00503nas a2200145 4500008004100000245011900041210007100160300000900231490000700240100001600247700001700263700001400280700001700294856004600311 2023 eng d00aDynamic plant–herbivore interactions between bison space use and vegetation heterogeneity in a tallgrass prairie0 aDynamic plant–herbivore interactions between bison space use and a52690 v151 aLing, Bohua1 aRaynor, E.J.1 aJoern, A.1 aGoodin, D.G. uhttps://www.mdpi.com/2072-4292/15/22/526902743nas a2200217 4500008004100000245008300041210006900124490000700193520201500200653000902215653003002224653002302254653002002277653002602297653002102323100001302344700001702357700001702374700001902391856011502410 2019 eng d00aEffects of fire and large herbivores on canopy nitrogen in a tallgrass prairie0 aEffects of fire and large herbivores on canopy nitrogen in a tal0 v113 a

This study analyzed the spatial heterogeneity of grassland canopy nitrogen in a tallgrass prairie with different treatments of fire and ungulate grazing (long-term bison grazing vs. recent cattle grazing). Variogram analysis was applied to continuous remotely sensed canopy nitrogen images to examine the spatial variability in grassland canopies. Heterogeneity metrics (e.g., the interspersion/juxtaposition index) were calculated from the categorical canopy nitrogen maps and compared among fire and grazing treatments. Results showed that watersheds burned within one year had higher canopy nitrogen content and lower interspersions of high-nitrogen content patches than watersheds with longer fire intervals, suggesting an immediate and transient fire effect on grassland vegetation. In watersheds burned within one year, high-intensity grazing reduced vegetation density, but promoted grassland heterogeneity, as indicated by lower canopy nitrogen concentrations and greater interspersions of high-nitrogen content patches at the grazed sites than at the ungrazed sites. Variogram analyses across watersheds with different grazing histories showed that long-term bison grazing created greater spatial variability of canopy nitrogen than recent grazing by cattle. This comparison between bison and cattle is novel, as few field experiments have evaluated the role of grazing history in driving grassland heterogeneity. Our analyses extend previous research of effects from pyric herbivory on grassland heterogeneity by highlighting the role of grazing history in modulating the spatial and temporal distribution of aboveground nitrogen content in tallgrass prairie vegetation using a remote sensing approach. The comparison of canopy nitrogen properties and the variogram analysis of canopy nitrogen distribution provided by our study are useful for further mapping grassland canopy features and modeling grassland dynamics involving interplays among fire, large grazers, and vegetation communities.

10afire10agrassland canopy nitrogen10agrassland dynamics10agrazing history10aSpatial heterogeneity10aUngulate grazing1 aLing, B.1 aRaynor, E.J.1 aGoodin, D.G.1 aJoern, Anthony uhttps://www.mdpi.com/2072-4292/11/11/1364?fbclid=IwAR3lLrrJFA3JBzN5IcRlRx-Gn7S_f-9nclPRB4H7IdDHxYQe34Ric_mraDs02178nas a2200205 4500008004100000245010100041210006900142490000700211520149900218653002701717653001801744653002501762653001901787653002201806100001501828700001701843700002301860700001901883856007001902 2019 eng d00aHyperspectral analysis of leaf pigments and nutritional elements in tallgrass prairie vegetation0 aHyperspectral analysis of leaf pigments and nutritional elements0 v103 a

Understanding the spatial distribution of forage quality is important to address critical research questions in grassland science. Due to its efficiency and accuracy, there has been a widespread interest in mapping the canopy vegetation characteristics using remote sensing methods. In this study, foliar chlorophylls, carotenoids, and nutritional elements across multiple tallgrass prairie functional groups were quantified at the leaf level using hyperspectral analysis in the region of 470–800 nm, which was expected to be a precursor to further remote sensing of canopy vegetation quality. A method of spectral standardization was developed using a form of the normalized difference, which proved feasible to reduce the interference from background effects in the leaf reflectance measurements. Chlorophylls and carotenoids were retrieved through inverting the physical model PROSPECT 5. The foliar nutritional elements were modeled empirically. Partial least squares regression was used to build the linkages between the high-dimensional spectral predictor variables and the foliar biochemical contents. Results showed that the retrieval of leaf biochemistry through hyperspectral analysis can be accurate and robust across different tallgrass prairie functional groups. In addition, correlations were found between the leaf pigments and nutritional elements. Results provided insight into the use of pigment-related vegetation indices as the proxy of plant nutrition quality.

