Stable Nitrogen and Carbon Pools in Grassland Soils of Variable Texture and Carbon Content

Nitrogen (N) inputs to many terrestrial ecosystems are increasing, and most of these inputs are sequestered in soil organic matter within 1–3 years. Rapid (minutes to days) immobilization focused previous N retention research on actively cycling plant, microbial, and inorganic N pools. However, most ecosystem N resides in soil organic matter that is not rapidly cycled. This large, stable soil N pool may be an important sink for elevated N inputs. In this study, we measured the capacity of grassland soils to retain ¹⁵N in a pool that was not mineralized by microorganisms during 1-year laboratory incubations (called “the stable pool”). We added two levels (2.5 and 50 g N m⁻²) of ¹⁵NH₄ ⁺ tracer to 60 field plots on coarse- and fine-textured soils along a soil carbon (C) gradient from Texas to Montana, USA. We hypothesized that stable tracer ¹⁵N retention and stable bulk soil (native + tracer) N pools would be positively correlated with soil clay and C content and stable soil C pools (C not respired during the incubation). Two growing seasons after the ¹⁵N addition, soils (0- to 20-cm depth) contained 71% and 26% of the tracer added to low- and high-N treatments, respectively. In both N treatments, 50% of the tracer retained in soil was stable. Total soil C (r ² = 0.72), stable soil C (r ² = 0.68), and soil clay content (r ² = 0.27) were correlated with stable bulk soil N pools, but not with stable ¹⁵N retention. We conclude that on annual time scales, substantial quantities of N are incorporated into stable organic pools that are not readily susceptible to microbial remineralization or subsequent plant uptake, leaching losses, or gaseous losses. Stable N formation may be an important pathway by which rapid soil N immobilization translates into long-term N retention. Received 2 April 2001; accepted 12 November 2001.     

Integration of CO2 flux and remotely-sensed data for primary production and ecosystem respiration analyses in the Northern Great Plains: potential for quantitative spatial extrapolation

Aim Extrapolation of tower CO₂ fluxes will be greatly facilitated if robust relationships between flux components and remotely sensed factors are established. Long‐term measurements at five Northern Great Plains locations were used to obtain relationships between CO₂ fluxes and photosynthetically active radiation (Q), other on‐site factors, and Normalized Difference Vegetation Index (NDVI) from the SPOT VEGETATION data set. Location CO₂ flux data from the following stations and years were analysed: Lethbridge, Alberta 1998–2001; Fort Peck, MT 2000, 2002; Miles City, MT 2000–01; Mandan, ND 1999–2001; and Cheyenne, WY 1997–98. Results Analyses based on light‐response functions allowed partitioning net CO₂ flux (F) into gross primary productivity (P_g) and ecosystem respiration (R_e). Weekly averages of daytime respiration, γ_day, estimated from light responses were closely correlated with weekly averages of measured night‐time respiration, γ_night (R² 0.64 to 0.95). Daytime respiration tended to be higher than night‐time respiration, and regressions of γ_day on γ_night for all sites were different from 1 : 1 relationships. Over 13 site‐years, gross primary production varied from 459 to 2491 g CO₂ m^?2 year^?1, ecosystem respiration from 996 to 1881 g CO₂ m^?2 year^?1, and net ecosystem exchange from ?537 (source) to +610 g CO₂ m^?2 year^?1 (sink). Maximum daily ecological light‐use efficiencies, ?_d,max = P_g/Q, were in the range 0.014 to 0.032 mol CO₂ (mol incident quanta)^?1. Main conclusions Ten‐day average P_g was significantly more highly correlated with NDVI than 10‐day average daytime flux, P_d (R² = 0.46 to 0.77 for P_g‐NDVI and 0.05 to 0.58 for P_d‐NDVI relationships). Ten‐day average R_e was also positively correlated with NDVI, with R² values from 0.57 to 0.77. Patterns of the relationships of P_g and R_e with NDVI and other factors indicate possibilities for establishing multivariate functions allowing scaling‐up local fluxes to larger areas using GIS data, temporal NDVI, and other factors.     

