South Dakota State University

Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.

Abstract This paper discusses the advantages and disadvantages of the different methods that separate net ecosystem exchange (NEE) into its major components, gross ecosystem carbon uptake (GEP) and ecosystem respiration ( R eco ). In particular, we analyse the effect of the extrapolation of night‐time values of ecosystem respiration into the daytime; this is usually done with a temperature response function that is derived from long‐term data sets. For this analysis, we used 16 one‐year‐long data sets of carbon dioxide exchange measurements from European and US‐American eddy covariance networks. These sites span from the boreal to Mediterranean climates, and include deciduous and evergreen forest, scrubland and crop ecosystems. We show that the temperature sensitivity of R eco , derived from long‐term (annual) data sets, does not reflect the short‐term temperature sensitivity that is effective when extrapolating from night‐ to daytime. Specifically, in summer active ecosystems the long‐term temperature sensitivity exceeds the short‐term sensitivity. Thus, in those ecosystems, the application of a long‐term temperature sensitivity to the extrapolation of respiration from night to day leads to a systematic overestimation of ecosystem respiration from half‐hourly to annual time‐scales, which can reach >25% for an annual budget and which consequently affects estimates of GEP. Conversely, in summer passive (Mediterranean) ecosystems, the long‐term temperature sensitivity is lower than the short‐term temperature sensitivity resulting in underestimation of annual sums of respiration. We introduce a new generic algorithm that derives a short‐term temperature sensitivity of R eco from eddy covariance data that applies this to the extrapolation from night‐ to daytime, and that further performs a filling of data gaps that exploits both, the covariance between fluxes and meteorological drivers and the temporal structure of the fluxes. While this algorithm should give less biased estimates of GEP and R eco , we discuss the remaining biases and recommend that eddy covariance measurements are still backed by ancillary flux measurements that can reduce the uncertainties inherent in the eddy covariance data.

An annotated reference sequence representing the hexaploid bread wheat genome in 21 pseudomolecules has been analyzed to identify the distribution and genomic context of coding and noncoding elements across the A, B, and D subgenomes. With an estimated coverage of 94% of the genome and containing 107,891 high-confidence gene models, this assembly enabled the discovery of tissue- and developmental stage-related coexpression networks by providing a transcriptome atlas representing major stages of wheat development. Dynamics of complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. This community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.

Fire is a worldwide phenomenon that appears in the geological record soon after the appearance of terrestrial plants. Fire influences global ecosystem patterns and processes, including vegetation distribution and structure, the carbon cycle, and climate. Although humans and fire have always coexisted, our capacity to manage fire remains imperfect and may become more difficult in the future as climate change alters fire regimes. This risk is difficult to assess, however, because fires are still poorly represented in global models. Here, we discuss some of the most important issues involved in developing a better understanding of the role of fire in the Earth system.

Landsat 8, a NASA and USGS collaboration, acquires global moderate-resolution measurements of the Earth's terrestrial and polar regions in the visible, near-infrared, short wave, and thermal infrared. Landsat 8 extends the remarkable 40 year Landsat record and has enhanced capabilities including new spectral bands in the blue and cirrus cloud-detection portion of the spectrum, two thermal bands, improved sensor signal-to-noise performance and associated improvements in radiometric resolution, and an improved duty cycle that allows collection of a significantly greater number of images per day. This paper introduces the current (2012–2017) Landsat Science Team's efforts to establish an initial understanding of Landsat 8 capabilities and the steps ahead in support of priorities identified by the team. Preliminary evaluation of Landsat 8 capabilities and identification of new science and applications opportunities are described with respect to calibration and radiometric characterization; surface reflectance; surface albedo; surface temperature, evapotranspiration and drought; agriculture; land cover, condition, disturbance and change; fresh and coastal water; and snow and ice. Insights into the development of derived ‘higher-level’ Landsat products are provided in recognition of the growing need for consistently processed, moderate spatial resolution, large area, long-term terrestrial data records for resource management and for climate and global change studies. The paper concludes with future prospects, emphasizing the opportunities for land imaging constellations by combining Landsat data with data collected from other international sensing systems, and consideration of successor Landsat mission requirements.

