Stand-level Growth Research Articles

Stand-level yield model for Scots pine (Pinus sylvestris L.) in north-east Spain

Simultaneous stand-level growth and yield models for Pinus sylvestris in north-east Spain were developed based on 21 permanent sample plots established in 1964 by the Instituto Nacional de Investigaciones Agrarias (INIA). The plots ranged in site index from 13 to 26 m (dominant height at 100 years), and were measured an average of 5 times. The estimation data consisted of 79 growth periods of stands ranging in age from 36 to 132 years. Non-linear three-stage least squares method was used to simultaneously fit prediction and projection equations for stand basal area, volume and stand density. An existing model for dominant height growth fitted with the same estimation data was used to project dominant height. The models were evaluated both quantitatively and qualitatively. Correlation among error components of the prediction equations for basal area and volume as well as the projection equations for number of trees per hectare and volume were strong and significant. The mean biases for basal area, volume and number of trees per hectare predictions were positive. The presented system of models can serve for forest-level management planning as a simple yield prediction system that requires only stand level input data.

Simultaneous growth and yield models forEucalyptus grandis(Hill) Maiden plantations in Zimbabwe

Synopsis Simultaneous stand-level growth and yield models for Eucalyptus grandis in Zimbabwe were developed from Correlated Curve Trend (CCT) and NeIder wheel experiments replicated on five different sites. Nonlinear three-stage least squares method was used to simultaneously fit prediction and projection equations for stand basal area, volume and stand density (S/ha). The age-dominant height model was fitted separately to the data to enable the estimation of site indices for the plots. The data consisted of a total of313 growth periods of stands ranging in age from 1.3 years to 19.5 years, and site indices from 14 m to 37 m (at an index age of7 years). The models were validated both quantitatively and qualitatively. Correlation between error components for basal area and volume was strong and significant while the correlation of stand density with basal area and volume was either weak or non-significant. Degree of determination was relatively high for all the models. The mean biases for basal area, volum...

Effects of Mixed Stand Management to Reduce Impacts of Spruce Budworm Defoliation on Balsam Fir Stand-Level Growth and Yield

Abstract Mixed hardwood-balsam fir stand management has been proposed as one silvicultural technique to reduce spruce budworm damage to balsam fir. An analysis was conducted using published results from New Brunswick, Canada, and northern New England, USA, to assess whether optimum hardwood levels (percent volume) could be determined for various levels of budworm defoliation. The goal was to maximize standing balsam fir volume and to determine trade-offs between reduced damage (hence reduced volumes losses) versus the amount of fir volume lost as a result of allocating growing space to hardwood species. Optimum hardwood levels depended on severity of budworm attack. Below 45% defoliation (5 yr average), the amount of balsam fir volume lost to increased hardwood growing space exceeded the amount of volume protected. As defoliation severity increased above 45%, the optimal hardwood levels increased. At severe levels of defoliation (> 75%) optimal hardwood content was approximately 50% of initial standing volume. The results suggest that mixed stand management can potentially reduce balsam fir volume losses in areas with frequent severe spruce budworm outbreaks. North. J. Appl. For. 16(1):19-24.

Modeling Stand Level Growth and Yield Response to Silvicultural Treatments

Abstract As plantation growth and yield research lead to new, more intensive, and site-specific silvicultural prescriptions, there is a perpetual need to adjust existing yield prediction models to reflect the response to these practices. A height growth model that includes a treatment response term to accommodate different expected response patterns is presented. This model is shown to provide an accurate description of the observed average dominant height growth response of slash pine plantations to several silvicultural treatments, relative to standard practice. An existing per-acre basal area prediction model for unthinned plantations that includes average dominant height as a predictor variable, in addition to age and trees per acre, also required an adjustment term to adequately reflect treatment effects on stand basal area growth. No such adjustment appeared to be necessary, to account for different silvicultural practices, to an existing stand level volume prediction model that includes both average dominant height and basal area per acre as predictor variables, in addition to age and trees per acre. For. Sci. 41(3):629-638.

RPGrow$: A Red Pine Analysis Spreadsheet for the Lake States

Abstract RPGrow$ is a spreadsheet that interactively projects standlevel growth and yield with financial analysis of red pine plantations in the Lake States. Three types of commonly found conditions related to red pine management can be analyzed: (1) an entire rotation from initial planting to final harvest; (2) an existing stand from any point in time until final harvest; and (3) conversion of an existing stand to red pine (marginal analysis). Stand growth projections are for 70 yr. User input includes site index, stand age, initial basal area, trees per acre, thinning regime, costs associated with establishment and culture, tax rates, inflation rate, and discount rate. RPGrow$ calculates and values pulpwood and sawtimber volumes from user-defined stumpage prices. The financial analysis uses discounted cash flow methods to calculate results both with and without tax effects. Different stand management scenarios and economic factors can be compared easily through sensitivity analysis. North. J. Appl. For. 11(4):141-145.