Use of climatic data and satellite imagery to model the abundance of Culicoides imicola, the vector of African horse sickness virus, in Morocco

African horse sickness (AHS) is a vector-borne, infectious disease of equids caused by African horse sickness virus (AHSV) . The only proven field vector of the virus is the biting midge Culicoides imicola. Following a recent epizootic (1989–91) of AHS in Morocco, light traps and automatic weather stations were operated for 2 years at twenty-two sites distributed over much of the country. The annually-averaged mean daily trap catch of C. imicola at these sites was negatively correlated with wind speed, and positively correlated with the average and mean annual minimum NDVI (Normalized Difference Vegetation Index, a remotely sensed measure of vegetation activity). There were no significant correlations between the mean daily trap catch and air temperature, soil temperature, relative humidity, saturation deficit, rainfall, altitude or the mean annual maximum or range of NDVI. The best two-variable model, which combined Windspeed_MnAvMn (the average daily minimum wind speed of the least windy month) and NDVI_min (the average annual minimum NDVI) as predictors, explained over 50% of the variance in the annually-averaged mean daily trap catch of C. imicola. There was a significant, positive correlation between minimum wind speed at night and the daily mortality rate of adult female C. imicola and it is suggested that the relationship between wind speed and the abundance of C. imicola arises from effects on adult mortality or dispersal. Considering several climatic variables, in North Africa NDVI_min was most significantly correlated with total annual rainfall. It is suggested that the relationship between NDVI_min and the abundance of C. imicola arises from the impact of soil moisture on both. It is proposed that areas of Morocco with higher levels of soil moisture in late summer or autumn provide more, larger and/or more enduring breeding sites for C. imicola, as well as supporting more photosynthetically active vegetation and hence having higher NDVI.     

Fish-habitat relationship in a tropical river under anthropogenic influences

This study analyzes the interaction of fish assemblages with 14 physicochemical and hydrogeomorphological variables at 31 sampling stations along the watershed of the Meia Ponte River, Upper Paraná Basin, Central Brazil, during low and high water seasons in 2001. This river and its tributaries drain both urban and agricultural areas. Fish were caught with sieves along a 100 m stretch demarcated in every sampling site, where environmental variables were also measured. A total of 3508 individuals belonging to 31 species were collected. Fish abundance and environmental data matrices were submitted to a multivariate analysis of co-inertia. Two axes were retained for interpretation (total variance explained = 63.65%) indicating that pH, water temperature, conductivity, chemical dissolved oxygen, and turbidity, all have an influence on fish assemblage structure. The co-structure found (fish assemblages and physicochemical variables) is correlated in both of the axes considered (r = 0.73 and r = 0.68, respectively), and is statistically significant (Monte Carlo test, P < 0.001). This co-structure is regulated by seasonality, but is influenced by fish habitat preferences, spawning and available food, the extent and effects of anthropogenic activities (domestic sewage, agriculture, ranching, urban areas) and the position of sampling stations along the watershed. Handling editor: S. M. Thomaz     

Accuracy of the AVHRR vegetation index as a predictor of biomass,primary productivity and net CO2 flux

The Normalized Difference Vegetation Index (NDVI) or greenness index, based on the Advanced Very High Resolution Radiometer (AVHRR) aboard the NOAA-7 satellite, has been widely interpreted as a measure of regional to global vegetation patterns. This study provides the first rigorous, quantitative evaluation of global relationships between the NDVI and geographically representative vegetation data-bases, including field metabolic measurements and carbon-balance results from global simulation models. Geographic reliability of the NDVI is judged by comparing NDVI values for different surface types with a general global trend and by statistical analysis of relationships to biomass amounts, net and gross primary productivity, and actual evapotranspiration. NDVI data appear to be relatively reliable predictors of primary productivity except in areas of complex terrain, for seasonal values at high latitudes, and in extreme deserts. The strength of the NDVI-productivity relationship seems comparable to that of earlier climate-based productivity models. Little consistent relationship was found, across different vegetation types, between NDVI and biomass amounts or net biospheric CO₂ flux.Abbreviations AET= Actual Evapotranspiration - AVHRR= Advanced Very High Resolution Radiometer - GPP= Gross Primary Production - GVI= Global Vegetation Index - NDVI= Normalized Difference Vegetation Index - NPP= Net Primary Production     

