A Multi-Scale Assessment of Solar-Induced Chlorophyll Fluorescence and Its Relation to Northern Hemisphere Forest Productivity

Photosynthesis, or gross primary productivity (GPP), plays a critical role in the global carbon cycle, since it is the sole pathway for carbon fixation by the biosphere. Quantifying GPP across multiple spatial scales is needed to improve our understanding of current and future behavior of biosphere-atmosphere carbon exchange and subsequent feedbacks on the climate system. Remote sensing represents one method to observe vegetation properties and processes, and solar-induced chlorophyll fluorescence (SIF), a light signal originating from leaves, has been shown to be proportional to GPP on diurnal and seasonal timescales. Recently, new techniques to retrieve SIF from satellite observations have provided an unprecedented opportunity to study GPP on a global scale. The relationship between SIF and GPP, however, is subject to significant uncertainty as it is influenced by a number of ecosystem traits (e.g. plant species, canopy structure, leaf age). In this dissertation, I evaluate SIF signals and their relation to GPP over Northern Hemisphere forest ecosystems. First, I compare climate-driven variations in satellite-based SIF to both longstanding satellite vegetation indices derived from reflected sunlight and tower-based estimates of GPP. Even when aggregated regionally, interannual variability (IAV) of SIF is found to be subject to low signal-to-noise performance, particularly during summer. However, through a statistical analysis, I show that increases in springtime temperature driven by warmer temperatures are offset by drier, less productive conditions later in the growing season. Summer productivity, however, is more strongly correlated with moisture than with temperature, suggesting that moisture exerts a greater influence on growing season-integrated signals. While these results demonstrate that satellite observations can be used to reveal meaningful carbon-climate interactions, they also show that currently available satellite observations of SIF do not allow for robust studies of IAV at scales comparable to surface-based observations. To investigate how SIF signals are related to ecosystem function at a local scale, I built and deployed a PhotoSpec spectrometer system to the AmeriFlux tower at the University of Michigan Biological Station (US-UMB) above a temperate deciduous forest. These observations show a strong correlation between SIF and GPP at diurnal and seasonal timescales, but SIF is more closely tied to solar radiation and exhibits a delayed response to water stress-induced losses in summer GPP. This decoupling during drought highlights the challenges in using SIF to detect changes in summertime productivity. However, an increased ratio between red and far-red SIF during drought indicates that the combination of SIF at multiple wavelengths may improve the detection of water stress. Lastly, I explore diurnal and directional aspects of the SIF signal. Observations of SIF are sensitive to sun-sensor geometry, with smaller incident angles (between solar and viewing angles) leading to stronger signals. However, afternoon SIF is typically lower than morning values at equivalent light levels due to ecosystem downregulation, which obfuscates angular dependencies in the afternoon. While satellite observations typically rely on a clear-sky sunlight proxy to scale instantaneous observations of SIF to daily values, these results demonstrate the need to account for sounding geometry and diurnal hysteresis in SIF signals in order to advance the interpretation of satellite observations. Overall, my results provide a multiscale assessment of SIF over Northern Hemisphere forests and emphasize that careful attention must be given to the spatial and temporal scales at which SIF can be used to make inferences about GPP.PHDAtmospheric, Oceanic & Space ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168011/1/zbutterf_1.pd

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Interannual and Seasonal Drivers of Carbon Cycle Variability Represented by the Community Earth System Model (CESM2)

Earth system models are intended to make long- term projections, but they can be evaluated at interannual and seasonal time scales. Although the Community Earth System Model (CESM2) showed improvements in a number of terrestrial carbon cycle benchmarks, relative to its predecessor, our analysis suggests that the interannual variability (IAV) in net terrestrial carbon fluxes did not show similar improvements. The model simulated low IAV of net ecosystem production (NEP), resulting in a weaker than observed sensitivity of the carbon cycle to climate variability. Low IAV in net fluxes likely resulted from low variability in gross primary productivity (GPP)- especially in the tropics- and a high covariation between GPP and ecosystem respiration. Although lower than observed, the IAV of NEP had significant climate sensitivities, with positive NEP anomalies associated with warmer and drier conditions in high latitudes, and with wetter and cooler conditions in mid and low latitudes. We identified two dominant modes of seasonal variability in carbon cycle flux anomalies in our fully coupled CESM2 simulations that are characterized by seasonal amplification and redistribution of ecosystem fluxes. Seasonal amplification of net and gross carbon fluxes showed climate sensitivities mirroring those of annual fluxes. Seasonal redistribution of carbon fluxes is initiated by springtime temperature anomalies, but subsequently negative feedbacks in soil moisture during the summer and fall result in net annual carbon losses from land. These modes of variability are also seen in satellite proxies of GPP, suggesting that CESM2 appropriately represents regional sensitivities of photosynthesis to climate variability on seasonal time scales.Plain Language SummaryEarth system models that are intended to make climate change projections also represent the global exchange of carbon dioxide (CO2) between the atmosphere, oceans, and land. As such, the growth rate and variability of CO2 concentrations in the atmosphere provide a robust measurement to evaluate models. We looked at the interannual variability (IAV) of terrestrial carbon fluxes and their sensitivity to variations in temperature and water that were simulated by the Community Earth System Model and compared them to observations. We found that the model underestimates the IAV of net terrestrial carbon fluxes, especially in the tropics. We also identified two modes of variability that correspond to an increase in summer land carbon uptake (amplification) and a change in the seasonal timing (redistribution) of land carbon fluxes. Notably, seasonal redistribution was initialized by warmer springs that increased early- season productivity, but subsequent water limitations in the summer and fall resulted in lower- than- average productivity over the growing season and net annual C losses to the atmosphere. Similar patterns of seasonal amplification and redistribution are seen in satellite observations of photosynthesis, suggesting that the model is realistically simulating characteristics of terrestrial ecosystems necessary for capturing carbon cycle- climate feedbacks.Key PointsSimulated net carbon fluxes show low interannual variability because of low tropical variability and high correlation in component fluxesSeasonal amplification and redistribution of fluxes characterize dominant modes of carbon cycle variability, consistent with observationsSeasonal redistribution is characterized by warm springs, dry summers, and can result in a net carbon loss from landPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/170288/1/2021GB007034-sup-0001-Supporting_Information_SI-S01.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/170288/2/gbc21163_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/170288/3/gbc21163.pd

Line-of-sight pursuit in strictly sweepable polygons

1 online resource (PDF, 36 pages, includes illustrations