10aHyperspectral analysis10aLeaf pigments10aNutritional elements10aremote sensing10atallgrass prairie1 aLing, B.H.1 aGoodin, D.G.1 aRaynor, Edward, J.1 aJoern, Anthony uhttps://www.frontiersin.org/articles/10.3389/fpls.2019.00142/full00494nas a2200121 4500008004100000245011200041210006900153260004300222490002200265100001500287700001700302856005300319 2018 eng d00aRemote sensing of vegetation characteristics and spatial analysis of pyric herbivory in a Tallgrass Prairie0 aRemote sensing of vegetation characteristics and spatial analysi aManhattan, KSbKansas State University0 vPhD. Dissertation1 aLing, B.H.1 aGoodin, D.G. uhttp://krex.k-state.edu/dspace/handle/2097/3909102673nas a2200181 4500008004100000245008000041210006900121490000600190520210100196100001702297700001902314700001702333700001502350700001902365700001502384700001702399856007502416 2017 eng d00aTemporal variability in large grazer space use in an experimental landscape0 aTemporal variability in large grazer space use in an experimenta0 v83 aLand use, climate change, and their interaction each have great potential to affect grazing systems. With anticipated more frequent and extensive future drought, a more complete understanding of the mechanisms that determine large grazer landscape-level distribution under varying climatic conditions is integral to ecosystem management. Using an experimental setting with contrasting fire treatments, we describe the inter-annual variability of the effect of landscape topography and disturbance from prescribed spring fire on large grazer space use in years of variable resource availability. Using GPS telemetry, we investigated space use of plains bison (Bison bison bison) as they moved among watersheds managed with variable experimental burn treatments (1-, 2-, 4-, and 20-year burn intervals) during a seven-year period spanning years of average-to-above average forage production and severe drought. At the landscape scale, bison more strongly favored high-elevation and recently burned watersheds with watersheds burned for the first time in 2 or 4 yr consistently showing higher use relative to annually burned watersheds. In particular, watersheds burned for the first time in 4 yr were avoided to lesser extent than other more frequently burned watersheds during the dormant season. This management type also maintained coupling between bison space use and post-fire regrowth across post-drought growing season months, whereas watersheds with more frequent fire-return intervals attracted bison in only the first month post-fire. Hence, fire frequency played a role in maintaining the coupling of grazer and post-fire regrowth, the fire–grazer interaction, in response to drought-induced reduction in fuel loads. Moreover, bison avoided upland habitat in poor forage production years, when forage regrowth is less likely to occur in upland than in lowland habitats. Such quantified responses of bison to landscape features can aid future conservation management efforts and planning to sustain fire–grazer interactions and resulting spatial heterogeneity in grassland ecosystems.1 aRaynor, E.J.1 aJoern, Anthony1 aSkibbe, A.M.1 aSowers, M.1 aBriggs, J., M.1 aLaws, A.N.1 aGoodin, D.G. uhttps://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/ecs2.167402806nas a2200253 4500008004100000245012700041210006900168300001400237490000700251520198600258653002402244653001602268653002102284653001802305653001502323653001902338100001802357700001902375700001702394700001502411700002302426700002002449856008302469 2016 eng d00aAssessing the potential for transitions from tallgrass prairie to woodlands: are we operating beyond critical transitions?0 aAssessing the potential for transitions from tallgrass prairie t a280–2870 v693 a

A growing body of evidence suggests humans are pushing ecosystems near or beyond key ecological thresholds, resulting in transitions to new, sometimes undesirable phases or states that are costly to reverse. We used remotely sensed fire data to assess if the Flint Hills—a landscape of tallgrass prairie in the Central Great Plains, United States—is operating beyond fire frequency thresholds. Long-term fire experiments and observational evidence suggests that applying prescribed fire at return intervals > 3 yr can lead to transitions from grassland to shrubland. Fire return intervals > 10 yr and complete fire suppression, in particular, can result in transitions to woodlands over 30 − 50 yr. Once shrublands and woodlands are established, restoration back to grassland is difficult with prescribed fires. We applied these fire frequency cutoffs to remotely sensed fire data from 2000 to 2010 in the Flint Hills, identifying the extent of tallgrass prairie susceptible to shrub and tree expansion. We found that 56% (15 620 km2) of grasslands in this region are burned less than every 3 yr and are therefore susceptible to conversion to shrub or tree dominance. The potential effects of this large-scale shift are greater risk for evergreen (Juniperus virginiana) woodland fires, reduced grazing potential, and increased abundance of woodland adapted species at the expense of the native grassland biota. Of the 12 127-km2 area likely to remain grassland, 43% is burned approximately annually, contributing to vegetative homogenization and potential air-quality issues. While this synthesis forecasts a precarious future for tallgrass prairie conservation and their ecosystem services, increases in shrub or tree dominances are usually reversible until fire frequency has been reduced for more than 20 yr. This delay leaves a small window of opportunity to return fire to the landscape and avoid large-scale transformation of tallgrass prairie.

