Invasive Species in the Delta: Segmentation and Classification of Water Hyacinth and Primrose

Because of its great beauty, Eichhornia crassipes (Water Hyacinth), originally from South America, has been introduced to 4 continents. Furthermore, because of its genetic make-up, high versatility and resiliency, this plant has become a frightening invasive, affecting boating and shipping, farming, water quality and fishermen livelihood wherever it thrives. However, Water Hyacinth (WH) is only 1 of over 84 invasives in the California Delta, which is where we focused our study. We took photographs along the Delta in treated and non-treated areas, and used an ENVI segmentation tool to find the best parameters for discriminating Water Hyacinth and Primrose. Once those parameters were found, we created a set of rules that would convey the percent cover of each invasive and dead plant material inside every photograph. This would help to determine the effectiveness of 2,4-D herbicide treatment on the invasives. The rules we created where based on the average RGB band ratios, and minimum and maximum RGB values of Water Hyacinth, Primrose, detritus, and water. We found that the herbicidal treatment was indeed effective to reduce invasive coverage, and that overall there were more Primrose than Water Hyacinth. The best segmentation parameters we found still did not accurately separate the two plant species within a given photo graph, but performed well on photographs with only one species. This ultimately affected the percent coverage found, but we conclude that the percentages are still accurate. A literature review was also conducted by compiling information from previous research articles that were written in regards to Water Hyacinth, and implications were stated to influence future research. Furthermore, a map we created of Water Hyacinth in the U.S allowed us to conclude that this invasive will most likely spread to the Central U.S region if its growth is not impeded

Using Remote Sensing Mapping and Growth Response to Environmental Variability to Aide Aquatic Invasive Plant Management

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass density), direct operations, and assess management impacts on plant communities. Archived satellite records enable review of results following previous climate and management events and aide in developing long-term strategies. Examples of remote sensing aiding effectiveness of aquatic weed management will be discussed as well as areas for potential technological improvement. Modeling at local and watershed scales using the SWAT modeling tool provides insight into land-use effects on water quality (described by Zhang in same Symposium). Controlled environment growth studies have been conducted to quantify the growth response of invasive aquatic plants to water quality and other environmental factors. Environmental variability occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Response time for invasive species response are examined at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature (air and water), nitrogen, phosphorus, and light effects. These provide response parameters for plant growth models in response to the variation and interact with management and economic models associated with aquatic weed management. Plant growth models are to be informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and phenology. Initial utilization of remote sensing tools developed for mapping of aquatic invasive plants improved operational efficiency in management practices. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta

Changes in the Carbon Cycle of Amazon Ecosystems During the 2010 Drought

Satellite remote sensing was combined with the NASA-CASA carbon cycle simulation model to evaluate the impact of the 2010 drought (July through September) throughout tropical South America. Results indicated that net primary production (NPP) in Amazon forest areas declined by an average of 7% in 2010 compared to 2008. This represented a loss of vegetation CO2 uptake and potential Amazon rainforest growth of nearly 0.5 Pg C in 2010. The largest overall decline in ecosystem carbon gains by land cover type was predicted for closed broadleaf forest areas of the Amazon River basin, including a large fraction of regularly flooded forest areas. Model results support the hypothesis that soil and dead wood carbon decomposition fluxes of CO2 to the atmosphere were elevated during the drought period of 2010 in periodically flooded forest areas, compared to forests outside the main river floodplains

Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling

<p>Abstract</p> <p>Background</p> <p>A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO₂is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades.</p> <p>Results</p> <p>Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr^-1(1 Tg = 10¹²g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO₂on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr^-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO₂to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr^-1for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas.</p> <p>Conclusions</p> <p>Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape.</p

Vegetation classification of Coffea on Hawaii Island using WorldView-2 satellite imagery

Coffee is an important crop in tropical regions of the world; about 125 million people depend on coffee agriculture for their livelihoods. Understanding the spatial extent of coffee fields is useful for management and control of coffee pests such as Hypothenemus hampei and other pests that use coffee fruit as a host for immature stages such as the Mediterranean fruit fly, for economic planning, and for following changes in coffee agroecosystems over time. We present two methods for detecting Coffea arabica fields using remote sensing and geospatial technologies on WorldView-2 high-resolution spectral data of the Kona region of Hawaii Island. The first method, a pixel-based method using a maximum likelihood algorithm, attained 72% producer accuracy and 69% user accuracy (68% overall accuracy) based on analysis of 104 ground truth testing polygons. The second method, an object-based image analysis (OBIA) method, considered both spectral and textural information and improved accuracy, resulting in 76% producer accuracy and 94% user accuracy (81% overall accuracy) for the same testing areas. We conclude that the OBIA method is useful for detecting coffee fields grown in the open and use it to estimate the distribution of about 1050 hectares under coffee agriculture in the Kona region in 2012

Development of the Ames Global Hyperspectral Synthetic Data Set: Surface Bidirectional Reflectance Distribution Function

