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L.L. Tieszen

Publications and source records attributed to L.L. Tieszen.

25 records · Page 2Linked to original sources
USGS2002

Using simple environmental variables to estimate below-ground productivity in grasslands

In many temperate and annual grasslands, above-ground net primary productivity (NPP) can be estimated by measuring peak above-ground biomass. Estimates of below-ground net primary productivity and, consequently, total net primary productivity, are more difficult. We addressed one of the three main objectives of the Global Primary Productivity Data Initiative for grassland systems to develop simple models or algorithms to estimate missing components of total system NPP. Any estimate of below-ground NPP (BNPP) requires an accounting of total root biomass, the percentage of living biomass and annual turnover of live roots. We derived a relationship using above-ground peak biomass and mean annual temperature as predictors of below-ground biomass (r2 = 0.54; P = 0.01). The percentage of live material was 0.6, based on published values. We used three different functions to describe root turnover: constant, a direct function of above-ground biomass, or as a positive exponential relationship with mean annual temperature. We tested the various models against a large database of global grassland NPP and the constant turnover and direct function models were approximately equally descriptive (r2 = 0.31 and 0.37), while the exponential function had a stronger correlation with the measured values (r2 = 0.40) and had a better fit than the other two models at the productive end of the BNPP gradient. When applied to extensive data we assembled from two grassland sites with reliable estimates of total NPP, the direct function was most effective, especially at lower productivity sites. We provide some caveats for its use in systems that lie at the extremes of the grassland gradient and stress that there are large uncertainties associated with measured and modelled estimates of BNPP.

Global Ecology and Biogeography↗
USGS2002

Satellite mapping of surface biophysical parameters at the biome scale over the North American grasslands: A case study

Quantification of biophysical parameters is needed by terrestrial process modeling and other applications. A study testing the role of multispectral data for monitoring biophysical parameters was conducted over a network of grassland field sites in the Great Plains of North America. Grassland biophysical parameters [leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fPAR), and biomass] and their relationships with ground radiometer normalized difference vegetation index (NDVI) were established in this study ( r 2 =.66–.85) from data collected across the central and northern Great Plains in 1995. These spectral/biophysical relationships were compared to 1996 field data from the Tallgrass Prairie Preserve in northeastern Oklahoma and showed no consistent biases, with most regression estimates falling within the respective 95% confidence intervals. Biophysical parameters were estimated for 21 “ground pixels” (grids) at the Tallgrass Prairie Preserve in 1996, representing three grazing/burning treatments. Each grid was 30×30 m in size and was systematically sampled with ground radiometer readings. The radiometric measurements were then converted to biophysical parameters and spatially interpolated using geostatistical kriging. Grid-based biophysical parameters were monitored through the growing season and regressed against Landsat Thematic Mapper (TM) NDVI ( r 2 =.92–.94). These regression equations were used to estimate biophysical parameters for grassland TM pixels over the Tallgrass Prairie Preserve in 1996. This method maintained consistent regression development and prediction scales and attempted to minimize scaling problems associated with mixed land cover pixels. A method for scaling Landsat biophysical parameters to coarser resolution satellite data sets (1 km 2 ) was also investigated.

Remote Sensing of Environment↗
USGS2001

Paleoclimate and Amerindians: Evidence from stable isotopes and atmospheric circulation

Two Amerindian demographic shifts are attributed to climate change in the northwest plains of North America: at ???11,000 calendar years before present (yr BP), Amerindian culture apparently split into foothills-mountains vs. plains biomes; and from 8,000-5,000 yr BP, scarce archaeological sites on the open plains suggest emigration during xeric "Altithermal" conditions. We reconstructed paleoclimates from stable isotopes in prehistoric bison bone and relations between weather and fractions of C4 plants in forage. Further, we developed a climate-change model that synthesized stable isotope, existing qualitative evidence (e.g., palynological, erosional), and global climate mechanisms affecting this midlatitude region. Our isotope data indicate significant warming from ???12,400 to 11,900 yr BP, supporting climate-driven cultural separation. However, isotope evidence of apparently wet, warm conditions at 7,300 yr BP refutes emigration to avoid xeric conditions. Scarcity of archaeological sites is best explained by rapid climate fluctuations after catastrophic draining of the Laurentide Lakes, which disrupted North Atlantic Deep Water production and subsequently altered monsoonal inputs to the open plains.