10acatastrophic shifts10aforecasting10amesic grasslands10aregime shifts10aresilience10atipping points1 aRatajczak, Z.1 aBriggs, J., M.1 aGoodin, D.G.1 aMohler, R.1 aNippert, Jesse, B.1 aObermeyer, B.K. uhttps://www.sciencedirect.com/science/article/pii/S1550742416300021?via%3Dihub02079nas a2200205 4500008004100000245013700041210006900178300001500247490000600262520139700268653002501665653003301690653002301723100001501746700001701761700001701778700001501795700001901810856004401829 2014 eng d00aEstimating canopy nitrogen content in a heterogeneous grassland with varying fire and grazing treatments: Konza Prairie, Kansas, USA0 aEstimating canopy nitrogen content in a heterogeneous grassland  a4430 -44530 v63 a

Quantitative, spatially explicit estimates of canopy nitrogen are essential for understanding the structure and function of natural and managed ecosystems. Methods for extracting nitrogen estimates via hyperspectral remote sensing have been an active area of research. Much of this research has been conducted either in the laboratory, or in relatively uniform canopies such as crops. Efforts to assess the feasibility of the use of hyperspectral analysis in heterogeneous canopies with diverse plant species and canopy structures have been less extensive. In this study, we use in situ and aircraft hyperspectral data to assess several empirical methods for extracting canopy nitrogen from a tallgrass prairie with varying fire and grazing treatments. The remote sensing data were collected four times between May and September in 2011, and were then coupled with the field-measured leaf nitrogen levels for empirical modeling of canopy nitrogen content based on first derivatives, continuum-removed reflectance and ratio-based indices in the 562–600 nm range. Results indicated that the best-performing model type varied between in situ and aircraft data in different months. However, models from the pooled samples over the growing season with acceptable accuracy suggested that these methods are robust with respect to canopy heterogeneity across spatial and temporal scales.

10aheterogeneous canopy10ahyperspectral remote sensing10anitrogen estimates1 aLing, B.H.1 aGoodin, D.G.1 aMohler, R.L.1 aLaws, A.N.1 aJoern, Anthony uhttps://www.mdpi.com/2072-4292/6/5/443001924nas a2200169 4500008004100000245010600041210006900147260004300216490002100259520134400280653001701624653002201641653002201663100001501685700001701700856003701717 2011 eng d00aMulti-scale burned area mapping in tallgrass prairie using in situ spectrometry and satellite imagery0 aMultiscale burned area mapping in tallgrass prairie using in sit aManhattan, KSbKansas State University0 vPhD Dissertation3 a

Prescribed burning in tallgrass prairie affects a wide range of human and natural systems. Consequently, managing this biome based on sound science, and with the concerns of all stakeholders taken into account, requires a method for mapping burned areas. In order to devise such a method, many different spectral ranges and spectral indices were tested for their ability to differentiate burned from unburned areas at both the field and satellite scales. Those bands and/or indices that performed well, as well as two different classification techniques and two different satellite-based sensors, were tested in order to come up with the best combination of band/index, classification technique, and sensor for mapping burned areas in tallgrass prairie. The ideal method used both the red and near-infrared spectral regions, used imagery at a spatial resolution of at least 250 m, used satellite imagery with daily temporal resolution, and used pixel-based classification techniques rather than object-based techniques. Using this method, burned area maps were generated for the Flint Hills for every year from 2000-2010, creating a fire history of the region during that time period. These maps were compared to active fire and burned area products, and these products were found to underestimate burned areas in tallgrass prairie.

