Patch selection by wintering white-tailed deer : consequences for eastern hemlock regeneration at local and landscape scales

Tsuga canadensis (eastern hemlock) is a highly shade-tolerant, late-successional, and long-lived conifer species found throughout eastern North America. It is most often found in pure or nearly pure stands, because highly acidic and nutrient poor forest floor conditions are thought to favor T. canadensis regeneration while simultaneously limiting the establishment of some hardwood species with greater nutrient requirements. Once a common species, T. canadensis is currently experiencing widescale declines across its range. The hemlock woolly adelgid (Adelges tsugae) is decimating the population across its eastern distribution. Across the Upper Great Lakes region, where the adelgid is currently being held at bay by cold winter temperatures, T. canadensis has been experiencing failures in regeneration attributed, in part, to herbivory by white-tailed deer (Odocoileus virginianus). Deer utilize T. canadensis stands as winter habitat in areas of high snow depth. Tsuga canadensis, once a major component of these forests, currently exists at just a fraction of its pre-settlement abundance due to historic logging and contemporary forest management practices, and what remains is found in small remnant patches surrounded by second- and third-growth deciduous forests. The deer population across the region, however, is likely double that of pre-European settlement times. In this dissertation I explore the relationship between white-tailed deer use of T. canadensis as winter habitat and the effect this use is having on regeneration and forest succession. For this research I quantified stand composition and structure and abiotic variables of elevation and snow depth in 39 randomly selected T. canadensis stands from across the western Upper Peninsula of Michigan. I also quantified composition and the configuration of the landscapes surrounding these stands. I measured relative deer use of T. canadensis stands as pellet group piles deposited in each stand during each of three consecutive winters, 2005-06, 2006-07, and 2007-08. The results of this research suggest that deer use of T. canadensis stands as winter habitat is influenced primarily by snow depth, elevation, and the composition and configuration of the greater landscapes surrounding these stands. Specifically, stands with more heterogeneous landscapes surrounding them (i.e., a patchy mosaic of conifer, deciduous, and open cover) had higher relative deer use than stands surrounded by homogenous deciduous forest cover. Additionally, the intensity of use and the number of stands used was greater in years with higher average snow depth. Tsuga canadensis regeneration in these stands was negatively associated with deer use and Acer saccharum (sugar maple) basal area. Of the 39 stands, 17 and 22 stands had no T. canadensis regeneration in small and large sapling categories, respectively. Acer saccharum was the most common understory tree species, and the importance of A. saccharum in the understory (stems < 10 cm dbh) of the stands was positively associated with overstory A. saccharum dominance. Tsuga canadensis establishment was associated with high-decay coarse woody debris and moss, and deciduous leaf litter inputs in these stands may be limiting access to these important microsites. Furthermore, A. saccharum is more tolerant to the effects of deer herbivory than T. canadensis, giving A. saccharum a competitive advantage in stands being utilized as winter habitat by deer. My research suggests that limited microsite availability, in conjunction with deer herbivory, may be leading to an erosion in T. canadensis patch stability and an altered successional trajectory toward one of A. saccharum dominance, an alternately stable climax species.

The spatial distribution of Copernicia alba (Morong) in the district of Bahia Negra, Paraguay

The Humid Chaco of Northeast Paraguay harbors monoculture palm savannas in which Copernicia alba is the only dominant overstory species. The study’s objective was to provide the complete spatial distribution of a simple ecosystem lacking confounding factors of overstory competition and changes in slope. Palms within six, 50 x 50m plots were marked by their GPS location and measured for dbh and total stem height. The spatial distribution was individually analyzed for each plot at the local scale up to 12 m using Ripley’s K test. For the total population including juvenile and adult plants, the sample plots contained both random and clustered distribution patterns. In each of the six plots, the juvenile populations exhibited more clustered patterns than the adult population of each plot.

Variation in carbon content of tropical tree species from Ghana

Most research on carbon content of trees has focused on temperate tree species with little information existing on the carbon content of tropical tree species. This study investigated the variation in carbon content of selected tropical tree species and compared carbon content of Khaya spp from two ecozones in Ghana. Allometric equations developed for mixed-plantation stands for wet evergreen forest verified the expected strong relationship between tree volumes and dbh (r2>0.93) and volume and dbh2×height (r2>0.97). Carbon concentration, wood density and carbon content differed significantly among species. Volume at age 12 ranged from 0.01 to 1.04 m3 per tree, and wood density was highly variable among species, ranging from 0.27 to 0.76 g cm-3. This suggests that species specific density data is critical for accurate conversion of volumes derived from allometric relationships into carbon contents. Significant differences in density of Khaya spp existed between the wet and moist semi-deciduous ecozones. The baseline species-level information from this study will be useful for carbon accounting and development of carbon sequestration strategies in Ghana and other tropical African countries.

Towards greater accuracy in individual-tree mortality regression

Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.

