Linear mixed models for longitudinal shape data with applications to facial modeling

We present a novel application of methods for analysis of high-dimensional longitudinal data to a comparison of facial shape over time between babies with cleft lip and palate and similarly aged controls. A pairwise methodology is used that was introduced in Fieuws and Verbeke (2006) in order to apply a linear mixed-effects model to data of high dimensions, such as describe facial shape. The approach involves fitting bivariate linear mixed-effects models to all the pairwise combinations of responses, where the latter result from the individual coordinate positions, and aggregating the results across repeated parameter estimates (such as the random-effects variance for a particular coordinate). We describe one example using landmarks and another using facial curves from the cleft lip study, the latter using B-splines to provide an efficient parameterization. The results are presented in 2 dimensions, both in the profile and in the frontal views, with bivariate confidence intervals for the mean position of each landmark or curve, allowing objective assessment of significant differences in particular areas of the face between the 2 groups. Model comparison is performed using Wald and pseudolikelihood ratio tests.     

Historical and projected carbon balance of mature black spruce ecosystems across North America: the role of carbon–nitrogen interactions

The role of carbon (C) and nitrogen (N) interactions on sequestration of atmospheric CO₂ in black spruce ecosystems across North America was evaluated with the Terrestrial Ecosystem Model (TEM) by applying parameterizations of the model in which C–N dynamics were either coupled or uncoupled. First, the performance of the parameterizations, which were developed for the dynamics of black spruce ecosystems at the Bonanza Creek Long-Term Ecological Research site in Alaska, were evaluated by simulating C dynamics at eddy correlation tower sites in the Boreal Ecosystem Atmosphere Study (BOREAS) for black spruce ecosystems in the northern study area (northern site) and the southern study area (southern site) with local climate data. We compared simulated monthly growing season (May to September) estimates of gross primary production (GPP), total ecosystem respiration (RESP), and net ecosystem production (NEP) from 1994 to 1997 to available field-based estimates at both sites. At the northern site, monthly growing season estimates of GPP and RESP for the coupled and uncoupled simulations were highly correlated with the field-based estimates (coupled: R ²= 0.77, 0.88 for GPP and RESP; uncoupled: R ² = 0.67, 0.92 for GPP and RESP). Although the simulated seasonal pattern of NEP generally matched the field-based data, the correlations between field-based and simulated monthly growing season NEP were lower (R ² = 0.40, 0.00 for coupled and uncoupled simulations, respectively) in comparison to the correlations between field-based and simulated GPP and RESP. The annual NEP simulated by the coupled parameterization fell within the uncertainty of field-based estimates in two of three years. On the other hand, annual NEP simulated by the uncoupled parameterization only fell within the field-based uncertainty in one of three years. At the southern site, simulated NEP generally matched field-based NEP estimates, and the correlation between monthly growing season field-based and simulated NEP (R ² = 0.36, 0.20 for coupled and uncoupled simulations, respectively) was similar to the correlations at the northern site. To evaluate the role of N dynamics in C balance of black spruce ecosystems across North America, we simulated historical and projected C dynamics from 1900 to 2100 with a global-based climatology at 0.5° resolution (latitude × longitude) with both the coupled and uncoupled parameterizations of TEM. From analyses at the northern site, several consistent patterns emerge. There was greater inter-annual variability in net primary production (NPP) simulated by the uncoupled parameterization as compared to the coupled parameterization, which led to substantial differences in inter-annual variability in NEP between the parameterizations. The divergence between NPP and heterotrophic respiration was greater in the uncoupled simulation, resulting in more C sequestration during the projected period. These responses were the result of fundamentally different responses of the coupled and uncoupled parameterizations to changes in CO₂ and climate.     

Trade-offs in covariate selection for species distribution models: a methodological comparison

