Geology and Wine 8. Modeling Viticultural Landscapes: A GIS Analysis of the Terroir Potential in the Umpqua Valley of Oregon

Terroir is a holistic concept that relates to both environmental and cultural factors that together influence the grape growing to wine production continuum. The physical factors that influence the process include matching a given grape variety to its ideal climate along with optimum site characteristics of elevation, slope, aspect, and soil. While some regions have had hundreds and even thousands of years to define, develop, and understand their best terroir, newer regions typically face a trial and error stage of finding the best variety and terroir match. This research facilitates the process by modeling the climate and landscape in a relatively young grape growing region in Oregon, the Umpqua Valley appellation. The result is an inventory of land suitability that provides both existing and new growers greater insight into the best terroirs of the region. SOMMAIRE Le terroir est un concept holiste de facteurs environnementaux et culturels agissant sur un continuum s'étendant de la croissance de la vigne à la vinification. Dans le domaine des facteurs physiques, il faut trouver la combinaison idéale entre la variété du raisin d'une part, et le climat et les caractéristiques du site de culture comme l'élévation, la pente, l'aspect et le type de sol, d'autre part. Alors qu'en certaines régions, on a eu des centaines, voire des milliers d'année pour définir, développer et définir le terroir idéal, dans les régions nouvelles, on doit procéder par essais et erreur pour trouver le meilleur appariement raisin et terroir. La recherche décrite ci-contre entend faciliter ce processus de mariage idéal en modélisant les facteurs du climat et du paysage dans une région viticole relativement jeune de l'Orégon, celle de la vallée de Umpqua. Le résultat obtenu est un inventaire des terrains propices, ce qui fait aussi bien l'affaire des vignerons établis que des nouveaux vignerons dans leur quête des meilleurs terroirs de la région

A new test of gravity – II. Application of marked correlation functions to luminous red galaxy samples

We apply the marked correlation function test proposed by Armijo et al. (Paper I) to samples of luminous red galaxies (LRGs) from the final data release of the Sloan Digital Sky Survey (SDSS) III. The test assigns a density-dependent mark to galaxies in the estimation of the projected marked correlation function. Two gravity models are compared: general relativity (GR) and gravity. We build mock catalogues which, by construction, reproduce the measured galaxy number density and two-point correlation function of the LRG samples, using the halo occupation distribution model (HOD). A range of HOD models give acceptable fits to the observational constraints, and this uncertainty is fed through to the error in the predicted marked correlation functions. The uncertainty from the HOD modelling is comparable to the sample variance for the SDSS-III LRG samples. Our analysis shows that current galaxy catalogues are too small for the test to distinguish a popular model from GR. However, upcoming surveys with a better measured galaxy number density and smaller errors on the two-point correlation function, or a better understanding of galaxy formation, may allow our method to distinguish between viable gravity models

A new marked correlation function scheme for testing gravity

We introduce a new scheme based on the marked correlation function to probe gravity using the large-scale structure of the Universe. We illustrate our approach by applying it to simulations of the metric-variation $f(R)$ modified gravity theory and general relativity (GR). The modifications to the equations in $f(R)$ gravity lead to changes in the environment of large-scale structures that could, in principle, be used to distinguish this model from GR. Applying the Monte Carlo Markov Chain algorithm, we use the observed number density and two-point clustering to fix the halo occupation distribution (HOD) model parameters and build mock galaxy catalogues from both simulations. To generate a mark for galaxies when computing the marked correlation function we estimate the local density using a Voronoi tessellation. Our approach allows us to isolate the contribution to the uncertainty in the predicted marked correlation function that arises from the range of viable HOD model parameters, in addition to the sample variance error for a single set of HOD parameters. This is critical for assessing the discriminatory power of the method. In a companion paper we apply our new scheme to a current large-scale structure survey.Comment: 11 pages, 7 figure