Small-scale timber stand management techniques : a case study of woodlots in Isangati, Tanzania

Small-scale village woodlots of less than 0.5ha are the preferred use of land for local farmers with extra land in the village of Isangati, a small community located in the southern highlands of Tanzania. Farmers view woodlots as lucrative investments that do not involve intensive labor or time. The climate is ideal for the types of trees grown and the risks are minimal with no serious threats from insects, fires, thieves, or grazing livestock. It was hypothesized that small-scale village woodlot owners were not maximizing timber outputs with their current timber stand management and harvesting techniques. Personal interviews were conducted over a five month period and field data was collected at each farmer’s woodlots over a seven month period. Woodlot field data included woodlot size, number of trees, tree species, tree height, dbh, age, and spacing. The results indicated that the lack of proper woodlot management techniques results in failure to fully capitalize on the investment of woodlots. While farmers should continue with their current harvesting rotations, some of the reasons for not maximizing tree growth include close spacing (2m x 2m), no tree thinning, extreme pruning (60% of tree), and little to no weeding. Through education and hands-on woodlot management workshops, the farmers could increase their timber output and value of woodlots.

Critical evaluation of diameter increment modelling in the Great Lakes region

Simulations of forest stand dynamics in a modelling framework including Forest Vegetation Simulator (FVS) are diameter driven, thus the diameter or basal area increment model needs a special attention. This dissertation critically evaluates diameter or basal area increment models and modelling approaches in the context of the Great Lakes region of the United States and Canada. A set of related studies are presented that critically evaluate the sub-model for change in individual tree basal diameter used in the Forest Vegetation Simulator (FVS), a dominant forestry model in the Great Lakes region. Various historical implementations of the STEMS (Stand and Tree Evaluation and Modeling System) family of diameter increment models, including the current public release of the Lake States variant of FVS (LS-FVS), were tested for the 30 most common tree species using data from the Michigan Forest Inventory and Analysis (FIA) program. The results showed that current public release of the LS-FVS diameter increment model over-predicts 10-year diameter increment by 17% on average. Also the study affirms that a simple adjustment factor as a function of a single predictor, dbh (diameter at breast height) used in the past versions, provides an inadequate correction of model prediction bias. In order to re-engineer the basal diameter increment model, the historical, conceptual and philosophical differences among the individual tree increment model families and their modelling approaches were analyzed and discussed. Two underlying conceptual approaches toward diameter or basal area increment modelling have been often used: the potential-modifier (POTMOD) and composite (COMP) approaches, which are exemplified by the STEMS/TWIGS and Prognosis models, respectively. It is argued that both approaches essentially use a similar base function and neither is conceptually different from a biological perspective, even though they look different in their model forms. No matter what modelling approach is used, the base function is the foundation of an increment model. Two base functions – gamma and Box-Lucas – were identified as candidate base functions for forestry applications. The results of a comparative analysis of empirical fits showed that quality of fit is essentially similar, and both are sufficiently detailed and flexible for forestry applications. The choice of either base function in order to model diameter or basal area increment is dependent upon personal preference; however, the gamma base function may be preferred over the Box-Lucas, as it fits the periodic increment data in both a linear and nonlinear composite model form. Finally, the utility of site index as a predictor variable has been criticized, as it has been widely used in models for complex, mixed species forest stands though not well suited for this purpose. An alternative to site index in an increment model was explored, using site index and a combination of climate variables and Forest Ecosystem Classification (FEC) ecosites and data from the Province of Ontario, Canada. The results showed that a combination of climate and FEC ecosites variables can replace site index in the diameter increment model.

ANALYSIS OF POPULUS TREMULOIDES CLONAL VARIATION AND DELINEATION IN THE OTTAWA NATIONAL FOREST

The technique of delineating Populus tremuloides (Michx.) clonal colonies based on morphology and phenology has been utilized in many studies and forestry applications since the 1950s. Recently, the availability and robustness of molecular markers has challenged the validity of such approaches for accurate clonal identification. However, genetically sampling an entire stand is largely impractical or impossible. For that reason, it is often necessary to delineate putative genet boundaries for a more selective approach when genetically analyzing a clonal population. Here I re-evaluated the usefulness of phenotypic delineation by: (1) genetically identifying clonal colonies using nuclear microsatellite markers, (2) assessing phenotypic inter- and intraclonal agreement, and (3) determining the accuracy of visible characters to correctly assign ramets to their respective genets. The long-term soil productivity study plot 28 was chosen for analysis and is located in the Ottawa National Forest, MI (46° 37'60.0" N, 89° 12'42.7" W). In total, 32 genets were identified from 181 stems using seven microsatellite markers. The average genet size was 5.5 ramets and six of the largest were selected for phenotypic analyses. Phenotypic analyses included budbreak timing, DBH, bark thickness, bark color or brightness, leaf senescence, leaf serrations, and leaf length ratio. All phenotypic characters, except for DBH, were useful for the analysis of inter- and intraclonal variation and phenotypic delineation. Generally, phenotypic expression was related to genotype with multiple response permutation procedure (MRPP) intraclonal distance values ranging from 0.148 and 0.427 and an observed MRPP delta value=0.221 when the expected delta=0.5. The phenotypic traits, though, overlapped significantly among some clones. When stems were assigned into phenotypic groups, six phenotypic groups were identified with each group containing a dominant genotype or clonal colony. All phenotypic groups contained stems from at least two clonal colonies and no clonal colony was entirely contained within one phenotypic group. These results demonstrate that phenotype varies with genotype and stand clonality can be determined using phenotypic characters, but phenotypic delineation is less precise. I therefore recommend that some genetic identification follow any phenotypic delineation. The amount of genetic identification required for clonal confirmation is likely to vary based on stand and environmental conditions. Further analysis, however, is needed to test these findings in other forest stands and populations.