Species distribution models (SDMs) are a common approach to describing species’ space-use and spatially-explicit abundance. With a myriad of model types, methods and parameterization options available, it is challenging to make informed decisions about how to build robust SDMs appropriate for a given purpose. One key component of SDM development is the appropriate parameterization of covariates, such as the inclusion of covariates that reflect underlying processes (e.g. abiotic and biotic covariates) and covariates that act as proxies for unobserved processes (e.g. space and time covariates). It is unclear how different SDMs apportion variance among a suite of covariates, and how parameterization decisions influence model accuracy and performance. To examine trade-offs in covariation parameterization in SDMs, we explore the attribution of spatiotemporal and environmental variation across a suite of SDMs. We first used simulated species distributions with known environmental preferences to compare three types of SDM: a machine learning model (boosted regression tree), a semi-parametric model (generalized additive model) and a spatiotemporal mixed-effects model (vector autoregressive spatiotemporal model, VAST). We then applied the same comparative framework to a case study with three fish species (arrowtooth flounder, pacific cod and walleye pollock) in the eastern Bering Sea, USA. Model type and covariate parameterization both had significant effects on model accuracy and performance. We found that including either spatiotemporal or environmental covariates typically reproduced patterns of species distribution and abundance across the three models tested, but model accuracy and performance was maximized when including both spatiotemporal and environmental covariates in the same model framework. Our results reveal trade-offs in the current generation of SDM tools between accurately estimating species abundance, accurately estimating spatial patterns, and accurately quantifying underlying species–environment relationships. These comparisons between model types and parameterization options can help SDM users better understand sources of model bias and estimate error.     

Trends and uncertainties in budburst projections of Norway spruce in Northern Europe

Budburst is regulated by temperature conditions, and a warming climate is associated with earlier budburst. A range of phenology models has been developed to assess climate change effects, and they tend to produce different results. This is mainly caused by different model representations of tree physiology processes, selection of observational data for model parameterization, and selection of climate model data to generate future projections. In this study, we applied (i) Bayesian inference to estimate model parameter values to address uncertainties associated with selection of observational data, (ii) selection of climate model data representative of a larger dataset, and (iii) ensembles modeling over multiple initial conditions, model classes, model parameterizations, and boundary conditions to generate future projections and uncertainty estimates. The ensemble projection indicated that the budburst of Norway spruce in northern Europe will on average take place 10.2 ± 3.7 days earlier in 2051–2080 than in 1971–2000, given climate conditions corresponding to RCP 8.5. Three provenances were assessed separately (one early and two late), and the projections indicated that the relationship among provenance will remain also in a warmer climate. Structurally complex models were more likely to fail predicting budburst for some combinations of site and year than simple models. However, they contributed to the overall picture of current understanding of climate impacts on tree phenology by capturing additional aspects of temperature response, for example, chilling. Model parameterizations based on single sites were more likely to result in model failure than parameterizations based on multiple sites, highlighting that the model parameterization is sensitive to initial conditions and may not perform well under other climate conditions, whether the change is due to a shift in space or over time. By addressing a range of uncertainties, this study showed that ensemble modeling provides a more robust impact assessment than would a single phenology model run.     

Model-based Evidence for Cyclic Phenomena in a High-Elevation,Two-Species Forest

Cyclic phenomena have been the focus of many studies in stressed conifer forests. In these systems, suppressed seedlings are released following the synchronous death of canopy trees. These cycles occur over hundreds of years, and thus studying them in the field is difficult, if not impossible in some cases. This difficulty highlights the advantages of vegetation modeling studies. We used the individual-based gap model, University of Virginia Forest Model Enhanced (UVAFME), to simulate forest dynamics over time at a high-elevation, subalpine forest (dominated by Engelmann spruce and subalpine fir) in southern Wyoming. Following model calibration, UVAFME was validated by running it up an elevation gradient to determine if it could simulate changes in species composition with elevation. UVAFME was then run exclusively at the high-elevation location for periods of 3000 years to simulate long-term forest dynamics at the site. It was found that without the intrusion of exogenous disturbances, the subalpine zone of the Rocky Mountains demonstrates cyclic phenomena, both at the plot scale and the landscape scale. By itself, Engelmann spruce demonstrates a natural periodicity of 300 years, whereas subalpine fir has a natural periodicity of 200 years. In the two-species forest, both species have a periodicity of 300 years. This output corresponds well with field data from similar high-elevation conifer sites. These results, along with other examples of cyclic phenomena in ecological systems, indicate that periodicities in ecosystems may be more common than previously thought, though they may be difficult to distinguish due to disturbances and the time- and space-scales at which they occur.     

A Study of Stand Growth Model for Pinus yunnanensis (Pinaceae) Based on Plots Data——A Case Study in Yangliu Township,Baoshan, Yunnan Province

Pinus yunnanensis is one of most important timber species in Yunnan Province, and widely distributed in southwest China. Studies on growth model have been reported, however, most of which focused on a specific part of growth model. To build detailed, easily used and accurate empirical stand growth model from the same dataset, a case study was conducted in Yangliu Township, Baoshan, Yunnan Province. A total of 86 sample plots data were collected using two stages sampling design. Several popular non-linear growth functions were fitted and compared, including Chapman-Richards, Mitscherlich, Schumacher, Gompertz, Logistic, Korf and Allometric function. Models of site index, density index, average diameter at breast height (DBH) and stock volume growth model were fitted respectively. The different models performed more or less similarly in terms of coefficients of determination and root mean square error (RMSE). However, empirical growth function “Schumacher” had lower coefficient of variation for all parameters than other models. Schumacher function was the most suitable one for site index, average DBH and stock volume growth model in all alternative functions.     