Hydrologic gradient and vegetation controls on CH4 and CO2 fluxes in a spring-fed forested wetland

Four different habitats in a spring-fed forested wetland (Clear Springs Wetland, Panola County, Mississippi, USA) varying in hydrologic regime were examined for methane and carbon dioxide fluxes from soils over 15 and 9 months, respectively. There was an increasing gradient of CH₄ flux rates from an unflooded upper-elevation forest site to an occasionally flooded bottomland forest site to a shallow permanently flooded site, and then to a deeper-water permanently flooded site. Depending on the time of year, all sites were sources of methane but only at the upper-elevation forest site, when gravimetric soil moisture content fell below 54%, was atmospheric methane consumed. On average, summer CH₄ emission rates were higher than those in other seasons. A multiple regression model with soil temperature and soil redox potential as independent variables could explain 65% of the variation in CH₄ flux rates. In the flooded zone, variation in CH₄ flux rates was correlated with aboveground plant biomass and stem density of emergent vascular plants, and plant-mediated CH₄ transport depended on plant type. The efflux of CH₄ to plant biomass (Eff:B) ratio was generally lower in Hydrocotyle umbellata compared to Festuca obtusa. Compared to several other freshwater forested wetlands in the southeastern USA, this spring-fed forested wetland ecosystem was a strong source of atmospheric CH₄, likely due to a long hydroperiod and high soil organic matter content. Carbon dioxide fluxes show a reverse spatial pattern than CH₄ fluxes with highest CO₂ emissions in the non-flooded zone at all times of the year, indicating the dominance of aerobic soil respiration. A multiple regression model also revealed a strong dependency of CO₂ fluxes (r ² = 0.73) on soil temperature and soil redox potential. Handling editor: J. M. Melack     

Two classification methods for developing and interpreting productivity zones using site properties

Crop performance is often shown as areas of differing grain yield. Many producers utilize simple GIS color ramping techniques to produce visual yield maps with delineated clusters. However, a more quantitative approach such as an unsupervised clustering procedure is generally used by scientists since it is much less arbitrary. Intuitively the yield clusters are due to soil and terrain properties, but there is no clear criterion for the delineation. We compared the effectiveness of two delineation or classification procedures: quadratic discriminant analysis (QDA) and k-nearest neighbor discriminant analysis (k-NN) for the study of how yield temporal patterns relate to site properties. This study used three production fields, one in Monticello, IL, and two in Centralia, MO. Clusters were defined using maize (Zea mays L.) and soybean (Glycine max (L.) Merr.) yield from three seasons. The k-NN had greater and more consistent successful classification rates than did QDA. Classification success rate varied from 0.465 to 0.790 for QDA while the k-NN classification rate varied from 0.794 to 0.874. This shows that areas of certain temporal yield patterns correspond to areas of specific site properties. Although profiles of site properties differ by crop and production field, areas of consistent low maize yield had greater shallow electrical conductivity (EC_shallow), than those of consistent high maize yield. Furthermore, areas of consistent high soybean yield had lower soil reflectance than those areas of consistent low yields.     