10aBurn mapping10aSatellite imagery10atallgrass prairie1 aMohler, R.1 aGoodin, D.G. uhttp://hdl.handle.net/2097/1198603231nas a2200265 4500008004100000245017900041210006900220300001100289490000700300520227800307653003302585653001002618653001102628653002802639653002402667653002202691100001902713700001802732700001802750700001602768700001702784700001902801700001702820856012802837 2006 eng d00aThe use of pasture reflectance characteristics and arbuscular mycorrhizal root colonization to predict pasture characteristics of tallgrass prairie grazed by cattle and bison0 ause of pasture reflectance characteristics and arbuscular mycorr a32 -410 v613 aAn experiment was conducted to evaluate the potential for using arbuscular mycorrhizal fungal (AMF) root colonization and pasture reflectance characteristics as indicators of changes in tallgrass prairie vegetation resulting from differences in grazing history. The experiment was conducted within the context of a separate long-term experiment in which eight 4·9-ha pastures were grazed by either bison or cattle for nine consecutive years. Two separate ungrazed pastures were selected for comparison with grazed areas on the basis of similarity in burning regime, vegetation, soil and topographic characteristics. Four 45 m-long transects were located in the upland sites within each pasture, and four plots were clipped to ground level along each transect. Reflectance readings were taken with a hand-held radiometer at each sampling location and a soil core was collected within each plot for analysis of AMF root colonization. Reflectance readings at sixteen different wavelengths were used directly as inputs during multiple regression development or were transformed into each of three vegetation indices (normalized difference vegetation index, soil-adjusted vegetation index and wide-dynamic-range vegetation index) and used in simple linear regressions. Ungrazed pastures were characterized by higher (P < 0·01) grass biomass, total biomass and canopy height than grazed pastures, but had a lower proportional abundance of forbs (P < 0·01) and amounts of forb biomass (P = 0·04). Species of herbivore did not significantly influence above-ground characteristics that were measured. In general, AMF root colonization was relatively small and was not significantly affected by treatment and, accordingly, the variation was insufficient to test its potential as an indicator of grazing effects on vegetation or its potential relationship with pasture reflectance. Multiple regression equations based on individual wavelength reflectance values explained significantly more of the variation in above-ground vegetation characteristics than did simple regressions using vegetation indices as predictor variables (r2 values from 0·36 to 0·46 vs. 0·11 to 0·27) and have the potential to predict above-ground vegetation characteristics in heterogeneous rangelands.10aArbuscular mycorrhizal fungi10abison10aCattle10apasture characteristics10areflectance methods10atallgrass prairie1 aVillarreal, M.1 aCochran, R.C.1 aJohnson, D.E.1 aTowne, E.G.1 aWilson, G.T.1 aHartnett, D.C.1 aGoodin, D.G. uhttp://knz.lternet.edu/content/use-pasture-reflectance-characteristics-and-arbuscular-mycorrhizal-root-colonization-predict00476nas a2200121 4500008004100000245008200041210006900123300001300192490000700205100001200212700001700224856011300241 2004 eng d00aDetermining landscape structure and heterogeneity using image texture indices0 aDetermining landscape structure and heterogeneity using image te a110 -1170 v271 aGao, J.1 aGoodin, D.G. uhttp://knz.lternet.edu/content/determining-landscape-structure-and-heterogeneity-using-image-texture-indices02752nas a2200145 4500008004100000245012200041210006900163300001300232490000700245520218800252100001702440700001202457700001802469856011902487 2004 eng d00aThe effect of solar zenith angle and sensor view angle on observed patterns of spatial structure in tallgrass prairie0 aeffect of solar zenith angle and sensor view angle on observed p a154 -1650 v423 aWhile it has long been recognized that the anisotropic reflectance properties of a natural surface affect the intensity and spectral distribution of radiance received by a remote sensing instrument, the effects of canopy reflectance geometry on the observed spatial structure of canopy reflectance have not adequately been evaluated. In this paper, near-surface spectrometers were used as part of two experiments to evaluate the systematic variations in the sun-target-sensor geometry on semivariogram metrics (range, sill+nugget variance) summarizing the spatial structure observed in a tallgrass prairie canopy. In the first experiment, reflectance measurements and normalized difference vegetation index (NDVI) values were collected at five sensor viewing angles (-50°, -25°, 0°, 25°, and 50°) from six measurement grids representing three burn treatments and two slope/aspect situations. In the second experiment, data were collected at 2-h intervals, beginning at ≈0800 LST from the same grids with the radiometer at nadir, allowing the spatial structure of reflectance and NDVI to be observed under naturally changing illumination. Results of the geostatistical analysis show that both the range and sill+nugget variance values change with viewing angle. These effects were consistent across all treatments and slope/aspect combinations. However, when viewed from nadir, the sill+nugget variance values of the canopy changed with solar illumination angle and the range values remained nearly constant. These relationships were also observed across all treatments and slope/aspect combinations. The results suggest that sill+nugget values for the same surface may not be directly comparable if not acquired under very similar view angle and illumination conditions. Range values are comparable if the nadir view is used, but not under off-nadir viewing conditions. The implications of these findings point to the need for caution in interpreting spatial structure derived from close-range radiometry or from satellite/aircraft instruments with cross-track or off-nadir pointing capabilities, and in the comparison of images acquired under varying illumination conditions.1 aGoodin, D.G.1 aGao, J.1 aHenebry, G.M. uhttp://knz.lternet.edu/content/effect-solar-zenith-angle-and-sensor-view-angle-observed-patterns-spatial-structure02212nas a2200145 4500008004100000245012400041210006900165300001500234490000700249520164300256100001701899700001201916700002301928856011501951 2004 eng d00aSeasonal, topographic and burn frequency effects on biophysical/spectral reflectance relationships in tallgrass prairie0 aSeasonal topographic and burn frequency effects on biophysicalsp a5429 -54450 v253 aApplication of remote sensing relies on understanding how the physical properties of surfaces (especially vegetated surfaces) control spectral reflectance. Empirical investigation of links between canopy properties/processes and spectral response have generally consisted of univariate modelling of one spectral response variable in terms of one canopy property, or less frequently, in terms of two or more canopy variables. While this approach has been fruitful, it cannot account for multivariate interactions of spectral and surface properties in determining canopy response across the spectrum. In this study, two closely related multivariate analysis techniques, canonical correlation and redundancy analysis, are used to investigate the relationship between a series of tallgrass prairie canopy biophysical properties and spectral reflectance measured in situ using a portable radiometer. To capture a variety of different conditions within the tallgrass canopy, data were collected at two times during the 2002 growing season (28 May and 18 August), from two different slope/aspect situations, located on one frequently burned and one infrequently burned watershed. Results suggest that canopy structure (canopy height, greenness fraction) is the most consistent influence on spectral reflectance during both data collection periods. Canopy optical properties also emerge as an important control in August. Neither soil moisture nor plant physiology/biochemistry systematically influenced spectral reflectance. The relative importance of the various canopy variables shows some dependence on burn frequency and topographic setting.1 aGoodin, D.G.1 aGao, J.1 aHutchinson, J.M.S. uhttp://knz.lternet.edu/content/seasonal-topographic-and-burn-frequency-effects-biophysicalspectral-reflectance00543nam a2200133 4500008004100000245008600041210006900127260003800196300001000234100001800244700001700262700001600279856011400295 2003 eng d00aClimate variability and ecosystem response at Long-Term Ecological Research sites0 aClimate variability and ecosystem response at LongTerm Ecologica aNew YorkbOxford University Press a459 -1 aGreenland, D.1 aGoodin, D.G.1 aSmith, R.C. uhttp://knz.lternet.edu/content/climate-variability-and-ecosystem-response-long-term-ecological-research-sites00656nas a2200169 4500008004100000245010200041210006900143260003800212300001300250100001700263700001200280700001700292700001800309700001700327700001600344856012600360 2003 eng d00aClimate variability in tallgrass prairie at multiple timescales: Konza Prairie Biological Station0 aClimate variability in tallgrass prairie at multiple timescales  aNew YorkbOxford University Press a411 -4241 aGoodin, D.G.1 aFay, P.1 aMcHugh, M.J.1 aGreenland, D.1 aGoodin, D.G.1 aSmith, R.C. uhttp://knz.lternet.edu/content/climate-variability-tallgrass-prairie-multiple-timescales-konza-prairie-biological-station00570nas a2200157 4500008004100000245007100041210006900112260003800181300001300219100001700232700001700249700001800266700001700284700001600301856009500317 2003 eng d00aInterdecadal-scale variability: An assessment of LTER climate data0 aInterdecadalscale variability An assessment of LTER climate data aNew YorkbOxford University Press a213 -2251 aMcHugh, M.J.1 aGoodin, D.G.1 aGreenland, D.1 aGoodin, D.G.1 