Spatial climate data sets of 1971-2000 mean monthly precipitation and minimum and maximum temperature were developed for the conterminous United States. These 30-arcsec (∼800-m) grids are the official spatial climate data sets of the U.S. Department of Agriculture. The PRISM (Parameter-elevation Relationships on Independent Slopes Model) interpolation method was used to develop data sets that reflected, as closely as possible, the current state of knowledge of spatial climate patterns in the United States. PRISM calculates a climate-elevation regression for each digital elevation model (DEM) grid cell, and stations entering the regression are assigned weights based primarily on the physiographic similarity of the station to the grid cell. Factors considered are location, elevation, coastal proximity, topographic facet orientation, vertical atmospheric layer, topographic position, and orographic effectiveness of the terrain. Surface stations used in the analysis numbered nearly 13 000 for precipitation and 10 000 for temperature. Station data were spatially quality controlled, and short-period-of-record averages adjusted to better reflect the 1971-2000 period.PRISM interpolation uncertainties were estimated with cross-validation (C-V) mean absolute error (MAE) and the 70% prediction interval of the climate-elevation regression function. The two measures were not well correlated at the point level, but were similar when averaged over large regions. The PRISM data set was compared with the WorldClim and Daymet spatial climate data sets. The comparison demonstrated that using a relatively dense station data set and the physiographically sensitive PRISM interpolation process resulted in substantially improved climate grids over those of WorldClim and Daymet. The improvement varied, however, depending on the complexity of the region. Mountainous and coastal areas of the western United States, characterized by sparse data coverage, large elevation gradients, rain shadows, inversions, cold air drainage, and coastal effects, showed the greatest improvement. The PRISM data set benefited from a peer review procedure that incorporated local knowledge and data into the development process.

The relationships between variations in grapevine (Vitis vinifera L. cv. Pinot noir) growth and resulting fruit and wine phenolic composition were investigated. The study was conducted in a commercial vineyard consisting of the same clone, rootstock, age, and vineyard management practices. The experimental design involved monitoring soil, vine growth, yield components, and fruit composition (soluble solids, flavan-3-ol monomers, proanthocyanidins, and pigmented polymers) on a georeferenced grid pattern to assess patterns in growth and development. Vine vigor parameters (trunk cross-sectional area, average shoot length, and leaf chlorophyll) were used to delineate zones within both blocks to produce research wines to investigate the vine-fruit-wine continuum. There was no significant influence of vine vigor on the amount of proanthocyanidin per seed and only minimal differences in seed proanthocyanidin composition. However, significant increases were found in skin proanthocyanidin (mg/berry), proportion of (-)-epigallocatechin, average molecular mass of proanthocyanidins, and pigmented polymer content in fruit from zones with a reduction in vine vigor. In the wines produced from low-vigor zones, there was a large increase in the proportion of skin tannin extracted into the wine, whereas little change occurred in seed proanthocyanidin extraction. The level of pigmented polymers and proanthocyanidin molecular mass were higher in wines made from low-vigor fruit compared to wines made from high-vigor fruit, whereas the flavan-3-ol monomer concentration was lower.

The relationships between grapevine (Vitis vinifera) vigor variation and resulting fruit anthocyanin accumulation and composition were investigated. The study was conducted in a commercial vineyard consisting of the same clone, rootstock, age, and vineyard management practices. The experimental design involved assigning vigor zones in two vineyard sites based upon differences in vine growth. Fruits and wines were analyzed by HPLC from designated vigor zones in 2003 and 2004. Average berry weight (grams), average dry skin weight (milligrams), degrees Brix, and pH were higher and titratable acidity (grams per liter) was lower in 2003 compared to 2004. In 2003, only the highest and lowest vigor zones had differences in berry weight, whereas there were no differences in 2004. In both years, high vigor zones had lower degrees Brix and higher titratable acidity (milligrams per liter). Accumulation of anthocyanins (milligrams per berry) was greater in 2003 compared to 2004. There was a trend for lower anthocyanin concentration (milligrams per berry) in high vigor zones in both years. In 2004 compared to 2003, there was a higher proportion of malvidin-3-O-glucoside and lower proportions of the other four anthocyanins (delphinidin-, cyanidin-, petunidin-, and peonidin-3-O-glucosides) found in Pinot Noir. In both years, site A had proportionally higher peonidin-3-O-glucoside and lower malvidin-3-O-glucoside than site B. Some of these differences may be related to the higher exposure and temperatures found in site B compared to site A and also in the low vigor zones.