Allelopathy in black walnut (Juglans nigraL.) alley cropping. II. Effects of juglone on hydroponically grown corn (Zea maysL.) and soybean (Glycine maxL. Merr.) growth and physiology

We conducted an experiment to investigate the effects of juglone (5-hydroxy-1, 4-napthoquinone) on the growth and physiology of hydroponically grown corn (Zea mays L.) and soybean (Glycine max L. Merr.) seedlings. Three different concentrations of juglone (10^-6 M, 10^-5 M, and 10^-4 M) along with a control were applied. Within 3 days, juglone exhibited significant inhibitory effects on all measured variables including shoot and root relative growth rates (RGR_s and RGR_r), leaf photosynthesis (P_net), transpiration (E), stomatal conductance (g_s), and leaf and root respiration. In general, soybean was found to be more sensitive to juglone than corn. RGR_r was the most inhibited variable for both species, and reductions of 86.5 and 99% were observed in corn and soybean, respectively, with 10_-4 M juglone concentrations. Among the physiological variables measured, P_net showed the greatest impact of toxicity though the other physiological parameters were also impacted. We conclude that both corn and soybean are sensitive to juglone and observed growth reductions in corn and soybean in black walnut alley cropping may partly be due to juglone phytotoxicity. Determination of actual phytotoxicity will require quantification of soil solution juglone levels, particularly in areas where soil solid-phase levels are high in close proximity to trees.     

Soil organic carbon dynamics jointly controlled by climate,carbon inputs,soil properties and soil carbon fractions

Soil organic carbon (SOC) dynamics are regulated by the complex interplay of climatic, edaphic and biotic conditions. However, the interrelation of SOC and these drivers and their potential connection networks are rarely assessed quantitatively. Using observations of SOC dynamics with detailed soil properties from 90 field trials at 28 sites under different agroecosystems across the Australian cropping regions, we investigated the direct and indirect effects of climate, soil properties, carbon (C) inputs and soil C pools (a total of 17 variables) on SOC change rate (r_C, Mg C ha^?1 yr^?1). Among these variables, we found that the most influential variables on r_C were the average C input amount and annual precipitation, and the total SOC stock at the beginning of the trials. Overall, C inputs (including C input amount and pasture frequency in the crop rotation system) accounted for 27% of the relative influence on r_C, followed by climate 25% (including precipitation and temperature), soil C pools 24% (including pool size and composition) and soil properties (such as cation exchange capacity, clay content, bulk density) 24%. Path analysis identified a network of intercorrelations of climate, soil properties, C inputs and soil C pools in determining r_C. The direct correlation of r_C with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa. These results reveal the relative importance of climate, soil properties, C inputs and C pools and their complex interconnections in regulating SOC dynamics. Ignorance of the impact of changes in soil properties, C pool composition and C input (quantity and quality) on SOC dynamics is likely one of the main sources of uncertainty in SOC predictions from the process‐based SOC models.     

Remote sensing of protected areas to derive baseline vegetation functioning characteristics

Question: How can we derive baseline/reference situations to evaluate the impact of global change on terrestrial ecosystem functioning? Location: Main biomes (steppes to rain forests) of Argentina. Methods: We used AVHRR/NOAA satellite data to characterize vegetation functioning. We used the seasonal dynamics of the Normalized Difference Vegetation Index (NDVI), a linear estimator of the fraction of the photosynthetic active radiation intercepted by vegetation (f_PAR), and the surface temperature (Ts), for the period 1981–1993. We extracted the following indices: NDVI integral (NDVI‐I), NDVI relative range (R_rel), NDVI maximum value (V_max), date of maximum NDVI (D_max) and actual evapotranspiration. Results: f _PAR varied from 2 to 80%, in relation to changes in net primary production (NPP) from 83 to 1700 g.m‐².yr^‐1. NDVI‐I, Vmax and f_PAR had positive, curvilinear relationships to mean annual precipitation (MAP), NPP was linearly related to MAP. Tropical and subtropical biomes had a significantly lower seasonality (R_rel) than temperate ones. D_max was not correlated with the defined environmental gradients. Evapotranspiration ranged from 100 to 1100 mm.yr^‐1. Interannual variability of NDVI attributes varied across the temperature and precipitation gradients. Conclusions: Our results may be used to represent baseline conditions in evaluating the impact of land use changes across environmental gradients. The relationships between functional attributes and environmental variables provide a way to extrapolate ecological patterns from protected areas across modified habitats and to generate maps of ecosystem functioning.     

