Latitudinal range shifts of tree species in the United States across multi-decadal time scales

2015 ◽  
Vol 16 (3) ◽  
pp. 231-238 ◽  
Author(s):  
Brice B. Hanberry ◽  
Mark H. Hansen
Keyword(s):  
United States ◽  
Time Scales ◽  
Tree Species ◽  
The United States ◽  
Range Shifts ◽  
Latitudinal Range

scholarly journals Relations between Temperature and Residential Natural Gas Consumption in the Central and Eastern United States

2007 ◽  
Vol 46 (11) ◽  
pp. 1993-2013 ◽  
Author(s):  
Reed P. Timmer ◽  
Peter J. Lamb
Keyword(s):  
United States ◽  
Natural Gas ◽  
Time Scales ◽  
The United States ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
The South ◽  
Northern Regions ◽  
Gas Consumption

Abstract The increased U.S. natural gas price volatility since the mid-to-late-1980s deregulation generally is attributed to the deregulated market being more sensitive to temperature-related residential demand. This study therefore quantifies relations between winter (November–February; December–February) temperature and residential gas consumption for the United States east of the Rocky Mountains for 1989–2000, by region and on monthly and seasonal time scales. State-level monthly gas consumption data are aggregated for nine multistate subregions of three Petroleum Administration for Defense Districts of the U.S. Department of Energy. Two temperature indices [days below percentile (DBP) and heating degree-days (HDD)] are developed using the Richman–Lamb fine-resolution (∼1° latitude–longitude) set of daily maximum and minimum temperatures for 1949–2000. Temperature parameters/values that maximize DBP/HDD correlations with gas consumption are identified. Maximum DBP and HDD correlations with gas consumption consistently are largest in the Great Lakes–Ohio Valley region on both monthly (from +0.89 to +0.91) and seasonal (from +0.93 to +0.97) time scales, for which they are based on daily maximum temperature. Such correlations are markedly lower on both time scales (from +0.62 to +0.80) in New England, where gas is less important than heating oil, and on the monthly scale (from +0.55 to +0.75) across the South because of low January correlations. For the South, maximum correlations are for daily DBP and HDD indices based on mean or minimum temperature. The percentiles having the highest DBP index correlations with gas consumption are slightly higher for northern regions than across the South. This is because lower (higher) relative (absolute) temperature thresholds are reached in warmer regions before home heating occurs. However, these optimum percentiles for all regions are bordered broadly by surrounding percentiles for which the correlations are almost as high as the maximum. This consistency establishes the robustness of the temperature–gas consumption relations obtained. The reference temperatures giving the highest HDD correlations with gas consumption are lower for the colder northern regions than farther south where the temperature range is truncated. However, all HDD reference temperatures greater than +10°C (+15°C) yield similar such correlations for northern (southern) regions, further confirming the robustness of the findings. This robustness, coupled with the very high correlation magnitudes obtained, suggests that potentially strong gas consumption predictability would follow from accurate seasonal temperature forecasts.

scholarly journals First Record ofPyramica epinotalis(Hymenoptera: Formicidae) for the United States

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Xuan Chen ◽  
Joe A. MacGown ◽  
Benjamin J. Adams ◽  
Katherine A. Parys ◽  
Rachel M. Strecker ◽  
...  
Keyword(s):  
United States ◽  
Tree Species ◽  
First Record ◽  
The United States ◽  
Pitfall Traps ◽  
Southern Mexico ◽  
Additional Specimen ◽  
Design And Implementation ◽  
Floating Vegetation ◽  
Made In

Pyramica epinotalisis an arboreal dacetine ant previously known only from Brazil, Costa Rica, Ecuador, and southern Mexico. Here we report the first records ofP. epinotalisfor the United States. Collections were made in three parishes across southern Louisiana in cypress-tupelo swamps using floating pitfall traps placed in floating vegetation and arboreal pitfall traps placed on trunks and limbs of three wetland tree species. One additional specimen of this species was collected in Highlands County, Florida. Based on collections of specimens in Louisiana, including multiple dealate females at different localities,P. epinotalisappears to be well established in this state. We discuss the design and implementation of modified arboreal pitfall traps that were instrumental in this discovery.