A new test of gravity – I. Introduction to the method

We introduce a new scheme based on the marked correlation function to probe gravity using the large-scale structure of the Universe. We illustrate our approach by applying it to simulations of the metric-variation f(R) modified gravity theory and general relativity (GR). The modifications to the equations in f(R) gravity lead to changes in the environment of large-scale structures that could, in principle, be used to distinguish this model from GR. Applying the Monte Carlo Markov Chain algorithm, we use the observed number density and two-point clustering to fix the halo occupation distribution (HOD) model parameters and build mock galaxy catalogues from both simulations. To generate a mark for galaxies when computing the marked correlation function we estimate the local density using a Voronoi tessellation. Our approach allows us to isolate the contribution to the uncertainty in the predicted marked correlation function that arises from the range of viable HOD model parameters, in addition to the sample variance error for a single set of HOD parameters. This is critical for assessing the discriminatory power of the method. In a companion paper, we apply our new scheme to a current large-scale structure survey

GLOBE Mosquito Habitat Mapper Citizen Science Data 2017–2020

The GLOBE Program\u27s GLOBE Observer application is a free citizen science mobile data collection and visualization tool compatible with iOS and Android operating systems. Citizen scientists armed with the app can report the mosquito larval habitats they identify using the GLOBE Mosquito Habitat Mapper tool. This data can complement the climate, weather, and land cover data obtained from satellite measurements by scientists who develop risk models for mosquito-borne diseases. Public participation in mosquito surveillance research provides the opportunity to obtain the volume, velocity and variety of data needed to fight the threat of vector-borne diseases, especially in under-resourced communities with minimal to no municipal surveillance and mitigation services. GLOBE Mosquito Habitat Mappers document and describe potential and active mosquito larval habitats in and around their homes and communities. An easy-to-use pictorial interface enables users to geolocate and describe oviposition sites encountered, count and identify mosquito larvae, and when appropriate, eliminate the larval habitats. During Mosquito Habitat Mapper\u27s first 3 years of use, over 24,000 data observations have been reported throughout the world. This technical report summarizes GLOBE Mosquito Habitat Mapper data reported by GLOBE citizen scientists from three regions: Africa, Asia and the Pacific Islands, and Latin America and the Caribbean. Localized mosquito larvae distribution patterns were examined by comparing data collected in three cities in Senegal–Dakar, Touba, and Thilmakha. The Senegal data show habitat and genera differences among mosquitoes identified by citizen scientists in the cities and illustrates the potential of the app for community-based surveillance and research

Spatial and temporal patterns of forest disturbance and regrowth within the area of the Northwest Forest Plan

Understanding fine-grain patterns of forest disturbance and regrowth at the landscape scale is critical for effective management, particularly in forests in western Washington, Oregon, and California, U.S., where the policy known as the Northwest Forest Plan (NWFP) was imposed in 1994 over > 8 million ha of forest in an effort to balance environmental and economic tensions. We developed approaches to create disturbance and regrowth maps for forests within the area of the NWFP from the results of LandTrendr, a temporal segmentation algorithm described previously only at the pixel scale. Maps were developed from 674 Landsat Thematic Mapper and Enhanced Thematic Mapper + images distributed across 22 separate scene areas, and were assessed for validity at 2360 points using TimeSync, a time-series validation and interpretation tool. Unlike maps derived using other techniques, maps derived from the segmentation approach were unique in providing simultaneous detection of abrupt disturbance, chronic disturbance, and ongoing vegetative growth with consistency across large areas and across time. Maps were then used to address six core monitoring questions focusing on the distribution of disturbance across time, ownership categories, and ecoregions. Forest was disturbed at rates that varied by ownership category and state, ranging from 9% to > 39% of forest area over the period 1985 to 2008, with highest cumulative disturbed area on private and native lands in Washington and Oregon and lowest disturbed area on federal protected lands in Washington. Effects of court injunctions and subsequent implementation of the NWFP lowered forest disturbance rates, particularly in Oregon, and also caused decreases in the relative magnitude of disturbance on those lands relative to private lands. State-managed forests showed forest disturbance rates that varied considerably among the three states, with the highest rates in Washington state and lowest in California. Affected by large, stochastic fire events, protected lands in both Oregon and California showed disturbance rates similar to those found on actively managed federal lands. Protected lands also experienced high rates of chronic disturbance, often associated with insect-related mortality. As expected, moisture-limited ecoregions recovered vegetation more slowly than those where moisture was not limiting. Vegetative regrowth rates showed substantial variation among ownership categories, suggesting that differential forest policies may affect vegetative recovery rate. Taken together, these results emphasize that forest management policies do have manifestations at the landscape scale, but that detection of these manifestations is best achieved with mapping approaches that can detect both abrupt and longer-duration processes within the Landsat archive.Keywords: Growth, Northwest forest plan, Change detection, Forest, Disturbance, Landsa