Modeling Symbiotic Performance of Introduced Rhizobia in the Field by Use of Indices of Indigenous Population Size and Nitrogen Status of the Soil

The ability to predict the symbiotic performance of rhizobia introduced into different environments would allow for a more judicious use of rhizobial inoculants. Data from eight standardized field inoculation trials were used to develop models that could be used to predict the success of rhizobial inoculation in diverse environments based on indices of the size of indigenous rhizobial populations and the availability of mineral N. Inoculation trials were conducted at five diverse sites on the island of Maui, Hawaii, with two to four legumes from among nine species, yielding 29 legume-site observations. The sizes of indigenous rhizobial populations were determined at planting. Soil N mineralization potential, total soil N, N accumulation and seed yield of nonnodulating soybean, and N derived from N₂ fixation in inoculated soybean served as indices of available soil N. Uninoculated, inoculated, and fertilizer N treatments evaluated the impact of indigenous rhizobial populations and soil N availability on inoculation response and crop yield potential. The ability of several mathematical models to describe the inverse relationship between numbers of indigenous rhizobia and legume inoculation responses was evaluated. Power, exponential, and hyperbolic functions yielded similar results; however, the hyperbolic equation provided the best fit of observed to estimated inoculation responses (r² = 0.59). The fact that 59% of the observed variation in inoculation responses could be accounted for by the relationship of inoculation responses to numbers of indigenous rhizobia illustrates the profound influence that the size of soil rhizobial populations has on the successful use of rhizobial inoculants. In the absence of indigenous rhizobia, the inoculation response was directly proportional to the availability of mineral N. Therefore, the hyperbolic response function was subsequently combined with several indices of soil N availability to generate models for predicting legume inoculation response. Among the models developed, those using either soil N mineralization potential or N derived from N₂ fixation in soybean to express the availability of mineral N were most useful in predicting the success of legume inoculation. Correlation coefficients between observed and estimated inoculation responses were r = 0.83 for the model incorporating soil N mineralization potential and r = 0.96 for the model incorporating N derived from N₂ fixation. Several equations collectively termed “soil N deficit factors” were also found to be useful in estimating inoculation responses. In general, models using postharvest indices of soil N were better estimators of observed inoculation responses than were those using laboratory measures of soil N availability. However, the latter, while providing less precise estimates, are more versatile because all input variables can be obtained through soil analysis prior to planting. These models should provide researchers, as well as regional planners, with a more precise predictive capability to determine the inoculation requirements of legumes grown in diverse environments.     

Topographic and climatic controls on soil respiration in six temperate mixed-hardwood forest slopes, Korea

To better understand the effects of local topography and climate on soil respiration, we conducted field measurements and soil incubation experiments to investigate various factors influencing spatial and temporal variations in soil respiration for six mixed‐hardwood forest slopes in the midst of the Korean Peninsula. Soil respiration and soil water content (SWC) were significantly greater (P=0.09 and 0.003, respectively) on north‐facing slopes compared to south‐facing slopes, while soil temperature was not significantly different between slopes (P>0.5). At all sites, soil temperature was the primary factor driving temporal variations in soil respiration (r²=0.84–0.96) followed by SWC, which accounted for 30% of soil respiration spatial and temporal variability. Results from both field measurements and incubation experiments indicate that variations in soil respiration due to aspect can be explained by a convex‐shaped function relating SWC to normalized soil respiration rates. Annual soil respiration estimates (1070–1246 g C m^?2 yr^?1) were not closely related to mean annual air temperatures among sites from different climate regimes. When soils from each site were incubated at similar temperatures in a laboratory, respiration rates for mineral soils from wetter and cooler sites were significantly higher than those for the drier and warmer sites (n=4, P<0.01). Our results indicate that the application of standard temperature‐based Q₁₀ models to estimate soil respiration rates for larger geographic areas covering different aspects or climatic regimes are not adequate unless other factors, such as SWC and total soil nitrogen, are considered in addition to soil temperature.     