aSmith, R.C. uhttp://knz.lternet.edu/content/interdecadal-scale-variability-assessment-lter-climate-data00581nas a2200169 4500008004100000245006600041210006300107260003800170300001000208100001800218700001700236700001600253700001800269700001700287700001600304856009100320 2003 eng d00aAn introduction to climate variability and ecosystem response0 aintroduction to climate variability and ecosystem response aNew YorkbOxford University Press a3 -191 aGreenland, D.1 aGoodin, D.G.1 aSmith, R.C.1 aGreenland, D.1 aGoodin, D.G.1 aSmith, R.C. uhttp://knz.lternet.edu/content/introduction-climate-variability-and-ecosystem-response00476nas a2200121 4500008004100000245008600041210006900127300001300196490000700209100001200216700001700228856010900245 2002 eng d00aBiodiversity analysis with multi-scale images in Konza Prairie Biological Station0 aBiodiversity analysis with multiscale images in Konza Prairie Bi a101 -1070 v251 aGao, J.1 aGoodin, D.G. uhttp://knz.lternet.edu/content/biodiversity-analysis-multi-scale-images-konza-prairie-biological-station02629nas a2200145 4500008004100000245010000041210006900141260003600210300001300246520210700259100001702366700001402383700001702397856006902414 2002 eng d00aClimate variability at multiple time scales: implications for productivity in tallgrass prairie0 aClimate variability at multiple time scales implications for pro bAmerican Meteorological Society a312 -3163 aClimate is a fundamental driver of biomass productivity in ecosystems. This is especially true for grassland systems, which display greater variability in net primary productivity in response to climate fluctuation than forest, desert, or arctic/alpine systems. Although basic climate/productivity relationships have been studied over shorter time scales, the effect of longer-term climate processes such as El Niño/Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), solar activity cycles, and other quasiperiodic climatic patterns on grassland systems is largely unknown, due to the lack of long term productivity data sets to evaluate against climate data. Here, we examine how variability in temperature and rainfall at a tallgrass prairie site (Konza Prairie Biological Station, KPBS) is related to various teleconnection indices and how these indices may relate to patterns of above ground net primary productivity (ANPP). We use two data sets, a 20 year ANPP data set collected at KPBS and a 108 year precipitation and temperature record (1891-1999) from nearby Manhattan, KS. Patterns of variation are analyzed using period-spectrum analysis and correlation of climate variables to ANPP. Results show that at shorter time scales (one year or less), productivity is influenced by magnitude of precipitation and temperature, but also by the seasonal timing of precipitation events and heat accumulation. Long-term precipitation was influenced on the decadal time scale by the NAO and North Pacific (NP) circulation patterns. Long-term temperature patterns showed strongest periodicities at intradecadal time scales (" 5- 8 years), and correlated most strongly with ENSO indices. Although speculative, our results suggest that the influence of atmospheric teleconnection patterns (and their resulting weather patterns) on tallgrass productivity is indirect. Teleconnection patterns interact to influence both the magnitude and seasonal distribution of temperature and precipitation. The interplay of these variations in weather appears to exert significant control over tallgrass ANPP.1 aGoodin, D.G.1 aFay, P.A.1 aMcHugh, M.J. uhttps://ams.confex.com/ams/15BioAero/techprogram/paper_48840.htm01720nas a2200133 4500008004100000245011000041210006900151300001500220490000700235520118100242100001701423700001801440856012801458 2002 eng d00aThe effect of rescaling on fine spatial resolution NDVI data: a test using multi-resolution aircraft data0 aeffect of rescaling on fine spatial resolution NDVI data a test  a3865 -38710 v233 aSimulation studies have suggested that pixel aggregation can rescale accurately both Normal Difference Vegetation Index (NDVI) data and fields of biogeophysical values inferred from NDVI. There is, however, a dearth of empirical tests of this hypothesis. This study uses nested NDVI observations acquired from an aircraft-mounted digital camera to assess the spatial properties of measured and rescaled image data. Imagery was collected at four altitudes, yielding spatial resolutions varying from 0.625 m to 3.125 m. The common area from these four images was extracted. The finest spatial resolution image was then rescaled by aggregating pixels to synthesize three rescaled images matching the spatial resolution of the measured images. The spatial properties of these measured and rescaled images were compared, using metrics derived from the variogram. Results demonstrate that the spatial patterns of rescaled data do not correspond to those of the directly observed data. The results suggest that rescaling by averaging blocks of pixels may not adequately preserve