Proceedings of the National Academy of Sciences of↗
USGS1997

NDVI, C3 and C4 production, and distributions in Great Plains grassland land cover classes

The distributions of C 3 and C 4 grasses were used to interpret the distribution, seasonal performance, and potential production of grasslands in the Great Plains of North America. Thirteen major grassland seasonal land cover classes were studied with data from three distinct sources. Normalized Difference Vegetation Index (NDVI) data derived from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) sensor were collected for each pixel over a 5-yr period (1989–1993), analyzed for quantitative attributes and seasonal relationships, and then aggregated by land cover class. Data from the State Soil Geographic (STATSGO) database were used to identify dominant plant species contributing to the potential production in each map unit. These species were identified as C 3 or C 4 , and contributions to production were aggregated to provide estimates of the percentage of C 3 and C 4 production for each intersection of the STATSGO map units and the seasonal land cover classes. Carbon isotope values were obtained at specific sites from the soil organic matter of the upper horizon of soil cores and were related to STATSGO estimates of potential production. The grassland classes were distributed with broad northwest-to-southeast orientations. Some classes had large variations in C 3 and C 4 composition with high proportions of C 4 species in the south and low proportions in the north. This diversity of photosynthetic types within land cover classes that cross regions of different temperature and precipitation results in similar seasonal patterns and magnitudes of NDVI. The easternmost class, 65, containing tallgrass prairie components, bluestem, Indiangrass, and switchgrass, possessed the highest maximum NDVI and time-integrated NDVI values each year. Grassland classes varied over 5 yr from a high integrated NDVI mean of 4.9 in class 65 in the east to a low of 1.2 in class 76 (sand sage, blue grama, wheatgrass, and buffalograss) in the southwest. Although environmental conditions varied widely during the 5 yr, the rankings of class performance were consistent across years for these NDVI metrics. Land cover classes were less consistent in time of onset, which was often earlier in areas in the north dominated by C 3 grasses than in areas to the south dominated by C 4 grasses. At the level of seasonal land cover classes, no significant relationship was found between the proportions of C 3 and C 4 species and estimates of potential production derived from the STATSGO database or inferred from the seasonal patterns of NDVI. The isotopic data from specific sites and the potential production data from STATSGO suggest similar patterns of high proportional production by C 4 species throughout the south and a decline in proportional production north of the central Great Plains. The land cover classes integrate ecosystem units that encompass a wide diversity of species and C 3 and C 4 proportions and provide a classification that consistently captures significant ecosystem parameters for the Great Plains.

Colorado, Kansas, Montana, Nebraska, New Mexico, N↗
USGS1996

An approach for using AVHRR data to monitor U.S. great plains grasslands

Environmental monitoring requires regular observations regarding the status of the landscape- The concept behind most monitoring efforts using satellite data involve deriving normalized difference vegetation index (NDVI) values or accumulating the NDVI over a specified time period. These efforts attempt to estimate the continuous growth of green biomass by using continuous additions of NDVI as a surrogate measure. To build upon this concept, this study proposes three refinements; 1) use an objective definition of the current growing season to adjust the time window during which the NDVI is accumulated, 2) accumulate only the NDVI values which are affected by green vegetation, and 3) base monitoring units upon land cover type. These refinements improve the sensitivity of detecting interannual vegetation variability, reduce the need for extensive and detailed knowledge of ground conditions and crop calendars, provide a framework in which several types of monitoring can take place over diverse land cover types, and provide an objective time frame during which monitoring takes place.

Geocarto International↗