Effects of Obesity and Body Fat Distribution on Lipids and Lipoproteins in Nondiabetic American Indians: The Strong Heart Study

Objectives: To examine the relationship between obesity and lipoprotein profiles and compare the effects of total obesity and central adiposity on lipids/lipoproteins in American Indians. Research Methods and Procedures: Participants were 773 nondiabetic American Indian women and 739 men aged 45 to 74 years participating in the Strong Heart Study. Total obesity was estimated using body mass index (BMI). Central obesity was measured as waist circumference. Lipoprotein measures included triglycerides, high‐density lipoprotei in (HDL) cholesterol, low‐density lipoprotein (LDL) cholesterol, apolipoprotein AI (apoAI), and apolipoprotein B (apoB). Partial and canonical correlation analyses were used to examine the associations between obesity and lipids/lipoproteins. Results: Women were more obese than men in Arizona (median BMI 32.1 vs. 29.2 kg/m²) and South Dakota and North Dakota (28.3 vs. 28.0 kg/m²), but there was no sex difference in waist circumference. Men had higher apoB and lower apoAI levels than did women. In women, when adjusted for center, gender, and age, BMI was significantly related to HDL cholesterol (r = ?0.24, p < 0.001). There was a significant but weak relation with apoAI (r = ?0.14 p < 0.001). Waist circumference was positively related to triglycerides (r = 0.14 p < 0.001) and negatively related to HDL cholesterol (r = ?0.23, p < 0.001) and apoAI (r = ?0.13, p < 0.001). In men, BMI was positively correlated with triglycerides (r = 0.30, p < 0.001) and negatively correlated with HDL cholesterol (r = ?0.35, p < 0.001) and apoAI (r = ?0.23, p < 0.001). Triglycerides increased with waist circumference (r = 0.30, p < 0.001) and HDL cholesterol decreased with waist circumference (r = ?0.36 p < 0.001). In both women and men there was an inverted U‐shaped relationship between obesity and waist with LDL cholesterol and apoB. In canonical correlation analysis, waist circumference received a greater weight (0.86) than did BMI (0.17) in women. However, the canonical weights were similar for waist (0.46) and BMI (0.56) in men. Only HDL cholesterol (?1.02) carried greater weight in women, whereas in men, triglycerides (0.50), and HDL cholesterol (?0.64) carried a large amount of weight. All the correlation coefficients between BMI, waist circumference, and the first canonical variable of lipids/lipoproteins or between the individual lipid/lipoprotein variables and the first canonical variable of obesity were smaller in women than in men. Triglycerides and HDL cholesterol showed clinically meaningful changes with BMI and waist circumference in men. All lipid/lipoprotein changes in women in relation to BMI and waist circumference were minimal. Discussion: The main lipoprotein abnormality related to obesity in American Indians was decreased HDL cholesterol, especially in men. Central adiposity was more associated with abnormal lipid/lipoprotein profiles than general obesity in women; both were equally important in men.     

Assessing the performance of NDVI as a proxy for plant biomass using non-linear models: a case study on the Kerguelen archipelago

Numerous ecological studies, including of the polar environment, are now using the remotely sensed normalized difference vegetation index (NDVI, e.g. PAL-NDVI or MODIS-NDVI) as a proxy of vegetation productivity rather than performing direct vegetation assessments. Even though previous data strongly suggested a saturation of NDVI at high biomass values, few studies have explicitly included this characteristic in the modelling process. Here, we developed a generalized non-linear model to explicitly model the relationship between temporal variations of NDVI (Pathfinder AVHRR Land 8 km dataset) and empirical field data. We illustrated our approach on the Kerguelen archipelago by using a green biomass index (point-intercept protocol) sampled at a small scale relative to PAL-NDVI data, and in presence of spatial (water) and temporal (cloud contamination, snow) heterogeneity, i.e. field conditions encountered in many ecological studies. We showed a strong relationship (r _pred.obs = 0.89 [0.77; 0.95]_95%) between this index and the seasonal component of NDVI time series (NDVI_comp). Despite the absence of lignified species in the stand, the NDVI_comp reached an asymptote (0.54 ± 0.05) for high values of green biomass index stressing the need to account for non-linearity when relating NDVI and plant measurements. We provided here a new methodological framework to standardize comparisons between studies assessing performance of NDVI as a proxy of vegetation data.