This study introduces the Ames Global Hyperspectral Synthetic Data set (AGHSD), in particular the surface bidirectional reflectance distribution function (BRDF) product, to support the NASA Surface Biology and Geology (SBG) mission development. The data set is generated based on the corresponding multispectral BRDF products from NASA\u27s MODIS satellite sensor. Based on theories of radiative transfer in vegetation canopies, we derive a simple but robust relationship that indicates that the hyperspectral surface BRDF can be accurately approximated as a weighted sum of the soil surface reflectance, the leaf single albedo, and the canopy scattering coefficient, where the weights or coefficients are spectrally invariant and thus readily estimated from the multispectral MODIS products. We validate the algorithm with simulations by a Monte Carlo Ray Tracing model and find the results highly consistent with the theoretic derivation. Using reflectance spectra of soil and vegetation derived from existing spectral libraries, we apply the algorithm to generate the AGHSD BRDF product at 1 km and 8-day resolutions for the year of 2019. The data set is biogeochemically and biogeophysically coherent and consistent, and serves the goal to support the SBG community in developing sciences and applications for the future global imaging spectroscopy mission

Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients

Baricitinib, is an oral Janus kinase (JAK)1/JAK2 inhibitor approved for the treatment of rheumatoid arthritis (RA) that was independently predicted, using artificial intelligence (AI)-algorithms, to be useful for COVID-19 infection via a proposed anti-cytokine effects and as an inhibitor of host cell viral propagation. We evaluated the in vitro pharmacology of baricitinib across relevant leukocyte subpopulations coupled to its in vivo pharmacokinetics and showed it inhibited signaling of cytokines implicated in COVID-19 infection. We validated the AI-predicted biochemical inhibitory effects of baricitinib on human numb-associated kinase (hNAK) members measuring nanomolar affinities for AAK1, BIKE, and GAK. Inhibition of NAKs led to reduced viral infectivity with baricitinib using human primary liver spheroids. These effects occurred at exposure levels seen clinically. In a case series of patients with bilateral COVID-19 pneumonia, baricitinib treatment was associated with clinical and radiologic recovery, a rapid decline in SARS-CoV-2 viral load, inflammatory markers, and IL-6 levels. Collectively, these data support further evaluation of the anti-cytokine and anti-viral activity of baricitinib and supports its assessment in randomized trials in hospitalized COVID-19 patients

Net primary productivity of forest stands in New Hampshire estimated from Landsat and MODIS satellite data

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Rheumatoid arthritis - treatment: 180. Utility of Body Weight Classified Low-Dose Leflunomide in Japanese Rheumatoid Arthritis

Background: In Japan, more than 20 rheumatoid arthritis (RA) patients died of interstitial pneumonia (IP) caused by leflunomide (LEF) were reported, but many of them were considered as the victims of opportunistic infection currently. In this paper, efficacy and safety of low-dose LEF classified by body weight (BW) were studied. Methods: Fifty-nine RA patients were started to administrate LEF from July 2007 to July 2009. Among them, 25 patients were excluded because of the combination with tacrolimus, and medication modification within 3 months before LEF. Remaining 34 RA patients administered 20 to 50 mg/week of LEF were followed up for 1 year and enrolled in this study. Dose of LEF was classified by BW (50 mg/week for over 50 kg, 40 mg/week for 40 to 50 kg and 20 to 30 mg/week for under 40 kg). The average age and RA duration of enrolled patients were 55.5 years old and 10.2 years. Prednisolone (PSL), methotrexate (MTX) and etanercept were used in 23, 28 and 2 patients, respectively. In case of insufficient response or adverse effect, dosage change or discontinuance of LEF were considered. Failure was defined as dosages up of PSL and MTX, or dosages down or discontinuance of LEF. Last observation carried forward method was used for the evaluation of failed patients at 1 year. Results: At 1 year after LEF start, good/ moderate/ no response assessed by the European League Against Rheumatism (EULAR) response criteria using Disease Activity Score, including a 28-joint count (DAS28)-C reactive protein (CRP) were showed in 14/ 10/ 10 patients, respectively. The dosage changes of LEF at 1 year were dosage up: 10, same dosage: 5, dosage down: 8 and discontinuance: 11 patients. The survival rate of patients in this study was 23.5% (24 patients failed) but actual LEF continuous rate was 67.6% (11 patients discontinued) at 1 year. The major reason of failure was liver dysfunction, and pneumocystis pneumonia was occurred in 1 patient resulted in full recovery. One patient died of sepsis caused by decubitus ulcer infection. DAS28-CRP score was decreased from 3.9 to 2.7 significantly. Although CRP was decreased from 1.50 to 0.93 mg/dl, it wasn't significant. Matrix metalloproteinase (MMP)-3 was decreased from 220.0 to 174.2 ng/ml significantly. Glutamate pyruvate transaminase (GPT) was increased from 19 to 35 U/l and number of leukocyte was decreased from 7832 to 6271 significantly. DAS28-CRP, CRP, and MMP-3 were improved significantly with MTX, although they weren't without MTX. Increase of GPT and leukopenia were seen significantly with MTX, although they weren't without MTX. Conclusions: It was reported that the risks of IP caused by LEF in Japanese RA patients were past IP history, loading dose administration and low BW. Addition of low-dose LEF is a potent safe alternative for the patients showing unsatisfactory response to current medicines, but need to pay attention for liver function and infection caused by leukopenia, especially with MTX. Disclosure statement: The authors have declared no conflicts of interes