The growth and productivity of kauri (Agathis australis (D. Don) Lindl.) in even-aged single-species planted stands and mixed-aged second-growth natural stands has been studied. Stand-level models of height, basal area and whole-tree volume were developed. Kauri growth and productivity in planted stands up to 83 years old were compared to that of natural stands that were up to 196 years of age. Within natural stands, the effect of thinning treatments on growth and productivity was also assessed. Models of growth and productivity were initially developed for each of the three different kauri stand types independently (planted, second-growth unthinned and thinned). Combined data sets allowed for the development of single models that were able to fit all stands. A Schumacher equation with local slope parameter and asymptote bounded at 45 m gave the best fit for height growth, while a von Bertalanffy-Richards equation in difference form with local slope parameter gave the best fit for basal area growth. Kauri in all stand types were found to be slow to establish with little height growth in planted stands for the first five years after planting, and for the first 25 years in natural stands. Similar trends were observed for basal area and whole-tree volume development. Models developed in this study are relevant only to kauri in the “ricker” or monopodial form irrespective of age, and for stands from 320-2000 stems/ha. Kauri growth and productivity in planted stands was substantively better than that in second-growth stands. Planted kauri had height increment of 0.4 m/yr for periods of up to 30 years. At age 50, planted kauri was predicted to be 20 m in height, over twice the height of kauri in natural stands, and to be 28.1 m by 100 years. Basal area at age 50 averaged 64.9 m2/ha for all planted stands, and was predicted to be 98.2 m2/ha at age 100. Whole-tree volume was predicted to increase by 11.7 m3/ha/annum for all stands, but was as high as 20.6 m3/ha/yr in one 70 year old stand. The maximum productivity of kauri was observed in one high-performing young kauri planted stand where whole-tree volume increment in excess of 30 m3/ha/yr were predicted for a period from age 15-30. Carbon sequestration was calculated from the volume model and predicted to be 316 t C/ha and 1168 t CO2/ha at age 100. Mortality of kauri in planted stands was as high as 3.9%/yr for individual stands, over their entire rotation to date. For all stands, mortality averaged 0.56%/yr. The highest mortality occurred in the years before the first assessment and averaged 0.64%/yr for all stands. From the first to the last assessment mortality averaged 0.30%/yr. Where mortality in individual stands was above the average rate the dominant cause was drought. The growth and productivity of kauri in second-growth stands was only marginally improved by thinning to reduce competition. The volume removed in thinning operations had not been replaced in the (up to) 50 years since thinning treatments were applied. At age 150, the predicted height of kauri in unthinned control and thinned stands were identical at 25.9 m. Basal area at age 150 was 64.5 m2/ha in unthinned stands and 52.6 m2/ha in thinned stands. Whole-tree volume was predicted to be 681 m3/ha in unthinned and 549 m3/ha in thinned stands. Volume increment peaked at 5.2 m3/ha/yr in unthinned stands and 4.7 m3/ha/yr in thinned stands. This study has shown that the worst growth and productivity of kauri in planted stands was better than that of the best natural stands. The difference in performance between plantation and second-growth kauri was most likely a result of a combination of lower site quality characteristics (soil type and fertility), stand structure and within-stand competition of natural stands. The data for planted kauri came from 31 permanent sample plots located in 25 planted stands. These stands ranged in age from 14-83 years at the last assessment, and ranged in stand density from 218-1800 stems/ha. The overall number of planted stands and plots from which data was available to develop models was small in comparison to many exotic forest species datasets. The majority of the planted stands were not silviculturally treated after planting, and considerable variation in establishment methods was recorded. The results of productivity from the models developed for planted kauri should therefore be considered to be conservative. The results of this study indicate an opportunity to grow kauri in plantations on good quality sites for the production of high quality sapwood timber over rotations of 60 years or less. They also indicate that second-growth stands will produce usable volumes of timber, but only over extended periods of time. To ensure that kauri in planted stands can meet the potential observed during the development of these models, a series of well-managed stands on a range of sites is urgently required where the effects of timely silviculture, including initial stand density, can be assessed, quantified and reported on. Further research on selection and breeding for the species would improve the early establishment and growth of planted kauri resulting in a reduced rotation length. Research on long-term management strategies that include continuous cover forestry may make the species an attractive proposition for carbon forestry and/or for the production of high quality, naturally durable heartwood. The dataset compiled for this study was the best data available. While it cannot as yet be used to develop prescriptions for the establishment and maintenance of planted kauri stands, it does provide clues and directions that should be pursued in further research, however.

No description available.

Diss. (sammanfattning). Uppsala : Sveriges lantbruksuniv., 2003. / Härtill 6 uppsatser.