In many regions of the world, the extremes of winter cold are a major determinant of the geographic distribution of perennial plant species and of their successful cultivation. In the United States, the U.S. Department of Agriculture (USDA) Plant Hardiness Zone Map (PHZM) is the primary reference for defining geospatial patterns of extreme winter cold for the horticulture and nursery industries, home gardeners, agrometeorologists, and plant scientists. This paper describes the approaches followed for updating the USDA PHZM, the last version of which was published in 1990. The new PHZM depicts 1976-2005 mean annual extreme minimum temperature, in 2.88C (58F) half zones, for the conterminous United States, Alaska, Hawaii, and Puerto Rico. Station data were interpolated to a grid with the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) climate-mapping system. PRISM accounts for the effects of elevation, terrain-induced airmass blockage, coastal effects, temperature inversions, and cold-air pooling on extreme minimum temperature patterns. Climatologically aided interpolation was applied, based on the 1971-2000 mean minimum temperature of the coldest month as the predictor grid. Evaluation of a standard-deviation map and two 15-yr maps (1976-90 and 1991-2005 averaging periods) revealed substantial vertical and horizontal gradients in trend and variability, especially in complex terrain. The new PHZM is generally warmer by one 2.88C (58F) half zone than the previous PHZM throughout much of the United States, as a result of a more recent averaging period. Nonetheless, a more sophisticated interpolation technique, greater physiographic detail, and more comprehensive station data were the main causes of zonal changes in complex terrain, especially in the western United States. The updated PHZM can be accessed online (http://www.planthardiness.ars.usda.gov).

Current knowledge of yield potential and best agronomic management practices for perennial bioenergy grasses is primarily derived from small-scale and short-term studies, yet these studies inform policy at the national scale. In an effort to learn more about how bioenergy grasses perform across multiple locations and years, the U.S. Department of Energy (US DOE)/Sun Grant Initiative Regional Feedstock Partnership was initiated in 2008. The objectives of the Feedstock Partnership were to (1) provide a wide range of information for feedstock selection (species choice) and management practice options for a variety of regions and (2) develop national maps of potential feedstock yield for each of the herbaceous species evaluated. The Feedstock Partnership expands our previous understanding of the bioenergy potential of switchgrass, Miscanthus, sorghum, energycane, and prairie mixtures on Conservation Reserve Program land by conducting long-term, replicated trials of each species at diverse environments in the U.S. Trials were initiated between 2008 and 2010 and completed between 2012 and 2015 depending on species. Field-scale plots were utilized for switchgrass and Conservation Reserve Program trials to use traditional agricultural machinery. This is important as we know that the smaller scale studies often overestimated yield potential of some of these species. Insufficient vegetative propagules of energycane and Miscanthus prohibited farm-scale trials of these species. The Feedstock Partnership studies also confirmed that environmental differences across years and across sites had a large impact on biomass production. Nitrogen application had variable effects across feedstocks, but some nitrogen fertilizer generally had a positive effect. National yield potential maps were developed using PRISM-ELM for each species in the Feedstock Partnership. This manuscript, with the accompanying supplemental data, will be useful in making decisions about feedstock selection as well as agronomic practices across a wide region of the country.

To increase the understanding of poplar and willow perennial woody crops and facilitate their deployment for the production of biofuels, bioproducts, and bioenergy, there is a need for broadscale yield maps. For national analysis of woody and herbaceous crops production potential, biomass feedstock yield maps should be developed using a common framework. This study developed willow and poplar potential yield maps by combining data from a network of willow and poplar field trials and the modeling power of PRISM-ELM. Yields of the top three willow cultivars across 17 sites ranged from 3.60 to 14.6 Mg ha À1 yr À1 dry weight, while the yields from 17 poplar trials ranged from 7.5 to 15.2 Mg ha À1 yr À1. Relationships between the environmental suitability estimates from the PRISM-ELM model and results from field trials had an R 2 of 0.60 for poplar and 0.81 for willow. The resulting potential yield maps reflected the range of poplar and willow yields that have been reported in the literature. Poplar covered a larger geographic range than willow, which likely reflects the poplar breeding efforts that have occurred for many more decades using genotypes from a broader range of environments than willow. While the field trial data sets used to develop these models represent the most complete information at the time, there is a need to expand and improve the model by monitoring trials over multiple cutting cycles and across a broader range of environmental gradients. Despite some limitations, the results of these models represent a dramatic improvement in projections of potential yield of poplar and willow crops across the United States.

Several crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long-term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstock Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM-ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long-term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low-temperature response, summer high-temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.

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