Vegetation indices, CO2 flux, and biomass for Northern Plains grasslands

Frank, A. B.; Karn, J. F.

doi:10.2458/azu_jrm_v56i4_frank

Cited by 12 publications

(19 citation statements)

References 3 publications

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“…5), and lower cumulative NEP along this gradient (Table 1; Svejcar et al, 2008). Peak CO 2 flux rates were reported to reach 7.8 g C m −2 day −1 in the Northern Great Plains (Frank and Karn, 2003). Our maximum rate was lower, approximately …”

Section: Nep Phenologymentioning

confidence: 57%

“…The NDVI composites were averaged over the course of a growing season (defined as 1 April to 30 September) to produce Growing Season NDVI (GSN), a proxy of actual yearly ecosystem performance (Wylie et al, 2008) that is spatially and temporally consistent. Remotely sensed vegetation indices such as the NDVI are strongly related to CO 2 flux, plant biomass, total ecosystem respiration, and Leaf Area Index (LAI) (Frank and Karn, 2003;Gilmanov et al, 2005), while GSN has been strongly correlated with Soil Survey Geographic (SSURGO) annual productivity for grasslands . GSN values include the effects of disturbances such as fire and insect damage, grazing, site potential, and yearly weather conditions (Wylie et al, 2008;Rigge et al, 2013).…”

Section: Ecosystem Performance Anomalies (Epa)mentioning

confidence: 99%

“…6). The seasonal pattern of phenology in each grassland type and ecoregion generally progressed as negative NEP in winter , sharp increase in spring with ample precipitation (Sims et al, 1978;Frank and Karn, 2003), peak in early summer (usually in week 20-23) (Chimner and Welker, 2011), then decline in late summer (usually in week 25-35) frequently becoming negative with drought and precipitation deficits. This pattern is largely due to 75% of annual precipitation accumulating during the April to September period in the Great Plains (Sims et al, 1978), much of it concentrated in April to June.…”

Section: Nep Phenologymentioning

confidence: 99%

“…This pattern is largely due to 75% of annual precipitation accumulating during the April to September period in the Great Plains (Sims et al, 1978), much of it concentrated in April to June. Other ecosystem attributes, such as above ground biomass, LAI, and carbon assimilation also often have peaks in mid-June to early-August (Frank and Karn, 2003).…”

Section: Nep Phenologymentioning

confidence: 99%

“…Harvesting biomass, grazing, and fires are additional pathways in which carbon could be removed from a site (Zhu et al, 2011). Grasslands in the central and northern Great Plains tend to have a long-term cumulative carbon balance near zero (i.e., equilibrium) (Haferkamp and MacNeil, 2004;Owensby et al, 2006;Wylie et al, 2007;Zhang et al, 2010;Chimner and Welker, 2011) or slightly positive (i.e., sink) (Frank and Karn, 2003;Zhang et al, 2011). Root turnover in grassland soils constitutes the largest input to soil organic carbon (SOC), the below-ground C pool, due to the high concentration of lignin and polyphenols, which are resistant to degradation (Soussana et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

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Influence of management and precipitation on carbon fluxes in great plains grasslands

Rigge¹,

Wylie²,

Zhang³

et al. 2013

Ecological Indicators

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a b s t r a c tSuitable management and sufficient precipitation on grasslands can provide carbon sinks. The net carbon accumulation of a site from the atmosphere, modeled as the Net Ecosystem Productivity (NEP), is a useful means to gauge carbon balance. Previous research has developed methods to integrate flux tower data with satellite biophysical datasets to estimate NEP across large regions. A related method uses the Ecosystem Performance Anomaly (EPA) as a satellite-derived indicator of disturbance intensity (e.g., livestock stocking rate, fire, and insect damage). To better understand the interactions among management, climate, and carbon dynamics, we evaluated the relationship between EPA and NEP data at the 250 m scale for grasslands in the Central Great Plains, USA (ranging from semi-arid to mesic). We also used weekly estimates of NEP to evaluate the phenology of carbon dynamics, classified by EPA (i.e., by level of disturbance impact). Results show that the cumulative carbon balance over these grasslands from 2000 to 2008 was a weak net sink of 13.7 g C m −2 yr −1 . Overall, NEP increased with precipitation (R 2 = 0.39, P < 0.05) from west to east. Disturbance influenced NEP phenology; however, climate and biophysical conditions were usually more important. The NEP response to disturbance varies by ecoregion, and more generally by grassland type, where the shortgrass prairie NEP is most sensitive to disturbance, the mixed-grass prairie displays a moderate response, and tallgrass prairie is the least impacted by disturbance (as measured by EPA). Sustainable management practices in the tallgrass and mixed-grass prairie may potentially induce a period of average net carbon sink until a new equilibrium soil organic carbon is achieved. In the shortgrass prairie, management should be considered sustainable if carbon stocks are simply maintained. The consideration of site carbon balance adds to the already difficult task of managing grasslands appropriately to site conditions. Results clarify the seasonal and interannual dynamics of NEP, specifically the influence of disturbance and moisture availability.