spatial properties of very high spatial resolution images and consequent inferred biogeophysical fields.1 aGoodin, D.G.1 aHenebry, G.M. uhttp://knz.lternet.edu/content/effect-rescaling-fine-spatial-resolution-ndvi-data-test-using-multi-resolution-aircraft-data00582nas a2200133 4500008004100000245013700041210006900178300001300247490000700260100002000267700001700287700001600304856012800320 2000 eng d00aRelating biophysical processes to spatial patterns of spectral reflectance: A multiple-scale analysis of prairie vegetation canopies0 aRelating biophysical processes to spatial patterns of spectral r a190 -1980 v231 aRundquist, B.C.1 aGoodin, D.G.1 aSmith, A.J. uhttp://knz.lternet.edu/content/relating-biophysical-processes-spatial-patterns-spectral-reflectance-multiple-scale-analysis00490nas a2200109 4500008004100000245010800041210006900149300001300218490000700231100001700238856012500255 1998 eng d00aEvaluation of a digital camera as a low-cost airborne sensor for high spatial resolution remote sensing0 aEvaluation of a digital camera as a lowcost airborne sensor for  a283 -2890 v211 aGoodin, D.G. uhttp://knz.lternet.edu/content/evaluation-digital-camera-low-cost-airborne-sensor-high-spatial-resolution-remote-sensing01675nas a2200145 4500008004100000245011300041210006900154300001500223490000700238520110000245653002201345100001701367700001801384856012701402 1998 eng d00aSeasonality of finely-resolved spatial structure of NDVI and its component reflectances in tallgrass prairie0 aSeasonality of finelyresolved spatial structure of NDVI and its  a3213 -32200 v193 aGrass canopies exhibit distinct seasonality in reflectance and spatial patterns in reflectance result from landscape heterogeneity. To investigate the spatial structure of NDVI and its two component reflectances at fine resolution in burned and unburned tallgrass prairie, we use range and relative nugget effect two indicators of spatial structure derived from semivariograms. Results show that spatial dependence of the three spectral measures are similar in the early season when the litter layer has been removed by burning and again in the later season when the canopy is senescent. However, as the canopy develops, the spatial dependence of NDVI deviates from that of its component reflectances. In the unburned canopy, red reflectance appears to strongly influence the spatial pattern of NDVI. In the burned canopy, neither component reflectance strictly determines the spatial pattern of NDVI. Maximum divergence in spatial pattern between NDVI and its components coincides with minimum available moisture, suggesting a relation between moisture stress and spatio-spectral heterogeneity.10atallgrass prairie1 aGoodin, D.G.1 aHenebry, G.M. uhttp://knz.lternet.edu/content/seasonality-finely-resolved-spatial-structure-ndvi-and-its-component-reflectances-tallgrass01646nas a2200121 4500008004100000245016200041210006900203300001300272520107800285100001701363700001901380856012501399 1998 eng d00aVariability of spectral reflectance and vegetation indices in tallgrass prairie: spatio-temporal analysis using semivariograms and close-range remote sensing0 aVariability of spectral reflectance and vegetation indices in ta a301 -3053 aThe effects of fire and other disturbances on spatial patterning of vegetation in tallgrass prairie has been extensively studied using remote sensing. Data used in these studies is frequently typically collected from operational remote sensing satellites with spatial resolution coarse relative to the grassland canopy. The authors use semivariograms calculated from close range remote sensing instruments to investigate the spatial structure of spectral reflectance and vegetation indices in tallgrass prairie at finer spatial resolution more appropriate to the developing canopy. Data were collected at the Konza Prairie Research Natural Area near Manhattan, KS. Two watersheds were surveyed; one unburned the other burned just prior to data collection. Spatial dependence and anisotropy for three spectral bands (TM3, TM4, and TM5) and two vegetation indices (NDVI, NDVIc) were calculated for three dates distributed throughout the 1997 growing season. Results show that both anisotropy and dominant scale of spatial dependence vary seasonally and across spectral region1 aGoodin, D.G.1 aHenebry., G.M. uhttp://knz.lternet.edu/content/variability-spectral-reflectance-and-vegetation-indices-tallgrass-prairie-spatio-temporal01694nas a2200181 4500008004100000245006700041210006700108300001100175490000800186520112600194100001901320700001601339700001701355700001801372700001701390700001701407856008801424 1997 eng d00aSpatial and temporal patterns of vegetation in the Flint Hills0 aSpatial and temporal patterns of vegetation in the Flint Hills a10 -200 v1003 aIn tallgrass prairie, complex interactions among multiple limiting resources in combination with a variety of land use practices can lead to a heterogeneous landscape. Remote-sensing data (AVHRR) were coupled with abiotic factors to explore