scholarly journals Potential Alternative Tree Species as Substrates for Forest Farming of Log-grown Shiitake Mushrooms in the Southeastern United States

2020 ◽  
Vol 30 (6) ◽  
pp. 741-744
Author(s):  
Gregory E. Frey ◽  
Tarik Durmus ◽  
Erin O. Sills ◽  
Fikret Isik ◽  
Marcus M. Comer
Keyword(s):  
United States ◽  
Tree Species ◽  
Southeastern United States ◽  
Acer Rubrum ◽  
The United States ◽  
Financial Returns ◽  
White Oak ◽  
Suitable Alternative ◽  
Shiitake Mushrooms ◽  
Potential Alternative

Shiitake (Lentinula edodes) is an edible mushroom-producing fungus. “Natural log-grown” shiitake mushrooms are favored by consumers and are often produced by small farmers and hobbyists in the United States. The tree species most often recommended as a substrate for shiitake is white oak (Quercus alba), which has many other economic uses. We tested two strains of shiitake in log substrates of three common, low-value tree species in the southeastern United States to identify potential alternatives to white oak. We found that sweetgum (Liquidambar styraciflua) was a good substitute for white oak, both in terms of mushroom production and financial returns. Red maple (Acer rubrum) had less potential, with lower production and marginal financial returns, and ailanthus (Ailanthus altissima) was not a suitable alternative substrate. Of the two shiitake strains tested, a commercially available strain performed better than a naturalized strain that was isolated from an uninoculated log. Further research is needed to identify other potential alternative substrates and production techniques in the southeastern United States and other regions.

scholarly journals A Changing Climatology of Precipitation Persistence across the United States Using Information-Based Measures

2019 ◽  
Vol 20 (8) ◽  
pp. 1649-1666 ◽  
Author(s):  
Allison E. Goodwell ◽  
Praveen Kumar
Keyword(s):  
United States ◽  
Time Scales ◽  
Daily Precipitation ◽  
Temporal Trends ◽  
The United States ◽  
Binary Sequences ◽  
Precipitation Frequency ◽  
Climate Trend ◽  
Information Measures ◽  
Time Lagged

Abstract The sequencing, or persistence, of daily precipitation influences variability in streamflow, soil moisture, and vegetation states. As these factors influence water availability and ecosystem health, it is important to identify spatial and temporal trends in precipitation persistence and predictability. We take an information theoretic perspective to address regional and temporal trends in daily patterns, based on the Climate Prediction Center (CPC) gridded gauge-based dataset of daily precipitation over the continental United States from 1948 to 2018. We apply information measures to binary sequences of precipitation occurrence to quantify uncertainty, predictability in the form of lagged mutual information between the current state and two time-lagged histories, and associated dominant time scales. We find that this information-based predictability is highest in the western United States, but the relative influence of longer lagged histories in comparison to a 1-day history is highest in the east. Information characteristics and time scales vary seasonally and regionally and constitute an information climatology that can be compared with traditional indices of precipitation and climate. Trend analyses over the 70-yr time period also show varying regional characteristics that differ between seasons. In addition to increasing precipitation frequency over most of the country, we detect increasing and decreasing predictability in western and eastern regions, respectively, with average trend magnitudes corresponding to shifts in predictability ranging from −50% to 110%. This new perspective on precipitation persistence has broad potential to link shifts in climate and weather to patterns and predictability of related environmental factors.

scholarly journals Multitemporal Analysis of TRMM-Based Satellite Precipitation Products for Land Data Assimilation Applications

2007 ◽  
Vol 8 (6) ◽  
pp. 1165-1183 ◽  
Author(s):  
Yudong Tian ◽  
Christa D. Peters-Lidard ◽  
Bhaskar J. Choudhury ◽  
Matthew Garcia
Keyword(s):  
United States ◽  
Data Assimilation ◽  
Time Scales ◽  
The United States ◽  
Probability Of Detection ◽  
Multiple Time Scales ◽  
Diurnal Cycles ◽  
Land Data Assimilation ◽  
Trmm 3B42 ◽  
Rms Errors