Improved soil water conservation has become an important subject in semi-arid areas due to low and erratic rainfall which is often combined with higher temperatures to provide unsuitable conditions for successful crop productivity. Dryland agriculture remains vulnerable to yield losses in these areas. This calls for implementation of conservation agricultural practices that would improve dryland maize productivity. An on-station field trial was started in 2007 at Zeekoegat experimental farm (24 kilometers north of Pretoria), to establish the effect of different conservation agriculture practices on soil and plant properties. The experimental lay-out was a split-plot randomized complete block design, replicated three times, with each replicate split into two tillage systems (whole plots) and then each whole plot (reduced tillage (RT) and conventional tillage (CT)) was subdivided into 12 treatments (two fertilizer levels x 6 cropping patterns). The present study explored the impacts of different tillage practices, cropping patterns and fertilization levels on soil water content, soil temperature and dryland maize productivity during the 2010/11 and 2011/12 growing seasons. To improve the quality of soil water content (SWC) data, the effect of correction for concretions on soil bulk density and the relationship between volumetric soil water content (SWC) vs neutron water meter (NWM) count ratios was also investigated. Corrections for concretions on soil bulk density did not improve NWM calibrations in this study. In all seasons, significantly higher mean SWC was found under RT treatment than in CT at all depths except at 0-300 mm. For example, during the 2010/11 growing season, SWC under RT was 1.32 % and 1.10 % higher than CT for the 300 – 1350 mm and 0 – 1350 mm soil profiles, respectively. The mean weekly SWC was consistently higher for RT throughout both the growing seasons. Significantly higher SWC was also found under monoculture at all soil depths (except at 0-300 mm during 2011/12) compared to treatments under intercropping. For example, during 2010/11, at 0-300mm, SWC under maize monoculture was 1.72 % higher than under intercropping. The maximum and minimum soil temperatures were significantly higher at 100 and 400 mm soil depths under CT than under RT during 2010/11. During 2011/12, significantly higher minimum soil temperatures at 100 mm depth and lower temperature differences (maximum – minimum soil temperatures) at 400 mm depth were observed under intercropping. Despite the higher SWC and reduced soil temperature under RT, the maize seeds emergence rate was lower and plant stand was reduced. This is attributed to other factors associated with RT systems such as increased soil penetration resistance which often leads to poor root development. The lower soil temperatures under RT were generally within the range that would not be expected to inhibit growth and uptake of nutrients. Slower growth under RT resulted in lower biomass and grain yield. Plants that received high fertilizer rates grew more vigorously than plants under lower fertilizer levels when water was not a limiting factor, but produced lower grain yield due to water shortage in March, especially in 2011/12. The harvest index was therefore lower for treatments that received high fertilizer levels. Maize biomass under monoculture x low fertilizer level was significantly lower compared to other fertilizer x cropping pattern treatments. Maize plant growth under intercropping was improved throughout the seasons, which led to significantly higher grain yield than under maize monoculture. It is therefore recommended that farmers in dryland areas take the advantage of intercropping maize with legumes to obtain higher maize productivity. Further research should focus on investigating the possibility of roots restrictions occurring under RT conditions and under various environmental and soil conditions. / Dissertation (MScAgric)--University of Pretoria, 2014. / lk2014 / Plant Production and Soil Science / MScAgric / Unrestricted

The Mississippi Institute for Forest Inventory (MIFI) multi-product forest inventory divides Mississippi into five inventory regions with one region inventoried each year on a rotating basis. Resource analyses that overlap these temporally separated regions require adjustment to a common comparative time base by applying appropriate forest stand growth and harvest allocation models to the portions of a selected area not inventoried at the desired common time base. Currently the Mississippi Dynamic Inventory Reporter (MDIR) does not make adjustments to temporally synchronize portions of user selected working circles, polygons, or counties that occur in separate inventory regions. Separate inventory reports for each overlap area must be prepared to which growth and harvest are manually allocated to bring each area to the same point in time. The study objective was to provide an automated solution to temporal reconciliation by developing a growth and yield system that reconciles modeled timber volume growth, mortality, and harvests with known values from previous successive inventories and state tax records of harvested volumes at the county level. The modeling effort focused on constructing an optimized system for the Southwest MIFI 2004 and 2012 inventories. Species group specific, distance independent, tree-list models, including probability of survival and diameter growth equations, were developed through logistic and linear regressions, respectively. Probability of survival models were assessed for model performance using logistic regression concordant/discordant pairs. R2 and parameter p-values were used to evaluate diameter growth model performance. As the 2004 and 2012 datasets are each composed of randomly selected plots within the Southwest region, county totals were used for temporal comparison. County level Doyle volume calibration was within 150 units of tolerance for all counties in the Southwest region. The resulting growth and yield system represents a successful effort to develop a methodology for bridging temporally separated MIFI inventory analyses, while providing newly developed diameter and mortality equations for the state. The accompanying computer application allows the addition of both enhanced growth and yield and stand table projection models. System implementation will greatly reduce the time required for producing multi-temporal analyses and, thus, increase their usability and functionality.