Attribution of disturbance change agent from Landsat time-series in support of habitat monitoring in the Puget Sound region, USA

To understand causes and consequences of landscape change, it is often not enough to simply detect change. Rather, the agent causing the change must also be determined. Here, we describe and test a method of change agent attribution built on four tenets: agents operate on patches rather than pixels; temporal context can provide insight into the agent of change; human interpretation is critical because agent labels are inherently human-defined; and statistical modeling must be flexible and non-parametric. In the Puget Sound, USA, we used LandTrendr Landsat time-series-based algorithms to identify abrupt disturbances, and then applied spatial rules to aggregate these to patches. We then derived a suite of spectral, patch-shape, and landscape position variables for each patch. These were then linked to patch-level training labels determined by interpreters at 1198 training patches, and modeled statistically using the Random Forest machine-learning algorithm. Labeled agents of change included urbanization, forest management, and natural change (largely fire), as well as labels associated with spectral change that was non-informative (false change). The success of the method was evaluated using both out-of-bag (OOB) error and a small, fully-independent validation interpretation dataset. Overall OOB accuracy was above 80%, but most successful in the numerically well-represented forest management class. Validation with the independent data was generally lower than that estimated with the OOB approach, but comparable when either first or second voting scores were used for prediction. Spatial and temporal patterns within the study area followed expectations well, with most urbanization occurring in the lower elevation regions around Seattle–Tacoma, most forest management occurring in mid-slope managed forests, and most natural disturbance occurring in protected areas. Temporal patterns of change agent aggregated to the watershed level suggest substantial year-over-year variability that could be used to examine year-over-year variability in fish species populations.Keywords: Disturbance, Change attribution, Puget Sound, Salmon, LandTrendr, Time series, Change detection, Landsa

Multi-compound polarization by DNP allows simultaneous assessment of multiple enzymatic activities in vivo

Methods for the simultaneous polarization of multiple 13C-enriched metabolites were developed to probe several enzymatic pathways and other physiologic properties in vivo, using a single intravenous bolus. A new method for polarization of 13C sodium bicarbonate suitable for use in patients was developed, and the co-polarization of 13C sodium bicarbonate and [1-13C]pyruvate in the same sample was achieved, resulting in high solution state polarizations (15.7% and 17.6%, respectively) and long spin-lattice relaxation times (T1) (46.7s and 47.7s respectively at 3T). Consistent with chemical shift anisotropy dominating the T1 relaxation of carbonyls, T1 values for 13C bicarbonate and [1-13C]pyruvate were even longer at 3T (49.7s and 67.3s, respectively). Co-polarized 13C bicarbonate and [1-13C] pyruvate were injected into normal mice and a murine prostate tumor model at 3T. Rapid equilibration of injected hyperpolarized 13C sodium bicarbonate with 13C CO2 allowed calculation of pH on a voxel by voxel basis, and simultaneous assessment of pyruvate metabolism with cellular uptake and conversion of [1-13C] pyruvate to its metabolic products. Initial studies in a Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) model demonstrated higher levels of hyperpolarized lactate and lower pH within tumor, relative to surrounding benign tissues and to the abdominal viscera of normal controls. There was no significant difference observed in the tumor lactate/pyruvate ratio obtained after the injection of co-polarized 13C bicarbonate and [1-13C]pyruvate or polarized [1-13C]pyruvate alone. The technique was extended to polarize four 13C labelled substrates potentially providing information on pH, metabolism, necrosis and perfusion, namely [1-13C]pyruvic acid, 13C sodium bicarbonate, [1,4-13C]fumaric acid, and 13C urea with high levels of solution polarization (17.5, 10.3, 15.6 and 11.6%, respectively) and spin-lattice relaxation values similar to those recorded for the individual metabolites. These studies demonstrated the feasibility of simultaneously measuring in vivo pH and tumor metabolism using nontoxic, endogenous species, and the potential to extend the multi-polarization approach to include up to four hyperpolarized probes providing multiple metabolic and physiologic measures in a single MR acquisition

