Leaf-level coordination principles propagate to the ecosystem scale.

Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories - the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis - are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production.

Sun-induced fluorescence in the far-red region (SIF) is increasingly used as a remote and proximal-sensing tool capable of tracking vegetation gross primary production (GPP). However, the use of SIF to probe changes in GPP is challenged during extreme climatic events, such as heatwaves. Here, we examined how the 2018 European heatwave (HW) affected the GPP-SIF relationship in evergreen broadleaved trees with a relatively invariant canopy structure. To do so, we combined canopy-scale SIF measurements, GPP estimated from an eddy covariance tower, and active pulse amplitude modulation fluorescence. The HW caused an inversion of the photosynthesis-fluorescence relationship at both the canopy and leaf scales. The highly nonlinear relationship was strongly shaped by nonphotochemical quenching (NPQ), that is, a dissipation mechanism to protect from the adverse effects of high light intensity. During the extreme heat stress, plants experienced a saturation of NPQ, causing a change in the allocation of energy dissipation pathways towards SIF. Our results show the complex modulation of the NPQ-SIF-GPP relationship at an extreme level of heat stress, which is not completely represented in state-of-the-art coupled radiative transfer and photosynthesis models.

The three major axes of terrestrial ecosystem function.

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

On the importance of root traits in seedlings of tropical tree species.

Plant biomass allocation may be optimized to acquire and conserve resources. How trade-offs in the allocation of tropical tree seedlings depend on different stressors remains poorly understood. Here we test whether above- and below-ground traits of tropical tree seedlings could explain observed occurrence along gradients of resources (light, water) and defoliation (fire, herbivory). We grew 24 tree species occurring in five African vegetation types, varying from dry savanna to moist forest, in a glasshouse for 6 months, and measured traits associated with biomass allocation. Classification based on above-ground traits resulted in clusters representing savanna and forest species, with low and high shoot investment, respectively. Classification based on root traits resulted in four clusters representing dry savanna, humid savanna, dry forest and moist forest, characterized by a deep mean rooting depth, root starch investment, high specific root length in deeper soil layers, and high specific root length in the top soil layer, respectively. In conclusion, tree seedlings in this study show root trait syndromes, which vary along gradients of resources and defoliation: seedlings from dry areas invest in deep roots, seedlings from shaded environments optimize shoot investment, and seedlings experiencing frequent defoliation store resources in the roots.

Assessment of CNN-Based Methods for Individual Tree Detection on Images Captured by RGB Cameras Attached to UAVs.

Detection and classification of tree species from remote sensing data were performed using mainly multispectral and hyperspectral images and Light Detection And Ranging (LiDAR) data. Despite the comparatively lower cost and higher spatial resolution, few studies focused on images captured by Red-Green-Blue (RGB) sensors. Besides, the recent years have witnessed an impressive progress of deep learning methods for object detection. Motivated by this scenario, we proposed and evaluated the usage of Convolutional Neural Network (CNN)-based methods combined with Unmanned Aerial Vehicle (UAV) high spatial resolution RGB imagery for the detection of law protected tree species. Three state-of-the-art object detection methods were evaluated: Faster Region-based Convolutional Neural Network (Faster R-CNN), YOLOv3 and RetinaNet. A dataset was built to assess the selected methods, comprising 392 RBG images captured from August 2018 to February 2019, over a forested urban area in midwest Brazil. The target object is an important tree species threatened by extinction known as Dipteryx alata Vogel (Fabaceae). The experimental analysis delivered average precision around 92% with an associated processing times below 30 miliseconds.

Delta-6-desaturase activity and arachidonic acid synthesis are increased in human breast cancer tissue.

Omega-6 (n-6) arachidonic acid (AA) and its pro-inflammatory metabolites, including prostaglandin E2 (PGE(2)), are known to promote tumorigenesis. Delta-6 desaturase (D6D) is the rate-limiting enzyme for converting n-6 linoleic acid (LA) to AA. Our objective was to determine if AA synthesis, specifically D6D activity, and PGE(2) levels are increased in cancerous breast tissue, and whether these variables differ between estrogen receptor positive (ER+) and negative (ER-) breast cancers. Gas chromatography was performed on surgical breast tissue samples collected from 69 women with breast cancer. Fifty-four had ER+ breast cancer, and 15 had ER- breast cancer. Liquid chromatography-mass spectrometry was used to determine PGE(2) levels. Lipid analysis revealed higher levels of LA metabolites (C18:3 n-6, C20:3 n-6, and AA) in cancerous tissue than in adjacent noncancerous tissue (P < 0.01). The ratio of LA metabolites to LA, a measure of D6D activity, was increased in cancerous tissue, suggesting greater conversion of LA to AA (P < 0.001), and was higher in ER- than in ER+ patients, indicating genotype-related trends. Similarly, PGE(2) levels were increased in cancerous tissue, particularly in ER- patients. The results showed that the endogenous AA synthetic pathway, D6D activity, and PGE(2) levels are increased in breast tumors, particularly those of the ER- genotype. These findings suggest that the AA synthetic pathway and the D6D enzyme in particular may be involved in the pathogenesis of breast cancer. The development of drugs and nutritional interventions to alter this pathway may provide new strategies for breast cancer prevention and treatment.