Genetic Variation for Adaptive Traits in Bottlebrush Squirreltail in the Northern Intermountain West,United States

Adaptive‐trait correlations in plant ecology are often calculated among species, but in order to develop and characterize plant materials of target species for restoration, intraspecific comparisons are of greatest relevance. Elymus elymoides (Raf.) Swezey (bottlebrush squirreltail) is an important component of sagebrush‐steppe communities in the northern Intermountain West, United States. We evaluated 32 accessions of E. elymoides subspecies C, a newly recognized unnamed taxon, in the field and greenhouse. Our objectives were to assess genetic diversity for putatively adaptive traits, to elucidate biological relationships among biomass, morphological, and phenological traits through correlation analysis, and to gather evidence suggesting whether these traits might be truly adaptive, that is, related to collection‐site variables. We observed a positive correlation (r = 0.73;p < 0.01) between greenhouse shoot and root biomass among accessions, suggesting that shoot and root biomass are not in an inherent trade‐off relationship across accessions. In addition, accessions with higher greenhouse shoot biomass possessed lower specific leaf area (r = ?0.43;p < 0.05) and lower specific root length (r = ?0.47,p < 0.05). Correlations between greenhouse and field‐measured productivity traits were not significant (p > 0.05), indicating seedling performance is not predictive of mature‐plant performance. Elevation was the collection‐site variable most closely correlated with plant‐measured traits, particularly phenological dates, whereas average annual precipitation was the least significant variable. Therefore, elevation may be used as an easily applied metric to match subspecies C plant material to restoration site in the northern Intermountain West.     

NDVI saturation adjustment: A new approach for improving cropland performance estimates in the Greater Platte River Basin,USA

In this study, we developed a new approach that adjusted normalized difference vegetation index (NDVI) pixel values that were near saturation to better characterize the cropland performance (CP) in the Greater Platte River Basin (GPRB), USA. The relationship between NDVI and the ratio vegetation index (RVI) at high NDVI values was investigated, and an empirical equation for estimating saturation-adjusted NDVI (NDVI_sat__adjust) based on RVI was developed. A 10-year (2000–2009) NDVI_sat__adjust data set was developed using 250-m 7-day composite historical eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. The growing season averaged NDVI (GSN), which is a proxy for ecosystem performance, was estimated and long-term NDVI non-saturation- and saturation-adjusted cropland performance (CP_non__sat__adjust, CP_sat__adjust) maps were produced over the GPRB. The final CP maps were validated using National Agricultural Statistics Service (NASS) crop yield data. The relationship between CP_sat__adjust and the NASS average corn yield data (r = 0.78, 113 samples) is stronger than the relationship between CP_non__sat__adjust and the NASS average corn yield data (r = 0.67, 113 samples), indicating that the new CP_sat__adjust map reduces the NDVI saturation effects and is in good agreement with the corn yield ground observations. Results demonstrate that the NDVI saturation adjustment approach improves the quality of the original GSN map and better depicts the actual vegetation conditions of the GPRB cropland systems.     

Seasonal changes in the contribution of root respiration to total soil respiration in a cool-temperate deciduous forest

A trenching method was used to determine the contribution of root respiration to soil respiration. Soil respiration rates in a trenched plot (R _trench) and in a control plot (R _control) were measured from May 2000 to September 2001 by using an open-flow gas exchange system with an infrared gas analyser. The decomposition rate of dead roots (R _D) was estimated by using a root-bag method to correct the soil respiration measured from the trenched plots for the additional decaying root biomass. The soil respiration rates in the control plot increased from May (240–320 mg CO₂ m^–2 h^–1) to August (840–1150 mg CO₂ m^–2 h^–1) and then decreased during autumn (200–650 mg CO₂ m^–2 h^–1). The soil respiration rates in the trenched plot showed a similar pattern of seasonal change, but the rates were lower than in the control plot except during the 2 months following the trenching. Root respiration rate (R _r) and heterotrophic respiration rate (R _h) were estimated from R _control, R _trench, and R _D. We estimated that the contribution of R _r to total soil respiration in the growing season ranged from 27 to 71%. There was a significant relationship between R _h and soil temperature, whereas R _r had no significant correlation with soil temperature. The results suggest that the factors controlling the seasonal change of respiration differ between the two components of soil respiration, R _r and R _h.     