spatial and temporal vegetation patterns of the Flint Hills in Kansas and Oklahoma. This information should enable the detection of both natural (e.g., interannual variation in precipitation and temperature) and anthropogenic (e.g., climate change, over-grazing, land-use practices) stresses on this grassland ecosystem. Shifts in the spatial and temporal patterns of vegetation (as measured from NDVI by AVHRR) have been correlated with meteorological data (from 117 weather stations) to identify key abiotic variables that determined vegetation patterns across this region. In 4 years, the combination of annual precipitation and growing degree days was useful to detect spatial and temporal vegetation patterns of the Flint Hills. However, it is imperative that land-use patterns are known in order to assess adequately spatial and temporal patterns of vegetation in this area.1 aBriggs, J., M.1 aRieck, D.R.1 aTurner, C.L.1 aHenebry, G.M.1 aGoodin, D.G.1 aNellis, M.D. uhttp://knz.lternet.edu/content/spatial-and-temporal-patterns-vegetation-flint-hills02320nas a2200145 4500008004100000245015000041210006900191300001300260490000700273520172000280653002202000100001702022700001802039856011702057 1997 eng d00aA technique for monitoring ecological disturbance in tallgrass prairie using seasonal NDVI trajectories and a discriminant function mixture model0 atechnique for monitoring ecological disturbance in tallgrass pra a270 -2780 v613 aNatural and anthropogenic disturbance in tallgrass prairie communities can induce changes in plant species composition, including shifts in the relative abundance of C3 and C4 lifeforms. The asynchronous seasonality in greenness exhibited by C3 and C4 species enables monitoring of their relative abundance using temporal trajectories of sensor-derived vegetation indices, such as NDVI. We use close-range measurements made over 22 experimental plots at the Konza Prairie Research Natural Area (KPRNA) to evaluate seasonal trajectories in NDVI as a function of Full-size image (<1 K) ratio. The NDVI data were collected from each plot at approximately 10-day intervals throughout the 1995 growing season. Metrics for summarizing the temporal behavior of NDVI trajectories were derived from two transformations of the data: 1) a conventional approach plotting NDVI against day of year and 2) an alternative approach plotting normalized cumulative integrated NDVI against growing degree day. Discriminant function mixture models derived from each set of inetrics were used together with species composition data from the experimental plots to derive relative Full-size image (<1 K) abundances. Results show that both methods can classify the majority of cases into their correct Full-size image (<1 K) abundance category; however, the transformation using normalized integrated NDVI against growing degree day was a significantly better discriminator (p=0.0102). The techniques presented are effective for monitoring relative Full-size image (<1 K) abundance in tallgrass prairie; however, more investigation is needed to assess their performance at different spatial resolutions and in different geographic settings.10atallgrass prairie1 aGoodin, D.G.1 aHenebry, G.M. uhttp://knz.lternet.edu/content/technique-monitoring-ecological-disturbance-tallgrass-prairie-using-seasonal-ndvi01754nas a2200145 4500008004100000245012100041210006900162260002500231300001300256520116100269653002201430100001701452700001801469856012101487 1996 eng d00aSeasonal NDVI trajectories in response to disturbance: toward a spectral-temporal mixing model for tallgrass prairie0 aSeasonal NDVI trajectories in response to disturbance toward a s aPiscataway, NJbIEEE a215 -2173 aNatural and anthropogenic disturbance in tallgrass prairie communities can induce changes in plant species composition, including shifts in abundance of C3 vs. C4 lifeforms. The asynchronous seasonalities in greenness that C3 and C4 species exhibit should enable monitoring of their relative abundance using sensor derived vegetation indices, such as NDVI. The authors used close-range measurements made over 22 experimental. Plots at the Konza Prairie Research Natural Area (KPRNA) to evaluate seasonal trajectories in canopy greenness as a function of C3/C4 ratio. NDVI data were collected from each plot at approximately ten day intervals throughout the 1995 growing season. Temporal trajectories were used to develop discriminant functions to model relative C3/C4 abundances. The discriminant model yielded values of Kendall's τb and Cohen's κ statistic of 0.794 and 0.781, indicating strong agreement between classes and an overall classification significantly better than random assignment. Results suggest the possibility of applying spectral-temporal mixture models derived from close-range sensing to larger scale monitoring of tallgrass prairie10atallgrass prairie1 aGoodin, D.G.1 aHenebry, G.M. uhttp://knz.lternet.edu/content/seasonal-ndvi-trajectories-response-disturbance-toward-spectral-temporal-mixing-model