Climate strongly influences global wildfire activity, and recent wildfire surges may signal fire weather-induced pyrogeographic shifts. Here we use three daily global climate data sets and three fire danger indices to develop a simple annual metric of fire weather season length, and map spatio-temporal trends from 1979 to 2013. We show that fire weather seasons have lengthened across 29.6 million km(2) (25.3%) of the Earth's vegetated surface, resulting in an 18.7% increase in global mean fire weather season length. We also show a doubling (108.1% increase) of global burnable area affected by long fire weather seasons (>1.0 σ above the historical mean) and an increased global frequency of long fire weather seasons across 62.4 million km(2) (53.4%) during the second half of the study period. If these fire weather changes are coupled with ignition sources and available fuel, they could markedly impact global ecosystems, societies, economies and climate.

Plants and their associated fungi reward partners that offer the best resources to sustain mutualism in complex systems.

BACKGROUND: RNA-seq is widely used for transcriptomic profiling, but the bioinformatics analysis of resultant data can be time-consuming and challenging, especially for biologists. We aim to streamline the bioinformatic analyses of gene-level data by developing a user-friendly, interactive web application for exploratory data analysis, differential expression, and pathway analysis. RESULTS: iDEP (integrated Differential Expression and Pathway analysis) seamlessly connects 63 R/Bioconductor packages, 2 web services, and comprehensive annotation and pathway databases for 220 plant and animal species. The workflow can be reproduced by downloading customized R code and related pathway files. As an example, we analyzed an RNA-Seq dataset of lung fibroblasts with Hoxa1 knockdown and revealed the possible roles of SP1 and E2F1 and their target genes, including microRNAs, in blocking G1/S transition. In another example, our analysis shows that in mouse B cells without functional p53, ionizing radiation activates the MYC pathway and its downstream genes involved in cell proliferation, ribosome biogenesis, and non-coding RNA metabolism. In wildtype B cells, radiation induces p53-mediated apoptosis and DNA repair while suppressing the target genes of MYC and E2F1, and leads to growth and cell cycle arrest. iDEP helps unveil the multifaceted functions of p53 and the possible involvement of several microRNAs such as miR-92a, miR-504, and miR-30a. In both examples, we validated known molecular pathways and generated novel, testable hypotheses. CONCLUSIONS: Combining comprehensive analytic functionalities with massive annotation databases, iDEP ( http://ge-lab.org/idep/ ) enables biologists to easily translate transcriptomic and proteomic data into actionable insights.

Nanoparticle metal oxides represent a new class of important materials that are increasingly being developed for use in research and health-related applications. Highly ionic metal oxides are interesting not only for their wide variety of physical and chemical properties but also for their antibacterial activity. Although the in vitro antibacterial activity and efficacy of regular zinc oxides have been investigated, little is known about the antibacterial activity of nanoparticles of ZnO. Preliminary growth analysis data suggest that nanoparticles of ZnO have significantly higher antibacterial effects on Staphylococcus aureus than do five other metal oxide nanoparticles. In addition, studies have clearly demonstrated that ZnO nanoparticles have a wide range of antibacterial effects on a number of other microorganisms. The antibacterial activity of ZnO may be dependent on the size and the presence of normal visible light. The data suggest that ZnO nanoparticles have a potential application as a bacteriostatic agent in visible light and may have future applications in the development of derivative agents to control the spread and infection of a variety of bacterial strains.

Despite the widespread use of social media by students and its increased use by instructors, very little empirical evidence is available concerning the impact of social media use on student learning and engagement. This paper describes our semester-long experimental study to determine if using Twitter – the microblogging and social networking platform most amenable to ongoing, public dialogue – for educationally relevant purposes can impact college student engagement and grades. A total of 125 students taking a first year seminar course for pre-health professional majors participated in this study (70 in the experimental group and 55 in the control group). With the experimental group, Twitter was used for various types of academic and co-curricular discussions. Engagement was quantified by using a 19-item scale based on the National Survey of Student Engagement. To assess differences in engagement and grades, we used mixed effects analysis of variance (ANOVA) models, with class sections nested within treatment groups. We also conducted content analyses of samples of Twitter exchanges. The ANOVA results showed that the experimental group had a significantly greater increase in engagement than the control group, as well as higher semester grade point averages. Analyses of Twitter communications showed that students and faculty were both highly engaged in the learning process in ways that transcended traditional classroom activities. This study provides experimental evidence that Twitter can be used as an educational tool to help engage students and to mobilize faculty into a more active and participatory role.

