Effects of stand development and weather on monthly leaf biomass dynamics of a loblolly pine (Pinus taeda L.) stand

Dougherty, Phillip M.; Hennessey, Thomas; Zarnoch, Stanley J.; Stenberg, Pauline; Holeman, Randal; Wittwer, Robert F.

doi:10.1016/0378-1127(95)97452-x

Cited by 47 publications

(40 citation statements)

References 6 publications

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“…As such, nitrogen limitations in loblolly pine forests restrict the maximum LA1 attainable, provided water is not limiting (NCSFNC 1991). Droughty conditions will induce premature foliage senescence (Dougherty et al 1995), and reduced development of the next year's foliage cohort (Hennessey et al 1992).…”

Section: Discussionmentioning

confidence: 99%

“…For example, decreased precipitation in one year would result in lower leaf area production in the following year (Dougherty et al 1995), resulting in reduced NPP and potentially a different response to climate projected for that year (Fig. 4c, d).…”

Section: Discussionmentioning

confidence: 99%

“…For any unit LAI, increased water availability or decreased evaporative demand (Teskey et al 1987) and increased ambient CO2 and/or increased foliar nitrogen concentration (Murthy et al in press) Increases photosynthesis and, therefore, productivity. Climate influences both the yearly pattern in foliage biomass accretion (Dougherty et al 1995) and foliage senescence (Hennessey et al 1992). Characterization of the magnitude and seasonal pattern in LAI, and site description of stand structure and soil water availability (McNulty et al 1994), in conjunction with natural climatic variability, wlll strongly influence NPP in regional slmulations.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of the UKMO and GFDL GCM climate projections in NPP simulations for southern loblolly pine stands

Da¹,

Cooter²,

Pm³

et al. 1996

Clim. Res.

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We used the process model BIOMASS version 13.0 to simulate contemporary net pnmary production (NPP) and NPP response to climate prolections for a doubhng of atmospheric CO2 concentration from 2 general circulation models (GCMs) that vary in their CO2 sensitivity: the less sensitive GFDL and the more sensitive UKMO. Increased GCM sensitivity to CO2 is reflected in increased predictions in the magnitude, vanation, and range of the clunate variables. Smulations used a 40 yr historical climate record, and 2 stand and site conditions to standardize the total NPP response estimates for eighteen 1x1" grid cells across the southern U n~t e d States. Contemporary NPP and NPP response estimates from the 18 cells were smoothed using a cell search algonthm to obtain a n NPP response index matrix for the entlre loblolly pine (Pinus taeda) forest-type We conducted a sensitivity analysis of the environmental variables projected to change in a 2xC0, environment to help interpret simulation output. Contemporary NPP varied from 2.5 to 8.5 Mg C ha-' yr-' over the range of loblolly pine High leaf area index (LA1) sirnulations had 1.5 to 2 times the productlvity of low LA1 simulations, but the regional patterns were similar, NPP was correlated with regional ddferences in precipitation and temperature. The NPP response to future climate and atmospheric changes depended on the GCM used, and on the stand and site condition assumed. Inter-annual estimates for the 18 cell simulations resulted in a +22 to + 8 4 % NPP response for the GFDL climate projections and a -30 to +94% NPP response for the UKMO clunate prolections. The 40-year average NPP response for the smoothed data ranged from + 4 3 to + 6 5 % and 1 to + 9 4 % for the GFDL and the UKMO climate prolections, respectively. Consequently, the magnitude and range of the 40-year average NPP response to the climate prolections was directly correlated with the GCM CO2 sensitivity. Although ~ncreased CO2 sensitivity resulted in broader extremes in the predicted temperature response, precipitation response for the 2 models was similar. The NPP response was also correlated with the patterns in predicted climate change, w~t h regional differences coupled to local climatic conditions. Climate projections from both models produced similar NPP responses when predicted temperatures and precipitation regvnes were similar. Elevated ambient CO2 had a greater effect on NPP response than temperature or precipitation in the sensitivity comparisons. Simulations indicate that a CO2 fertilizer effect, assuming no CO2 acclimation, more than compensates for decllnes in productlvity over most of the loblolly pine forest-type associated with projected decreased precipitation and/or projected low to moderate increases in temperature and, therefore, increased maintenance respiration costs.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comparison of the UKMO and GFDL GCM climate projections in NPP simulations for southern loblolly pine stands

Da¹,

Cooter²,

Pm³

et al. 1996

Clim. Res.

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show abstract

“…Within a fully stocked stand, approximately 10%-20% of incident radiation reaches the forest floor. The canopy architecture for P. taeda exhibits significant variation due to indeterminate growth (multiple flushes) and high plasticity, i.e., developmental patterns in foliage accretion and abscission in response to site fertility and drought [8,[11][12][13]. P. taeda varied twofold interannually with a minimum LAI in March-April and a maximum in September [8].…”

Section: Elements Of Variationmentioning

confidence: 99%

Uncertainty Analysis in the Creation of a Fine-Resolution Leaf Area Index (LAI) Reference Map for Validation of Moderate Resolution LAI Products

et al. 2015

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Abstract:The validation process for a moderate resolution leaf area index (LAI) product (i.e., MODIS) involves the creation of a high spatial resolution LAI reference map (Lai-RM), which when scaled to the moderate LAI resolution (i.e., > 1 km) allows for comparison and analysis with this LAI product. This research addresses two major sources of uncertainty in the creation of the LAI-RM: (1) the uncertainty associated with the indirect in situ optical measurements of southeastern United States needle-leaf LAI and (2) the uncertainty in the process of classifying land cover (LC). Uncertainty within the loblolly pine (Pinus taeda) in situ data collection was highest for the assessment of the plant area index (PAI), Le (27.2%), and the woody-to-total ratio, α, (30.6%). The needle-to-shoot ratio, λE, and the element clumping index, ΩE, contributed 14.9% and 9.3%, respectively, to the uncertainty in the calculation of LAI. Combining LC differences (3.4%) with the uncertainty within the loblolly pine component resulted in doubling the LAI-RM variability (σ = 0.50 to σ = 0.97) at the 1 km 2 validation site located in Appomattox, Virginia, USA.

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“…Several forest ecosystem processes are strongly controlled by LAI including interception of light (Machado & Reich, 1999) and precipitation (Van Dijk & Bruijnzeel, 2001), gross primary productivity (Jarvis & Leverenz, 1983), transpiration (Granier et al, 2000), and soil respiration (Davidson et al, 2002). LAI is also related to other important ecological processes such as evapotranspiration, CO 2 and water exchange with the atmosphere, nutrient cycling and nutrient storage in plants (Dougherty et al 1995). Therefore, measurements of forest biomass and structure are critical in the study of ecosystems for many applications including management of forest plantations, wildlife and biodiversity, fire modeling, and carbon sequestration among others.…”

Section: Introductionmentioning

confidence: 99%

Using Remotely Sensed Imagery for Forest Resource Assessment and Inventory

Morales¹

2012

Forest Ecosystems - More Than Just Trees

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Effects of stand development and weather on monthly leaf biomass dynamics of a loblolly pine (Pinus taeda L.) stand

Cited by 47 publications

References 6 publications

Comparison of the UKMO and GFDL GCM climate projections in NPP simulations for southern loblolly pine stands

Comparison of the UKMO and GFDL GCM climate projections in NPP simulations for southern loblolly pine stands

Uncertainty Analysis in the Creation of a Fine-Resolution Leaf Area Index (LAI) Reference Map for Validation of Moderate Resolution LAI Products

Using Remotely Sensed Imagery for Forest Resource Assessment and Inventory

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