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Section: Nep Phenologymentioning

confidence: 57%

Section: Ecosystem Performance Anomalies (Epa)mentioning

confidence: 99%

Section: Nep Phenologymentioning

confidence: 99%

Section: Nep Phenologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Influence of management and precipitation on carbon fluxes in great plains grasslands

Rigge¹,

Wylie²,

Zhang³

et al. 2013

Ecological Indicators

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Assessing impacts to primary productivity at the park edge in Murchison Falls Conservation Area, Uganda

et al. 2016

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Abstract. Human activities around parks can alter vegetation patterns within them, resulting in edge effects that degrade their ability to sustain ecological processes and support biodiversity. We quantified vegetation patterns and edge effects over a large geographic extent in Murchison Falls Conservation Area, Uganda, using freely available remotely sensed data. Over a 13-yr period, we quantified seasonal patterns in productivity using the Normalized Difference Vegetation Index (NDVI), comparing the park exterior, a boundary zone ≤10 km from the border inside the park, and the park interior. To identify the extent of edge effects, we further fit mixed models by vegetation type within 1-km bands within the boundary zone. Productivity was higher in the park interior than exterior in both wet and dry seasons, and in the wet season, it was also lower in the boundary zone than the interior. NDVI variability differed between seasons; it declined from exterior to interior in the wet season, but was highest in the boundary zone and similar between interior and exterior during the dry season. Within the boundary zone, edge effects varied by land cover type and extended 4-6 km into MFCA. Abrupt differences in vegetation patterns between the park and adjacent unprotected areas indicated a "hard edge" in this system. While hard edges are readily apparent, the subtle changes in productivity that extend into and degrade park systems are harder to detect. We demonstrated a low-cost and novel approach to detect such effects using readily available satellite imagery, which indicated human influence affecting 29-40% of the park. As human populations grow, parks will become further isolated, and measuring and managing edge effects may be crucial to achieving conservation objectives.

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Modeling gross primary production of irrigated and rain-fed maize using MODIS imagery and CO2 flux tower data

Kalfas

Xiao

Vanegas

et al. 2011

Agricultural and Forest Meteorology

107

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Information on gross primary production (GPP) of maize croplands is needed for assessing and monitoring maize crop conditions and the carbon cycle. A number of studies have used the eddy covariance technique to measure net ecosystem exchange (NEE) of CO 2 between maize cropland fields and the atmosphere and partitioned NEE data to estimate seasonal dynamics and interannual variation of GPP in maize fields having various crop rotation systems and different water management practices. How to scale up in situ observations from flux tower sites to regional and global scales is a challenging task. In this study, the Vegetation Photosynthesis Model (VPM) and satellite images from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate seasonal dynamics and interannual variation of GPP during 2001-2005 at five maize cropland sites located in Nebraska and Minnesota of the U.S.A. These sites have different crop rotation systems (continuously maize vs. maize and soybean rotated annually) and different water management practices (irrigation vs. rainfed). The VPM is based on the concept of light absorption by chlorophyll and is driven by the Enhanced Vegetation Index (EVI) and the Land Surface Water Index (LSWI), photosynthetically active radiation (PAR), and air temperature. The seasonal dynamics of GPP predicted by the VPM agreed well with GPP estimates from eddy covariance flux tower data over the period of 2001-2005. These simulation results clearly demonstrate the potential of the VPM to scale-up GPP estimation of maize cropland, which is relevant to food, biofuel, and feedstock production, as well as food and energy security.

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Vegetation indices, CO2 flux, and biomass for Northern Plains grasslands

Cited by 12 publications

References 3 publications

Influence of management and precipitation on carbon fluxes in great plains grasslands

Influence of management and precipitation on carbon fluxes in great plains grasslands

Assessing impacts to primary productivity at the park edge in Murchison Falls Conservation Area, Uganda

Modeling gross primary production of irrigated and rain-fed maize using MODIS imagery and CO2 flux tower data

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