Professor Putnam’s much celebrated tome on the decline of social capital is an important, path-breaking work. His scholarship is social science at its best. Putnam asks the “big questions” about th...

The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Terra and Aqua satellites have provided nearly two decades of global fire data. Here, we describe refinements made to the 500-m global burned area mapping algorithm that were implemented in late 2016 as part of the MODIS Collection 6 (C6) land-product reprocessing. The updated algorithm improves upon the heritage Collection 5.1 (C5.1) MCD64A1 and MCD45A1 algorithms by offering significantly better detection of small burns, a modest reduction in burn-date temporal uncertainty, and a large reduction in the extent of unmapped areas. Comparison of the C6 and C5.1 MCD64A1 products for fifteen years (2002-2016) on a regional basis shows that the C6 product detects considerably more burned area globally (26%) and in almost every region considered. The sole exception was in Boreal North America, where the mean annual area burned was 6% lower for C6, primarily as a result of a large increase in the number of small lakes mapped (and subsequently masked) at high latitudes in the upstream C6 input data. With respect to temporal reporting accuracy, 44% of the C6 MCD64A1 burned grid cells were de-tected on the same day as an active fire, and 68% within 2 days, which represents a substantial reduction in temporal uncertainty compared to the C5.1 MCD64A1 and MCD45A1 products. In addition, an areal accuracy assessment of the C6 burned area product undertaken using high resolution burned area reference maps derived from 108 Landsat image pairs is reported.

Humans and their ancestors are unique in being a fire-making species, but 'natural' (i.e. independent of humans) fires have an ancient, geological history on Earth. Natural fires have influenced biological evolution and global biogeochemical cycles, making fire integral to the functioning of some biomes. Globally, debate rages about the impact on ecosystems of prehistoric human-set fires, with views ranging from catastrophic to negligible. Understanding of the diversity of human fire regimes on Earth in the past, present and future remains rudimentary. It remains uncertain how humans have caused a departure from 'natural' background levels that vary with climate change. Available evidence shows that modern humans can increase or decrease background levels of natural fire activity by clearing forests, promoting grazing, dispersing plants, altering ignition patterns and actively suppressing fires, thereby causing substantial ecosystem changes and loss of biodiversity. Some of these contemporary fire regimes cause substantial economic disruptions owing to the destruction of infrastructure, degradation of ecosystem services, loss of life, and smoke-related health effects. These episodic disasters help frame negative public attitudes towards landscape fires, despite the need for burning to sustain some ecosystems. Greenhouse gas-induced warming and changes in the hydrological cycle may increase the occurrence of large, severe fires, with potentially significant feedbacks to the Earth system. Improved understanding of human fire regimes demands: (1) better data on past and current human influences on fire regimes to enable global comparative analyses, (2) a greater understanding of different cultural traditions of landscape burning and their positive and negative social, economic and ecological effects, and (3) more realistic representations of anthropogenic fire in global vegetation and climate change models. We provide an historical framework to promote understanding of the development and diversification of fire regimes, covering the pre-human period, human domestication of fire, and the subsequent transition from subsistence agriculture to industrial economies. All of these phases still occur on Earth, providing opportunities for comparative research.

