Leaf Area Index (LAI) of Loblolly Pine and Emergent Vegetation Following a Harvest

Forests provide goods and services to society and, often, refugia for plants and animals; forest managers utilize silviculture to provide ecosystem services and to create habitat. On the Coastal Plain of North Carolina, forest management objectives typically include wood fiber production but may also include the maintenance of environmental quality and, sometimes, species diversity. Silvicultural prescriptions alter stand structure and development trajectories by influencing the competitive interactions among plant species for site resources. Early site intervention may include nutrient additions and/or vegetation control; in coastal loblolly pine (Pinus taeda L.) stands, herbaceous and arborescent species can dominate the site leaf area index (LAI) for many years after a harvest (followed by planting). LAI is an important structural and functional component of a forest stand. Many eco‐hydrologic and water quality models do not accurately account for LAI as the process driver to evapotranspiration (ET), and thus they ignore the ecophysiological effects of LAI on site water balance and nutrient loading. We measured LAI of emergent vegetation following a harvest, mechanical site preparation, and then pine planting for a drained loblolly pine plantation in coastal North Carolina. For six years monthly, growing season estimates of LAI were obtained using a LI‐COR LAI 2000 Plant Canopy Analyzer (PCA) for control (D1), thinned (D3), and harvested (D2) watersheds. In this article, we present results from the D2 treatment. In D2, we “harvested” all emergent vegetation in 18 randomly placed 1 m2 clip plots for three growing seasons where we estimated LAI using species‐pooled estimates of specific leaf area and total leaf dry mass (i.e., LAICLIP); PCA measurements were recorded prior to clipping (LAIPCA). We also simulated loblolly pine seedling growth and development using the biogeochemical process model SECRETS‐3PG to examine site differentiation in LAI. Four years post‐harvest maximum LAICLIP exceeded 8 m2 m‐2 (projected area basis). LAIPCA underestimated LAICLIP; LAICLIP = 1.436 × LAIPCA (r2 = 0.53; p < 0.0001; n = 195). Corrected LAIPCA estimates exceeded simulated pine LAI (LAISIM) for ~4.5 years post‐planting. Emergent vegetation dominated the site for nearly five years and likely exerted a strong influence over site water balance and nutrient use during early stand development.

[1]  J. Haywood,et al.  A Regional Study on the Influence of Woody and Herbaceous Competition on Early Loblolly Pine Growth , 1991 .

[2]  Henry L. Gholz,et al.  Energy exchange across a chronosequence of slash pine forests in Florida , 2002 .

[3]  R. Wynne,et al.  Edaphic and climatic effects on forest stand development, net primary production, and net ecosystem productivity simulated for Coastal Plain loblolly pine in Virginia , 2008 .

[4]  Ge Sun,et al.  MODELING THE HYDROLOGIC IMPACTS OF FOREST HARVESTING ON FLORIDA FLATWOODS 1 , 1998 .

[5]  D. Amatya,et al.  Effects of Thinning on Hydrology and Water Quality of a Drained Pine Forest in Coastal North Carolina , 2008 .

[6]  H. L. Allen,et al.  Monthly leaf area index estimates from point-in-time measurements and needle phenology for Pinus taeda , 2003 .

[7]  R. Hunt,et al.  Components of relative growth rate and their interrelations in 59 temperate plant species , 1997 .

[8]  Duncan S. Wilson,et al.  Early growth responses of slash and loblolly pine following fertilization and herbaceous weed control treatments at establishment. , 2000 .

[9]  P. Balandier,et al.  Designing forest vegetation management strategies based on the mechanisms and dynamics of crop tree competition by neighbouring vegetation , 2006 .

[10]  P. Stenberg,et al.  Response of LAI-2000 estimates to changes in plant surface area index in a Scots pine stand. , 1996, Tree physiology.

[11]  F. Woodward.  THE SIGNIFICANCE OF INTERSPECIFIC DIFFERENCES IN SPECIFIC LEAF AREA TO THE GROWTH OF SELECTED HERBACEOUS SPECIES FROM DIFFERENT ALTITUDES , 1983 .

[12]  Changsheng Li,et al.  Bi-criteria evaluation of the MIKE SHE model for a forested watershed on the South Carolina coastal plain , 2010 .

[13]  S. T. Gower,et al.  A comparison of optical and direct methods for estimating foliage surface area index in forests , 1994 .

[14]  J. Welles,et al.  Canopy structure measurement by gap fraction analysis using commercial instrumentation , 1996 .

[15]  G. P. Fernandez,et al.  Hydrology of Poorly Drained Coastal Watersheds in Eastern North Carolina , 2002 .

[16]  K. Johnsen,et al.  Production, allocation, and stemwood growth efficiency of Pinus taeda L. stands in response to 6 years of intensive management , 2004 .

[17]  Timothy A. Martin,et al.  Production dynamics of intensively managed loblolly pine stands in the southern United States: a synthesis of seven long-term experiments , 2004 .

[18]  Devendra M. Amatya,et al.  Modeling water, carbon, and nitrogen dynamics for two drained pine plantations under intensive management practices , 2012 .

[19]  J. M. Chen,et al.  Effects of clumping on estimates of stand leaf area index using the LI-COR LAI-2000 , 1993 .

[20]  S. Tian,et al.  Development and Application of the Forestry Version of DRAINMOD-NII. , 2009 .