The 2dF Galaxy Redshift Survey: the clustering of galaxy groups

We measure the clustering of galaxy groups in the 2dFGRS Percolation-Inferred Galaxy Group (2PIGG) catalogue. The 2PIGG sample has 28 877 groups with at least two members. The clustering amplitude of the full 2PIGG catalogue is weaker than that of 2dFGRS galaxies, in agreement with theoretical predictions. We have subdivided the 2PIGG catalogue into samples that span a factor of ≈ 25 in median total luminosity. Our correlation function measurements span an unprecedented range of clustering strengths, connecting the regimes probed by groups fainter than L* galaxies and rich clusters. There is a steady increase in clustering strength with group luminosity; the most luminous groups are 10 times more strongly clustered than the full 2PIGG catalogue. We demonstrate that the 2PIGG results are in very good agreement with the clustering of groups expected in the ΛCDM mode

Comparison and assessment of coarse resolution land cover maps for Northern Eurasia

Information on land cover at global and continental scales is critical for addressing a range of ecological, socioeconomic and policy questions. Global land cover maps have evolved rapidly in the last decade, but efforts to evaluate map uncertainties have been limited, especially in remote areas like Northern Eurasia. Northern Eurasia comprises a particularly diverse region covering a wide range of climate zones and ecosystems: from arctic deserts, tundra, boreal forest, and wetlands, to semi-arid steppes and the deserts of Central Asia. In this study, we assessed four of the most recent global land cover datasets: GLC-2000, GLOBCOVER, and the MODIS Collection 4 and Collection 5 Land Cover Product using cross-comparison analyses and Landsat-based reference maps distributed throughout the region. A consistent comparison of these maps was challenging because of disparities in class definitions, thematic detail, and spatial resolution. We found that the choice of sampling unit significantly influenced accuracy estimates, which indicates that comparisons of reported global map accuracies might be misleading. To minimize classification ambiguities, we devised a generalized legend based on dominant life form types (LFT) (tree, shrub, and herbaceous vegetation, barren land and water). LFT served as a necessary common denominator in the analyzed map legends, but significantly decreased the thematic detail. We found significant differences in the spatial representation of LFT's between global maps with high spatial agreement (above 0.8) concentrated in the forest belt of Northern Eurasia and low agreement (below 0.5) concentrated in the northern taiga-tundra zone, and the southern dry lands. Total pixel-level agreement between global maps and six test sites was moderate to fair (overall agreement: 0.67-0.74, Kappa: 0.41-0.52) and increased by 0.09-0.45 when only homogenous land cover types were analyzed. Low map accuracies at our tundra test site confirmed regional disagreements and difficulties of current global maps in accurately mapping shrub and herbaceous vegetation types at the biome borders of Northern Eurasia. In comparison, tree dominated vegetation classes in the forest belt of the region were accurately mapped, but were slightly overestimated (10%-20%), in all maps. Low agreement of global maps in the northern and southern vegetation transition zones of Northern Eurasia is likely to have important implications for global change research, as those areas are vulnerable to both climate and socio-economic changes. (C) 2011 Elsevier Inc. All rights reserved.Keywords: Land cover, MODIS, Eurasia, Global, Validation, GLC-2000, LCCS, GLOBCOVERKeywords: Land cover, MODIS, Eurasia, Global, Validation, GLC-2000, LCCS, GLOBCOVE