Acute respiratory distress syndrome secondary to inhalation of chlorine gas in sheep.

BACKGROUND: Toxic industrial chemicals (TICs) are potential terrorist weapons. Several TICs, such as chlorine, act primarily on the respiratory tract, but knowledge of the pathophysiology and treatment of these injuries is inadequate. This study aims to characterize the acute respiratory distress syndrome (ARDS) caused by chlorine gas (Cl2) inhalation in a large-animal model. METHODS: Anesthetized female sheep were ventilated with 300 L of a Cl2/air/oxygen mixture for 30 minutes. In phase 1 (n = 35), doses were 0 ppm (Group 1, n = 6); 120 ppm (Group 2, n = 6); 240 to 350 ppm (Group 3, n = 11); and 400 to 500 ppm (Group 4, n = 12). In phase 2 (n = 17), doses were 0 ppm (Group 5, n = 5); 60 ppm (Group 6, n = 5); and 90 ppm (Group 7, n = 7), and the multiple inert gas elimination technique (MIGET) was used to characterize the etiology of hypoxemia. Computed tomography (CT) scans were performed daily for all animals. RESULTS: In Phase 1, lung function was well maintained in Group 1; Cl2 caused immediate and sustained acute lung injury (PaO2-to-FiO2 ratio, PFR<3.0) in Group 2 and ARDS (PFR<2.0) in Groups 3 and 4. All animals in Groups 1 and 2 survived 96 hours. Kaplan-Meier analysis showed dose-related differences in survival (log-rank test, p < 0.0001). Logistic regression identified 280 ppm as the lethal dose 50%. CT and histopathology demonstrated lesions of both small airways and alveoli. In Phase 2, MIGET showed diversion of blood flow from normal to true-shunt lung compartments and, transiently, to poorly ventilated compartments. CONCLUSIONS: Cl2 causes severe, dose-related lung injury, with features seen in both smoke inhalation and in ARDS secondary to systemic disease. This model will be used to test new therapeutic modalities.

Hyperspectral imaging: a new approach to the diagnosis of hemorrhagic shock.

BACKGROUND: Skin color changes and mottling are frequently described signs of hemorrhagic shock (HEM). Based on this, we developed a noninvasive, noncontact hyperspectral imaging system (HSI), which quantifies and depicts the surface tissue saturation of oxygen (SHSIO2) for each pixel in a region of interest (ROI). Our purpose was to assess HSI in a porcine HEM model. We hypothesized that HEM would cause decreases in SHSIO2 of the skin. METHODS: The HyperMed HSI system employs a spectral separator to vary the wavelength of light admitted to a digital camera. During image acquisition, a "hypercube" of images, each at a separate wavelength, is generated (at 5-nm intervals, from 500 to 600 nm). Then, the visible light spectrum for each pixel in the hypercube is compared by linear regression to standard spectra for oxyhemoglobin (OxyHb) and deoxyhemoglobin (DeoxyHb). The resulting fit coefficients for OxyHb and DeoxyHb are used to calculate SHSIO2 values for each pixel in the ROI. The mean values for OxyHb, DeoxyHb, and SHSIO2 across the ROI are calculated. Grayscale SHSIO2 pictures of the ROI are also generated, in which the brightness of each pixel is proportional to its value. Seventeen pigs, 36.4 +/- 0.11 kg, underwent standard preparation, and were maintained on ketamine and isoflurane. Normothermia was maintained (37 degrees C to 39 degrees C). The hemorrhage group (HEM, n = 9) underwent three blood withdrawals, each 10 mL/kg, with 15 minutes between withdrawals. After the third withdrawal, animals were resuscitated with lactated Ringer's and then shed blood. The control group (CTRL, n = 8) received intravenous fluids at 100 mL/h. HSI images were obtained of the inner hindlimb throughout. RESULTS: All HEM animals showed linear decreases in both mean SHSIO2 and OxyHb values with blood loss, which were reversed by resuscitation. These changes were evident on the grayscale SHSIO2 pictures, but not to the naked eye, and paralleled those of invasively obtained arterial base excess and mixed venous oxygen saturation. CONCLUSIONS: HSI is a promising noninvasive and noncontact tool for quantifying changes in skin oxygenation during HEM and resuscitation.