Seed quality QTLs identified in a molecular map of early maturing soybean

This study identified QTLs influencing seed quality characters in a cross of two early maturing soybean (Glycine max [L.] Merr.) cultivars (Ma.Belle and Proto) adapted to the short growing seasons of Central Europe. A molecular linkage map was constructed by using 113 SSR, 6 RAPD and 1 RFLP markers segregating in 82 individuals of an F₂ population. The map consists of 23 linkage groups and corresponds wellto previously published soybean maps. Using phenotypic data of the F₂-derived lines grown in five environments, four markers for protein content, three for oil content and eight for seed weight were identified. Four from fifteen seed quality QTL-regions identified in the present study were also found by other authors. Markers associated with seed weight QTLs were consistent across all environments and proved to have effects large enough to be useful in a marker-assisted breeding program, whereas protein and oil QTLs showed environmental interactions. Received: 9 October 2000 / Accepted: 26 February 2001     

Regulation of advanced glycation end product (AGE) receptors and apoptosis by AGEs in osteoblast-like cells

It has been reported that apelin functions as an adipokine, which has been associated to obesity and insulin resistance. The objective of this study was to analyze the apelin mRNA expression in white adipose tissue (WAT) from high-fat (Cafeteria) fed rats, in order to examine potential relationships with obesity markers and other related risk factors. Animals fed on the high-fat diet during 56 days increased their body weight, total body fat and WAT depots weights when compared to controls. Apelin subcutaneous mRNA expression was higher in the Cafeteria than in the Control fed group and this increase was partially reversed by dietary vitamin C supplementation. Statistically significant associations between subcutaneous apelin gene expression and almost all the studied variables were identified, being of special interest the correlations found with serum leptin (r = 0.517), liver malondialdehyde (MDA) levels (r = 0.477), and leptin, IRS-3 and IL-1ra retroperitoneal mRNA expression (r = 0.701; r = 0.692 and r = 0.561, respectively). These associations evidence a possible role for apelin in the excessive weight gain induced by high-fat feeding and increased adiposity, insulin-resistance, liver oxidative stress and inflammation.     

Modulation of respiratory metabolism in response to nutrient changes along a soil chronosequence

Laboratory studies indicate that plant respiratory efficiency may decrease in response to low nutrient availability due to increased partitioning of electrons to the energy‐wasteful alternative oxidase (AOX); however, field confirmation of this hypothesis is lacking. We therefore investigated plant respiratory changes associated with succession and retrogression in soils aged from 10 to 120 000 years along the Franz Josef soil chronosequence, New Zealand. Respiration rates and electron partitioning were determined based on oxygen isotopic fractionation. Leaf structural traits, foliar nutrient status, carbohydrates and species composition were measured as explanatory variables. Although soil nutrient levels and species composition varied by site along the chronosequence, foliar respiration across all sites and species corresponded strongly with leaf nitrogen concentration (r² = 0.8). In contrast, electron partitioning declined with increasing nitrogen/phosphorus (r² = 0.23) and AOX activity correlated with phosphorus (r² = 0.64). Independently, total respiration was further associated with foliar Cu, possibly linked to its effect on AOX. Independent control of AOX and cytochrome pathway activities is also discussed. These responses of plant terminal respiratory oxidases – and therefore respiratory carbon efficiency – to multiple nutrient deficiencies demonstrate that modulation of respiratory metabolism may play an important role in plant responses to nutrient gradients.