Phenological Pattern in the Shortgrass Prairie

Dickinson, Charles E.; Dodd, J. L.

doi:10.2307/2424076

Cited by 82 publications

(59 citation statements)

References 5 publications

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“…The availability of seeds of B. gracilis to each plot was based on probabilities associated with the production and dispersal of seeds of B. gracilis. The probability of seeds being produced was a function of the amount of aboveground biomass of B. gracilis and the amount of precipitation received in the previous year, since seeds of B. gracilis produced in the fall of one year are available to germinate in the spring of the following year (Dickinson and Dodd 1976;Coffin and Lauenroth 1989). We assumed that 49 g/m 2, or 50% of the maximum biomass of B. gracilis, was necessary for seeds to be produced.…”

Section: Model Descriptionmentioning

confidence: 99%

Disturbances and gap dynamics in a semiarid grassland: A landscape-level approach

Coffin

Lauenroth

1989

Landscape Ecol

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We developed a spatially-explicit gap dynamics simulation model to evaluate the effects of disturbances at the scale of a landscape for a semiarid grassland in northcentral Colorado, USA. The model simulates the establishment, growth, and death of individual plants on a small plot through time at an annual time step. Long-term successional dynamics on individual plots (single gaps) and on a landscape composed of a grid of plots were evaluated. Landscapes were simulated as either a collection of independent plots or as a collection of interacting plots where processes on one plot were influenced by processes on adjacent plots. Because we were interested in the recovery of the dominant plant species, the perennial grass blue grama (Bouteloua gracilis (H.B.K.) Lag. ex Griffiths) after disturbances, we focused on scale-dependent processes, such as seed dispersal, that are important to the recruitment of individuals of B. gracilis.The type o f simulated landscape was important to the recovery time o f B. gracilis after a disturbance. Landscapes composed of independent plots recovered more rapidly following a disturbance than landscapes composed of interacting plots in which the recovery time was dependent on the spatial scale of the disturbance.

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Section: Model Descriptionmentioning

confidence: 99%

Disturbances and gap dynamics in a semiarid grassland: A landscape-level approach

Coffin

Lauenroth

1989

Landscape Ecol

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“…Grasslands are sensitive to temperature, precipitation [French and Sauer, 1974;Mueggter, 1983], and soil moisture [Dickinson and Dodd, 1976] . Growth in dry grasslands is controlled largely by moisture [Kemp, 1983] while grasslands in cooler, moister areas are limited primarily by temperature [Ram et at., 1988].…”

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confidence: 99%

A continental phenology model for monitoring vegetation responses to interannual climatic variability

White¹,

Thornton²,

Running³

1997

Global Biogeochemical Cycles

1,063

883

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Abstract. Regional phenology is important in ecosystem simulation models and coupled biosphere/atmosphere models. In the continental United States, the timing of the onset of greenness in the spring (leaf expansion, grass green-up) and offset of greenness in the fall (leaf abscission, cessation of height growth, grass brown-off) are strongly influenced by meteorological and climatological conditions. We developed predictive phenology models based on traditional phenology research using commonly available meteorological and climatological data. Predictions were compared with satellite phenology observations at numerous 20 km x 20 km contiguous landcover sites. Onset mean absolute error was 7.2 days in the deciduous broadleaf forest (DBF) biome and 6.1 days in the grassland biome. Offset mean absolute error was 5.3 days in the DBF biorne and 6.3 days in the grassland biome. Maximum expected errors at a 95% probability level ranged from 10 to 14 days. Onset was strongly associated with temperature summations in both grassland and DBF biomes; DBF offset was best predicted with a photoperiod function, while grassland offset required a combination of precipitation and temperature controls.

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“…Plants of this species initiate growth during the early spring months when seasonal temperatures are relatively cool (6). Flowering occurs in June; thus, this species completes a major portion of its life cycle before the commencement of high air temperatures which characterize the remainder of the growing season.…”

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confidence: 99%

Temperature Dependence of Photosynthesis in Agropyron smithii Rydb.

Monson¹,

Stidham²,

Williams³

et al. 1982

Plant Physiol.

113

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ABSTRACTof photosynthesis observed at above-optimum temperatures (3).Temperature has also been shown to affect both the Km (CO2) and V,= of RuBP carboxylase in vitro (2,24). Weis (35) has suggested that a temperature-dependent inactivation of RuBP carboxylase occurs at above-optimal temperatures in intact spinach chloroplasts. Such temperature effects may be partly responsible for the reversible temperature limitations on net photosynthesis observed for intact leaves. However, difficulties arise in interpreting these data due to the uncertainties encountered in using in vitro studies to describe processes in vivo.Photosynthetic inhibition at analysis temperatures beyond the point of reversibility is due in part to irreversible inhibition of the quantum yield for CO2 fixation, and decreased activity of certain enzyme reactions (4). An irreversible reduction in the quantum yield has been used as an indication of heat damage to the photosynthetic apparatus (29), and is presumably related to the integrity of the thylakoid membranes (1).Agropyron smithii is a C3 perennial grass which constitutes a major biomass producer of the short-and mixed-grass prairie ecosystems. Plants of this species initiate growth during the early spring months when seasonal temperatures are relatively cool (6). (P2%0-P21%0,/P2%0,) 100(1)Leaf transmittance and reflectance measurements were conducted on freshly cut leaf discs, at 5-nm wavelength intervals between 400 and 700 nm, with the integrating sphere described by Robberecht and Caldwell (28 min prior to initiating each assay, a 2-to 3-ml aliquot of the frozen extract was removed from the mortar and allowed to thaw at room temperature. The thawed extract was pressed through a 40-,um nylon net attached to a 20-ml syringe and irnmediately assayed.The assays were conducted in small glass vials which were half immersed in a temperature-controlled water bath. The assay buffer (100 mM C02-free Tricine, pH 8.0), which contained 5 mm DTT and 20 mm MgCl2, was added to each reaction vial approximately 2 min prior to each assay in order to insure temperature equilibration. N2 was bubbled through the assay medium for the entire 2-min equilibration period. Carbonic anhydrase (100 units) and RuBP (0.4 mm) were added to the assay medium at 60 and 45 s prior to initiating each assay, respectively. The appropriate concentration of NaH4C03-(7.0 mCi mm-) was added 5 s before initiating the reaction, thus minimizing losses of 14CO2 to the atmosphere above the reaction medium. The reaction was initiated by the addition of 20 IAl of crude extract. The final volume of the reaction mixture was 1 ml. The reaction was terminated after 30 s (1 min at 10 and 15°C) by the addition of 200 ,ul of 6 N HCI. The contents of each reaction vial were transferred to a scintillation

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Phenological Pattern in the Shortgrass Prairie

Cited by 82 publications

References 5 publications

Disturbances and gap dynamics in a semiarid grassland: A landscape-level approach

Disturbances and gap dynamics in a semiarid grassland: A landscape-level approach

A continental phenology model for monitoring vegetation responses to interannual climatic variability

Temperature Dependence of Photosynthesis in Agropyron smithii Rydb.

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