基于混合效应的大别山地区杉木树高-胸径模型比较

基于安徽省大别山区马鬃岭林场杉木人工林30块样地1087组数据,选用7个常用树高-胸径(H-D)模型(线性模型、Chapman-Richards模型、Logistic模型等),采用最小二乘法拟合并选出最优基础模型(式11,只含D变量的Chapman-Richards模型),然后基于该模型构建含林分变量优势木平均高度、密度的H-D模型(式12),同时考虑样地水平的随机效应,分别基于式11、12构建混合模型(式13、14),并用幂函数、指数函数消除误差异方差,利用决定系数(R²)、均方根误差(RMSE)、平均绝对误差(MAE)和平均相对误差绝对值(MAPE)等指标来评价模型的拟合与预测能力,最终获取最优树高预测模型.结果表明:含林分变量的模型的拟合精度(式12,R²=0.863、RMSE=1.381、MAE=0.971)优于基础模型(式11,R²=0.827、RMSE=1.554、MAE=0.101).对于误差方差,幂函数、指数函数均能较好地消除异方差,但幂函数相对最好.混合模型的拟合与预测能力均优于式11、12,但混合模型(式13、14)之间的拟合与预测精度相差不大.基于混合效应的H-D模型(式13)能够较好地描述不同林分间H-D关系的差异,实际运用中可选用该模型来预测杉木树高,具有较高的预测精度.     

Defoliation effects on the ectomycorrhizal community of a mixed Pinus contorta/Picea engelmannii stand in Yellowstone Park

Molecular genetic methods were used to determine whether artificial defoliation affects ectomycorrhizal (EM) colonization, EM fungal species richness, and species composition in a mixed Pinus contorta (lodgepole pine)/Picea engelmannii (Engelmann spruce) forest in Yellowstone National Park, Wyoming. All lodgepole pines in three replicate plots were defoliated 50%, while Engelmann spruce were left untreated. This was done to determine how defoliation of one conifer species would affect EM mutualisms of both treated and neighboring, untreated conifers. The results indicated no significant effect on either EM colonization (142.0 EM tips/core in control plots and 142.4 in treatment plots) or species richness (5.0 species/core in controls and 4.5 in treatments). However, the relative abundance of EM of the two tree species shifted from a ratio of approximately 6:1 without treatment (lodgepole EM:spruce EM), to a near 1:1 ratio post-treatment. This shift may be responsible for maintaining total EM colonization and species richness following defoliation. In addition, EM species composition changed significantly post-defoliation; the system dominant, an Inocybe species, was rare in defoliation plots, while Agaricoid and Suilloid species that were rare in controls were dominant in treatments. Furthermore, species of EM fungi associating with both lodgepole pine and Engelmann spruce were affected, which indicates that changing the photosynthetic capacity of one species can affect mycorrhizal associations of neighboring non-defoliated trees.     

Rapid identification of white-Engelmann spruce species by RAPD markers

Fragments of random amplified polymorphic DNA (RAPDs) were used as markers to distinguish Picea glauca (Moench) Voss (white spruce) and Picea engelmannii Parry (Engelmann spruce). These species and their putative hybrids are difficult to differentiate morphologically and are collectively known as interior spruce. Four oligodeoxynucleotide decamer primers showed species-specific amplification products between white spruce and Engelmann spruce. These fragments are highly conserved among seed lots and individual trees of each species from diverse geographic origins. The consistency and reproducibility of these species-specific amplification products were tested in more than two amplification reactions. Therefore, RAPD markers can provide genetic markers for easy and rapid identification of the specific genetic entry of these spruce species and their reported putative hybrids. According to the frequencies of the species-specific RAPD markers, it is possible to estimate the hybrid fraction, indicative of true introgression between the two species. These results are useful for quick identification of both species and their hybrid swarms at any stage in the sporophyte phase of the life cycle, for determining the occurrence and the magnitude of introgressive hybridization in an overlap zone between the two species, and for certification purposes in operational re-forestation and tree-improvement programs.     