At over 40 years, the Landsat satellites provide the longest temporal record of space-based land surface observations, and the successful 2013 launch of the Landsat-8 is continuing this legacy. Ideally, the Landsat data record should be consistent over the Landsat sensor series. The Landsat-8 Operational Land Imager (OLI) has improved calibration, signal to noise characteristics, higher 12-bit radiometric resolution, and spectrally narrower wavebands than the previous Landsat-7 Enhanced Thematic Mapper (ETM +). Reflective wavelength differences between the two Landsat sensors depend also on the surface reflectance and atmospheric state which are difficult to model comprehensively. The orbit and sensing geometries of the Landsat-8 OLI and Landsat-7 ETM + provide swath edge overlapping paths sensed only one day apart. The overlap regions are sensed in alternating backscatter and forward scattering orientations so Landsat bi-directional reflectance effects are evident but approximately balanced between the two sensors when large amounts of time series data are considered. Taking advantage of this configuration a total of 59 million 30 m corresponding sensor observations extracted from 6317 Landsat-7 ETM + and Landsat-8 OLI images acquired over three winter and three summer months for all the conterminous United States (CONUS) are compared. Results considering different stages of cloud and saturation filtering, and filtering to reduce one day surface state differences, demonstrate the importance of appropriate per-pixel data screening. Top of atmosphere (TOA) and atmospherically corrected surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared bands, and derived normalized difference vegetation index (NDVI), are compared and their differences quantified. On average the OLI TOA reflectance is greater than the ETM + TOA reflectance for all bands, with greatest differences in the near-infrared (NIR) and the shortwave infrared bands due to the quite different spectral response functions between the sensors. The atmospheric correction reduces the mean difference in the NIR and shortwave infrared but increases the mean difference in the visible bands. Regardless of whether TOA or surface reflectance are used to generate NDVI, on average, for vegetated soil and vegetation surfaces (0 ≤ NDVI ≤ 1), the OLI NDVI is greater than the ETM + NDVI. Statistical functions to transform between the comparable sensor bands and sensor NDVI values are presented so that the user community may apply them in their own research to improve temporal continuity between the Landsat-7 ETM + and Landsat-8 OLI sensor data. The transformation functions were developed using ordinary least squares (OLS) regression and were fit quite reliably (r2 values > 0.7 for the reflectance data and > 0.9 for the NDVI data, p-values < 0.0001).

The sperm chromatin structure assay (SCSA) was used to measure over 500 human semen samples from two independent studies: Study I, 402 samples from 165 presumably fertile couples wishing to achieve pregnancy over 12 menstrual cycles; Study II, samples from 115 patients seeking fertility counselling. The SCSA measures susceptibility to DNA denaturation in situ in spermatozoa exposed to acid for 30 s, followed by acridine orange staining. SCSA data from the male partners of 73 couples (group 1) achieving pregnancy during months 1-3 of Study I were used as the standard of 'sperm chromatin compatible with high fertility' and were significantly different from those of 40 couples (group 3) achieving pregnancy in months 4-12 (P < 0.01) and those of male partners of 31 couples (group 4) not achieving pregnancy (P < 0.001). Group 2 contained couples who had a miscarriage. SCSA values for Study II were almost twice that of the Study I fertility standards. Within-couple repeatability tended to be less for group 3 than for groups 1, 2 or 4. Based on logistic regression, spermatozoa with denatured DNA (cells outside the main population, COMP alpha t) were the best predictor for whether a couple would not achieve pregnancy. Some 84% of males in group 1 had COMP alpha t < 15%, while no couples achieved pregnancy in group 1 with > or = 30% COMP alpha t, a threshold level considered not compatible with good fertility. Using selected cut-off values for chromatin integrity, the SCSA data predicted seven of 18 miscarriages (39%).

Formal planning and development of what became the first Landsat satellite commenced over 50 years ago in 1967. Now, having collected earth observation data for well over four decades since the 1972 launch of Landsat-1, the Landsat program is increasingly complex and vibrant. Critical programmatic elements are ensuring the continuity of high quality measurements for scientific and operational investigations, including ground systems, acquisition planning, data archiving and management, and provision of analysis ready data products. Free and open access to archival and new imagery has resulted in a myriad of innovative applications and novel scientific insights. The planning of future compatible satellites in the Landsat series, which maintain continuity while

The Sperm Chromatin Structure Assay (SCSA) was first described in the December 5, 1980 issue of Science (Evenson et al, 1980a). The data described in that article showed a significant difference between proven fertile and subfertility or infertility in men and bulls and the susceptibility to denaturation of their sperm nuclear DNA. A subsequent study The data were heterogeneous, and begged the question, what was SCSA measuring? Great effort has been spent over the past 15 years on animal model systems, mostly related to dose-response toxicology experiments and large animal fertility trials. The results from these studies showed that SCSA was highly dose-responsive to toxicants, highly repeatable, and provided meaningful biological information on sperm nuclear DNA defects.