[21]  M. Werger,et al.  Canopy Structure and Photon Flux Partitioning Among Species in a Herbaceous Plant Community , 1995 .

[22]  R. W. Skaggs,et al.  EXPERIMENTAL DETERMINATION OF THE HYDROLOGIC COMPONENTS OF A DRAINED FOREST WATERSHED , 1991 .

[23]  D. Amatya,et al.  Hydrologic and Water Quality Effects of Harvesting and Regeneration of a Drained Pine Forest , 2006 .

[24]  R. Ceulemans,et al.  Simulated soil CO2 efflux and net ecosystem exchange in a 70-year-old Belgian Scots pine stand using the process model SECRETS , 2001 .

[25]  R. W. Skaggs,et al.  Energy and water balance of two contrasting loblolly pine plantations on the lower coastal plain of North Carolina, USA , 2010 .

[26]  N. Breda.  Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. , 2003, Journal of experimental botany.

[27]  H. Lee Allen,et al.  What is Ahead for Intensive Pine Plantation Silviculture in the South , 2005 .

[28]  J. Norman,et al.  Instrument for Indirect Measurement of Canopy Architecture , 1991 .

[29]  P. Stenberg,et al.  Performance of the LAI-2000 plant canopy analyzer in estimating leaf area index of some Scots pine stands. , 1994, Tree physiology.

[30]  Richard H. Waring,et al.  Fertilization effects on forest carbon storage and exchange, and net primary production: A new hybrid process model for stand management. , 2006 .

[31]  R. W. Skaggs,et al.  A water management model for shallow water table soils , 1978 .

[32]  Changsheng Li,et al.  An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems , 2002 .

[33]  James M. Vose,et al.  Long-term hydrologic and water quality responses following commercial clearcutting of mixed hardwoods on a southern Appalachian catchment , 2001 .

[34]  S. T. Gower,et al.  Rapid Estimation of Leaf Area Index in Conifer and Broad-Leaf Plantations , 1991 .

[35]  R. Allen,et al.  Evapotranspiration and Irrigation Water Requirements , 1990 .

[36]  V. Sit,et al.  CATALOGUE OF CURVES FOR CURVE FITTING , 1994 .

[37]  H. Lee Allen,et al.  Direct and indirect estimates of Leaf Area Index (LAI) for lodgepole and loblolly pine stands , 2006, Trees.

[38]  Ge Sun,et al.  MODELING THE FOREST HYDROLOGY OF WETLAND‐UPLAND ECOSYSTEMS IN FLORIDA 1 , 1998 .

[39]  R. W. Skaggs,et al.  Hydrologic Model for Drained Forest Watershed , 1992 .

[40]  D. Amatya,et al.  EFFECTS OF CONTROLLED DRAINAGE ON STORM EVENT HYDROLOGY IN A LOBLOLLY PINE PLANTATION 1 , 2000 .

[41]  R. Bailey,et al.  Loblolly Pine—Pushing the Limits of Growth , 2001 .

[42]  J. Haywood,et al.  Long-term trends in loblolly pine productivity and stand characteristics in response to thinning and fertilization in the West Gulf region , 2004 .

[43]  H. L. Allen,et al.  Long term growth responses of loblolly pine to optimal nutrient and water resource availability , 2004 .

[44]  John R. Williams,et al.  LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT 1 , 1998 .

[45]  J. Monteith.  Evaporation and environment. , 1965, Symposia of the Society for Experimental Biology.

[46]  R. Skaggs,et al.  Simulation and Evaluation of Water Management Systems for a Pine Plantation Watershed , 1992 .

[47]  N. Comerford,et al.  Biomass development for intensively managed loblolly pine plantations growing on Spodosols in the southeastern USA , 2002 .

[48]  Bill Shipley,et al.  Interacting determinants of specific leaf area in 22 herbaceous species: effects of irradiance and nutrient availability , 1999 .

[49]  Barry D. Shiver,et al.  Early Results from an Old-Field Loblolly Pine Spacing Study in the Georgia Piedmont with Competition Control , 1993 .

[50]  Marilou Beaudet,et al.  Light extinction coefficients specific to the understory vegetation of the southern boreal forest, Quebec. , 2000 .

[51]  S. Tian,et al.  Field evaluations of a forestry version of drainmod-nii model , 2010 .

[52]  D. Amatya,et al.  Effects of controlled drainage on the hydrology of drained pine plantations in the North Carolina coastal plain , 1996 .

[53]  M. Edwards,et al.  Stand Dynamics and Plant Associates of Loblolly Pine Plantations to Midrotation after Early Intensive Vegetation Management—A Southeastern United States Regional Study , 2003 .

[54]  R. Waring,et al.  A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning , 1997 .

[55]  R. W. Skaggs,et al.  Hydrologic Modeling of a Drained Pine Plantation on Poorly Drained Soils , 2001 .

[56]  Changsheng Li.  Quantifying greenhouse gas emissions from soils: Scientific basis and modeling approach , 2007 .

[57]  H. L. Allen.  6. Silvicultural Treatments to Enhance Productivity , 2008 .

[58]  N. Thevathasan,et al.  Effects of Controlled Weed Densities and Soil Types on Soil Nitrate Accumulation, Spruce Growth, and Weed Growth , 2000 .

[59]  Shiying Tian,et al.  Development and Field-Testing of the DRAINMOD-FOREST Model for Predicting Water, Soil Carbon and Nitrogen Dynamics and Plant Growth in Drained Forests. , 2010 .