Linking individual-tree and stand-level growth models

An algorithm is presented to provide a linkage between stand-level models and individual-tree models. The algorithm is based on the assumptions that stand-level estimates of basal area, trees per unit area, and average diameter are correct and that the projected individual trees must be adjusted to equate to the stand-level estimates. The form of the individual-tree model is not important so long as initial and projected tree lists are provided. It is further assumed that the relative growth between individuals is to be maintained and the adjusted survivals are restricted to be less than or equal to 100%. Simplification of the general algorithm are also developed. These simplifications take the form of dropping the survival equation from the individual-tree model and dropping the average diameter estimate from the stand-level model. Examples are provided of a bimodal diameter distribution.

Growth trends and stand dynamics in natural loblolly pine in the southeastern United States

A number of recent studies have shown reduced stand-level and individual-tree growth in natural loblolly pine (Pinustaeda L.) stands in the southeastern United States. This study uses increment cores from dominant and codominant trees to determine if individual-tree growth has changed from 1915 to 1985. The cores are grouped for comparison by first sorting on the basis of median stand age and then further sorting these groups of cores by individual-tree age. These trees experienced increasing basal area increments from the mid-1940s into the mid-1970s, after which growth rates returned to preincrease levels. These data support recent findings of growth reductions, but also indicate previously unreported growth increases preceding the growth decreases. These and supplemental permanent plot data suggest that stand dynamics is a viable hypothesis for explaining these growth trends.

Growth Reductions in Naturally Regenerated Southern Pine Stands in Alabama and Georgia

Abstract Data from Forest Inventory and Analysis (FIA) units of the USDA Forest Service were used to compare average annual stand-level basal area accretion onto survivor pines in naturally regenerated pine stands throughout Alabama and Georgia. Growth rates measured between 1972-82 were compared to growth rates during the previous 10-year survey cycle in each state. Separate analyses were conducted for loblolly (Pinus taeda), longleaf (P. palustris), shortleaf (P. echinata), and slash (P. elliottii) pine cover types. The unadjusted average stand-level growth rates for survivor pines 1.0 in. diameter and greater at breast height were notably lower for all cover types during the latter survey in Georgia, while only the average unadjusted growth of shortleaf was substantially lower during this period in Alabama. However, when growth rates were adjusted with regression models to account for differences in initial stand structure (stand size class, stand density, site quality class, hardwood competition, and mortality) between the two survey periods, reductions in average adjusted basal area growth ranged from 3% to 31% during the later cycle in both states. The reductions were statistically significant in almost every case. The agents causing the growth differences were not identified, but it is unlikely that stand dynamics are responsible. The observational nature of the FIA dataset precludes further resolution of causal relationships. South. J. Appl. For. 15(2):73-79.

Modelling the Sustainability of Forest Production and Yield for a Changing and Uncertain Future

The expected growth of the human population to about 11 billion sometime within the next rotation of most northern temperate forest crops will put greatly increased and varied demands on today's forested lands. Development of the timber resources on those lands that remain dedicated to timber production must be demonstrably sustainable if forest management is to help arrest rather than aggravate the continuing deterioration of the global environment, and if managed forests are to be a carbon sink rather than a carbon source with respect to the global "green-house effect". Unfortunately, the experience-based models traditionally used by foresters cannot make accurate predictions of future forest growth, yield, and carbon balance for the altered growing conditions that are expected to accompany this increase in human numbers. These tools are therefore unsuitable as a means of assessing the sustainability of site productivity under current or anticipated future forest management practices and the expected future soil, climate, and biotic conditions. It is time for foresters around the world to confront this issue and to develop and use more ecologically-sensitive, ecosystem-level stand growth and yield models.Knowledge-based, process-simulation stand growth models have many theoretical advantages, and are the only way of predicting future forest growth and carbon budgets on a particular site in the absence of accurate data on the past growth of forests on that site. However, such models have generally had significant practical limitations as an alternative to traditional forest yield models. They have either been too simple, or, if sufficiently complex, have had unacceptably large calibration data requirements, which has limited their portability. This has restricted most process-based simulation models to research and educational applications.An alternative approach which combines both the experience-based and the knowledge-based approaches offers a more practical alternative. The combination of "historical bioassay" and process-based modelling approaches into "hybrid simulation" stand models can provide a means by which to rank the most probable outcomes and the sustainability of alternative stand-level management strategies under a variety of possible future growing conditions.The accuracy of most forest management and forest economics models ultimately depends on the accuracy of stand-level growth models. As the world experiences increasing problems of air pollution (acid rain and the greenhouse effect), soil degradation, and deforestation, there is an urgent need for foresters to use ecosystem-level growth models that are sensitive to human-induced and naturally caused environmental changes. Use of such models is a necessary prerequisite to good stewardship of forest land and our legacy to future generations.

A stand-level multispecies growth model for Appalachian hardwoods

A stand-level growth and yield model was developed to predict future diameter at breast height (dbh) distributions of thinned stands of mixed Appalachian hardwoods. The model allows prediction by species group and dbh class. Stand attributes (basal area per unit area, trees per unit area, minimum stand dbh, and arithmetic mean dbh) were projected through time for the whole stand and for individual species groups. Future dbh distributions were obtained using the three-parameter Weibull probability density function and a variation of the parameter recovery method. The recovery method used employed the first two noncentral moments of dbh (arithmetic mean dbh and quadratic mean dbh2) to generate Weibull parameters. Future dbh distributions were generated for the whole stand and every species group but one; the diameter distribution for the remaining species group was obtained by subtraction.