The importance of bottomland hardwood (BLH) forests to support the economy through timber production and carbon sequestration is acknowledged; however, their full potential is yet to be explored. This study developed variable density yield models for BLH oak-gum-cypress forests along the US Gulf Coast and Lower Mississippi River Delta. The models, with an adjusted R2 of 98% for cubic foot growing stock volume and 77% for Doyle board foot sawlog volume, are expected to be valuable tools for landowners and managers seeking to make informed decisions about BLH forest management. A carbon stock model was also developed, and carbon sequestration was explored based on basal area increment. The results showed potential for carbon sequestration with an average carbon stock of 30.56 tons/acre and a maximum average discounted present value of carbon accumulation of $15.94/ton/acre/year. This provides valuable information to managers and landowners willing to participate in carbon credit markets.

Little information is available to nonindustrial-private forest (NIPF) owners regarding economic tradeoffs between managing pine plantations for timber production or wildlife habitat. Loblolly (Pinus taeda) and longleaf (Pinus palustris) pine plantations were modeled to quantify economic tradeoffs for competing management scenarios utilizing densities aimed at wildlife habitat or timber production in Mississippi. Models contained a range of site indices, planting densities, and rotation lengths for timber maximization and white-tailed deer (Odocoileus virginianus) or northern bobwhite (Colinus virginianus) habitat production. All management scenarios in loblolly plantations produced positive Land Expectation Values (LEVs), while one fifth of the management scenarios in longleaf plantations produced positive LEVs. Comparison to the regional hunting lease rate the compensatory lease rates from the study could be realized, making wildlife management as valuable as timber management. The results of this study will help landowners be more informed about economic tradeoffs when making management decisions on their property.

A greater emphasis is being placed on hardwood management, yet there has been relatively little effort to develop growth and yield information for hardwood forest types. Measurements on permanent growth and yield plots collected in 1981, 1988, 1994, and 2006 in minor stream bottoms in Mississippi and Alabama were used to construct a stand level growth and yield model for red oak/sweetgum stands. The model predicts arithmetic mean diameter, quadratic mean diameter, trees per acre, basal area, total tree height, and cubic foot volume per acre for the total stand and by species. Different sets of equations were constructed depending on the amount of information known about a hardwood stand. Models were chosen based on significance of variables, coefficient of determination, index of fit, and biological trends. Predicted stand development patterns are discussed. These models will be base models for a complete diameter distribution growth and yield model.

The purpose of this research was to model the growth and yield of bottomland hardwood forests of the Lower Mississippi Alluvial Valley and to explain the economic tradeoffs of even- and uneven-aged management. The US Forest Service (USFS) Forest Vegetation Simulator was used to model growth and yield for four different bottomland hardwood forest types using USFS inventory data. Even- and uneven-aged management scenarios were optimized for timber revenue maximization using the Land Expectation Value formula. Analyses suggested that growth and yield of even-aged and uneven-aged management approaches differ in terms of end products and harvesting time. The even-aged management scenarios performed better over the uneven-aged management scenarios with few exceptions; however, the magnitude of the economic tradeoff depended upon initial stand conditions and required rates of return. These analyses will allow landowners to understand how much economic gain or loss they may realize by adopting an alternative management.

The purpose of this study was to determine if control charts are an effective tool to identify trends in forest growth and yield model accuracy. Accurate forest growth and yield models are important for projecting future forest composition. However, environmental factors have the potential to make forest growth models created from historic data inaccurate. Control charts in this study determine if forest growth predictions fall within confidence limits established for historic growth at a number of points in time. Two data sets were used in this study: the first was a Continuous Forest Inventory (CFI) from three tracts at the University of Tennessee Cumberland Research Station and the second data set was Forest Inventory and Analysis data collected by the U.S. Forest Service. The CFI plots represented a stand level data set measured every 5 years from 1962-1977 and revisited for a re-measurement in 2009. The FIA plots were a regional data with subsets of plots measured annually from 1999-2008. The FIA data set was limited to plots of the oak/hickory forest type from Tennessee, Alabama, and Georgia. Two forest growth and yield models were used to predict growth: (1) WinYield and (2) Forest Vegetation Simulator (FVS). The two different data sets were used with both FVS and WinYield to evaluate control charts using different models ad at different spatial and temporal scales. The data sets were also subset by site index, stand age, stocking percent, aspect, and species composition to determine if control charts could identify changes in model accuracy for forests subjected to different growing conditions. The CFI and FIA data had short growth predictions and control charts indicated that there were no trends affecting accuracy. The CFI data also had a long growth prediction of 32 years and the control charts found that the predictions using WinYield and FVS were inaccurate, indicating that there may be a trend causing inaccuracy in the model.