Cancer metastasis is the major cause of cancer morbidity and mortality, and accounts for about 90% of cancer deaths. Although cancer survival rate has been significantly improved over the years, the improvement is primarily due to early diagnosis and cancer growth inhibition. Limited progress has been made in the treatment of cancer metastasis due to various factors. Current treatments for cancer metastasis are mainly chemotherapy and radiotherapy, though the new generation anti-cancer drugs (predominantly neutralizing antibodies for growth factors and small molecule kinase inhibitors) do have the effects on cancer metastasis in addition to their effects on cancer growth. Cancer metastasis begins with detachment of metastatic cells from the primary tumor, travel of the cells to different sites through blood/lymphatic vessels, settlement and growth of the cells at a distal site. During the process, metastatic cells go through detachment, migration, invasion and adhesion. These four essential, metastatic steps are inter-related and affected by multi-biochemical events and parameters. Additionally, it is known that tumor microenvironment (such as extracellular matrix structure, growth factors, chemokines, matrix metalloproteinases) plays a significant role in cancer metastasis. The biochemical events and parameters involved in the metastatic process and tumor microenvironment have been targeted or can be potential targets for metastasis prevention and inhibition. This review provides an overview of these metastasis essential steps, related biochemical factors, and targets for intervention.

Currently, obesity has become a global health issue and is referred to as an epidemic. Dysfunctional obese adipose tissue plays a pivotal role in the development of insulin resistance. However, the mechanism of how dysfunctional obese-adipose tissue develops insulin-resistant circumstances remains poorly understood. Therefore, this review attempts to highlight the potential mechanisms behind obesity-associated insulin resistance. Multiple risk factors are directly or indirectly associated with the increased risk of obesity; among them, environmental factors, genetics, aging, gut microbiota, and diets are prominent. Once an individual becomes obese, adipocytes increase in their size; therefore, adipose tissues become larger and dysfunctional, recruit macrophages, and then these polarize to pro-inflammatory states. Enlarged adipose tissues release excess free fatty acids (FFAs), reactive oxygen species (ROS), and pro-inflammatory cytokines. Excess systemic FFAs and dietary lipids enter inside the cells of non-adipose organs such as the liver, muscle, and pancreas, and are deposited as ectopic fat, generating lipotoxicity. Toxic lipids dysregulate cellular organelles, e.g., mitochondria, endoplasmic reticulum, and lysosomes. Dysregulated organelles release excess ROS and pro-inflammation, resulting in systemic inflammation. Long term low-grade systemic inflammation prevents insulin from its action in the insulin signaling pathway, disrupts glucose homeostasis, and results in systemic dysregulation. Overall, long-term obesity and overnutrition develop into insulin resistance and chronic low-grade systemic inflammation through lipotoxicity, creating the circumstances to develop clinical conditions. This review also shows that the liver is the most sensitive organ undergoing insulin impairment faster than other organs, and thus, hepatic insulin resistance is the primary event that leads to the subsequent development of peripheral tissue insulin resistance.

![Figure][1] Free image. This Landsat 5 image of the southeastern corner of the Black Sea is part of the general U.S. archive that will be accessible for free under the new USGS policy. CREDIT: BOSTON UNIVERSITY CENTER FOR REMOTE SENSING We are entering a new era in the Landsat Program, the oldest and most venerable of our Earth-observing satellite programs. With little fanfare, the U.S. Geological Survey (USGS) has begun providing imagery for free over the Internet. Throughout the history of the Landsat Program, the cost and access to imagery has always limited our ability to study our planet and the way it is changing. Beginning with a pilot program to provide “Web-enabled” access to Landsat 7 images of the United States that were collected between 2003 and this year, the USGS now plans to provide top-quality image products for free upon request for the entire U.S. archive, including over 2 million images back to Landsat 1 (1972) [for details and schedules, see ([1][2])]. The release by NASA and the USGS in January 2008 of a new Landsat Data Distribution Policy ([2][3]) was a key step to this goal. Free imagery will enable reconstruction of the history of Earth's surface back to 1972, chronicling both anthropogenic and natural changes during a time when our population doubled and the impacts of climate change became noticeable. The Landsat Science Team: 1. 1.[↵][4]USGS Technical Announcement ([http://landsat.usgs.gov/images/squares/USGS\_Landsat\_Imagery_Release.pdf][5]). 2. 2.[↵][6]Landsat Missions ([http://ldcm.usgs.gov/pdf/Landsat\_Data\_Policy.pdf][7]). [1]: pending:yes [2]: #ref-1 [3]: #ref-2 [4]: #xref-ref-1-1 View reference 1. in text [5]: http://landsat.usgs.gov/images/squares/USGS_Landsat_Imagery_Release.pdf [6]: #xref-ref-2-1 View reference 2. in text [7]: http://ldcm.usgs.gov/pdf/Landsat_Data_Policy.pdf