies could be applied to infrared spectra data. For instance, the partial least squares regression (PLS) is a multivariate regression method commonly used to build up prediction models using NIR and FTIR spectra data. However, the implementation of advanced statistical approaches, such as Bayesian approaches and machine learning methods, might allow us to achieve more robust and accurate predictions. In this talk, we will describe and discuss some of the challenges and potentials of NIR and FTIR tools for large-scale precision phenotyping. Some examples include the use of NIR and Visible-NIR (Vis-NIR) for assessing meat quality parameters (also using portable instruments able to collect spectra directly from the muscle surface at the slaughterhouse) and the use of FTIR for predicting several traits related to fine milk composition and technological traits in dairy cattle.

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Overwintering evergreen oaks reverse typical relationships between leaf traits in a species spectrum

Royal Society Open Science ◽

10.1098/rsos.160276 ◽

2016 ◽

Vol 3 (7) ◽

pp. 160276 ◽

Cited By ~ 7

Author(s):

Hisanori Harayama ◽

Atsushi Ishida ◽

Jin Yoshimura

Keyword(s):

Leaf Traits ◽

Global Scale ◽

Carbon Gain ◽

Leaf Mass Per Area ◽

Nitrogen Allocation ◽

Leaf Economics Spectrum ◽

Trade Offs ◽

Almost All ◽

Leaf Economics ◽

Evergreen Oaks

The leaf economics spectrum has given us a fundamental understanding of the species variations in leaf variables. Across plant species, tight correlations among leaf mass per area (LMA), mass-based nitrogen ( N m ) and photosynthetic rate ( A m ) and leaf lifespan have been well known as trade-offs in leaf carbon economy. However, the regional or biome-level correlations may not be necessary to correspond with the global-scale analysis. Here, we show that almost all leaf variables in overwintering evergreen oaks in Japan were relatively well included within the evergreen-broadleaved trees in worldwide temperate forests, but N m was more consistent with that in deciduous broadleaved trees. Contrary to the universal correlations, the correlation between A m and N m among the evergreen oaks was negative and the correlation between A m and LMA disappeared. The unique performance was due to specific nitrogen allocation within leaves, i.e. the evergreen oaks with later leaf maturation had lower N m but higher nitrogen allocation to photosynthetic enzymes within leaves, to enhance carbon gain against the delayed leaf maturation and the shortened photosynthetic period due to cold winters. Our data demonstrate that correlations between leaf variables in a local scale are occasionally different from averaged global-scale datasets, because of the constraints in each biome.

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Using near Infrared Spectroscopy for Predicting Process Conditions. A Laboratory Study from Pulp Production

Journal of Near Infrared Spectroscopy ◽

10.1255/jnirs.557 ◽

2005 ◽

Vol 13 (5) ◽

pp. 265-276 ◽

Cited By ~ 3

Author(s):

Heidi Henriksen ◽

Tormod Næs ◽

Vegard Segtnan ◽

Are Aastveit

Keyword(s):

Data Storage ◽

Large Scale ◽

Near Infrared ◽

Model Development ◽

Nir Spectroscopy ◽

Principal Component ◽

Process Conditions ◽

Multivariate Techniques ◽

Least Squares Regression ◽

Statistical Process

Most industries face a growing challenge concerning data handling due to the large data storage capacity available today. In many cases, it is difficult to navigate through these amounts of data in search of relevant information. An important tool in this context is statistical process control (SPC), which enables the discovery of possible process drift or other problems as early as possible. In this work the potential of using near infrared (NIR) spectroscopy as a multifunction tool for SPC in the context of process monitoring has been investigated. Both principal component analysis (PCA) and partial least squares regression (PLS) are tested as tools for extracting useful information from NIR spectra. The two methods have been compared based on interpretation of score plots and explained variance. We have also tested classification tools for prediction of classes and various types of validation, since these data came from designed experiments. It has been demonstrated that PLS is a useful tool both for forward and backward predictions. Another topic considered is discovery of instrument drift and outlier detection. It has been demonstrated that PLS is a useful tool in both contexts. The robustness of PLS predictions has been investigated and it was found that PLS score plots can reveal useful information early in the process. This study was a feasibility study and the models can not be used directly in any large scale installations. This work has, however, demonstrated the usefulness of multivariate techniques in such processes and found a good basis for further model development.

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