Abstract In this study, the recent work of Gottschalck et al. and Ebert et al. is extended by assessing the suitability of two Tropical Rainfall Measuring Mission (TRMM)-based precipitation products for hydrological land data assimilation applications. The two products are NASA’s gauge-corrected TRMM 3B42 Version 6 (3B42), and the satellite-only NOAA Climate Prediction Center (CPC) morphing technique (CMORPH). The two products were evaluated against ground-based rain gauge–only and gauge-corrected Doppler radar measurements. The analyses were performed at multiple time scales, ranging from annual to diurnal, for the period March 2003 through February 2006. The analyses show that at annual or seasonal time scales, TRMM 3B42 has much lower biases and RMS errors than CMORPH. CMORPH shows season-dependent biases, with overestimation in summer and underestimation in winter. This leads to 50% higher RMS errors in CMORPH’s area-averaged daily precipitation than TRMM 3B42. At shorter time scales (5 days or less), CMORPH has slightly less uncertainty, and about 10%–20% higher probability of detection of rain events than TRMM 3B42. In addition, the satellite estimates detect more high-intensity events, causing a remarkable shift in precipitation spectrum. Summertime diurnal cycles in the United States are well captured by both products, although the 8-km CMORPH seems to capture more diurnal features than the 0.25° CMORPH or 3B42 products. CMORPH tends to overestimate the amplitude of the diurnal cycles, particularly in the central United States. Possible causes for the discrepancies between these products are discussed.

scholarly journals Assessment on latitudinal tree species richness using environmental factors in the southeastern United States

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6781
Author(s):  
Youngsang Kwon ◽  
Taesoo Lee ◽  
Alison Lang ◽  
Dorian Burnette
Keyword(s):  
United States ◽  
Species Richness ◽  
Environmental Factors ◽  
Tree Species ◽  
The United States ◽  
Forested Area ◽  
Tree Species Richness ◽  
Mean Temperature ◽  
Precipitation Seasonality ◽  
Southeastern Region

The southeastern region of the United States exhibits an unusual trend of decreasing tree species richness (TSR) from higher to lower latitudes over the Florida peninsula. This trend contradicts the widely marked latitudinal diversity gradient where species richness is highest in tropical zones and decreases towards extratropical regions. This study aims to assess the environmental factors that prompt this atypical inverse latitudinal gradient seen in TSR using the USDA Forest Service’s Forest Inventory and Analysis (FIA) database. Fifteen variables under four categories of forested area, groundwater, soil properties, and climate groups were examined to model TSR in the region. Generalized linear models (GLMs) with Poisson distributions first assessed individual variables to test explanatory power then the LASSO regularization method was utilized to extract two subsets of the most influential variables to predict TSR. Forest area and four climate variables (mean annual temperature, precipitation seasonality, mean temperature of coldest quarter, and mean precipitation of driest quarter) were the top five variables during the initial GLM assessment implying their potential individual influence in regulating TSR. Two subsets of LASSO models contained seven and three predictor variables, respectively. Frist subset includes seven predictors, presented in highest to low standardized coefficient, mean temperature of coldest quarter, forested area, precipitation seasonality, mean precipitation of driest quarter, water table depth, spodosol, and available water storage. The other subset further excluded four lowest influential variables from the first set, leaving the top three variables from the first subset. The first subset of the LASSO model predicted TSR with 63.4% explained deviance while the second subset reproduced 60.2% of deviance explained. With only three variables used, the second model outperformed the first model evaluated by the AIC value. We conclude that forest patch area, mean temperature of coldest quarter, and precipitation seasonality are the highly influential variables of TSR among environmental factors in the southeastern region of U.S., but evolutionary or historic cause should be further incorporated to fully understand tree species diversity pattern in this region.

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