Effects of abscisic acid and its acetylenic alcohol on dormancy, root development and transpiration in three conifer species

Abscisic acid (ABA) and a synthetic analog, the 2- cis acetylenic alcohol, were compared to evaluate their effectiveness in conditioning seedlings of Douglas-fir [ Pseudotsuga menziesii (Mirb.) Franco], Engelmann spruce ( Picea engelmannii Parry) and lodgepole pine ( Pinus contorta Dougl.). Following preconditioning with ABA and the analog, seedlings were water stressed with the osmoticum polyethylene glycol (PEG) 3350. The effects of the growth regulators on transpiration, net photosynthesis, their ratio, called water use efficiency, and cell water relations parameters were then compared in stressed and unstressed plants. The antitranspirant action of these compounds varied depending on the species, the growth regulator, and the level of stress. ABA promoted transpiration in unstressed seedlings for all 3 species seven days after application. The analog was superior to ABA as an antitranspirant in osmotically-stressed lodgepole pine and Engelmann spruce, but neither compound was effective in Douglas-fir. For Douglas-fir and Engelmann spruce, net photosynthesis remained consistently higher in ABA-treated plants during the two levels of osmotic stress, relative to control and analog treatments. Neither compound had any effect on root development or cell water relations. ABA, and to a lesser extent its analog, hastened terminal bud formation in seedlings exposed to short days and low temperatures.     

Bias and variance in model results associated with spatial scaling of measurements for parameterization in regional assessments

Models are central to global change analyses, but they are often parameterized using data that represent only a portion of heterogeneity in a region. This creates uncertainty in the results and constrains the reliability of model inferences. Our objective was to evaluate the uncertainty associated with differential scaling of parameterization data to model soil organic carbon stock changes as a function of US agricultural land use and management. Specifically, we compared analyses in which model parameters were derived from field experimental data that were scaled to the entire US vs. the same data scaled to climate regions within the country. We evaluated the effect of differential scaling on both bias and variance in model results. Model results had less variance by scaling data to the entire country because of a larger sample size for deriving individual parameter values, although there was a relatively large bias associated with this parameterization, estimated at 2.7 Tg C yr^?1. Even with the large bias, resulting confidence intervals from the two parameterizations had considerable overlap for the estimated national rate of SOC change (i.e. 77% overlap in those intervals). Consequently, the results were relatively similar when focusing on the uncertainty rather than solely on the mean estimate. In contrast, large biases created less overlap in confidence intervals for the change rates within individual climate regions, compared with the national estimates. For example, the overlap in resulting intervals from the two parameterizations was only 32% for the warm temperate moist region, with a corresponding bias of 3.1 Tg C yr^?1. These findings demonstrate that there is a greater risk of making erroneous inferences because of large biases if models are parameterized with broader scale information, such as an entire country, and then used to address impacts at a finer spatial scale, such as sub‐regions within a country. In addition, the study demonstrates a trade‐off between variance and bias in model results that depends on the scaling of data for model parameterization.     

Genetic evidence for species cohesion,substructure and hybrids in spruce

The origin and history of species are shaped by various evolutionary dynamics, including their persistence in the face of potential gene flow from related taxa. In this study, we use broad geographical and taxonomic sampling (2,219 individuals) to establish the distribution of species, hybrids and cryptic genetic variation within the conifer genus Picea (spruce) across western North America. We demonstrate that the six species of spruce in this region are distinguishable based on their genetic composition, and that the more closely related Engelmann spruce (P. engelmannii) and white spruce (P. glauca) have generated numerous and widespread hybrids. These hybrids occur in the central Rocky Mountains, well to the south of the well‐established region of admixture in Canada. Additionally, we provide evidence for subdivision within Engelmann spruce, manifested as a southern Rocky Mountains form, and a northern Rocky Mountain and Cascade mountains (western) form. In the intervening central Rocky Mountains region (forests in Wyoming and adjacent states) we found primarily individuals with admixed ancestry. Following their origin, these species of spruce have interacted repeatedly and in different geographical contexts. Multiple pairs of species have been shown to hybridize, yet the species persist and retain distinguishable compositions. At the same time, large geographical areas exist where hybrids are pervasive. Consequently, spruce provide a case study for the maintenance of species boundaries, particularly for how widespread hybridization need not lead to the collapse and loss of species.     

Classifying seedlots of Picea sitchensis and P. glauca in zones of introgression using restriction analysis of chloroplast DNA

Summary Chloroplast DNA (cpDNA) restriction analysis was used to classify five reforestation seedlots as to species. The material included two Sitka spruce (Picea sitchensis (Bong.) Carr.), one white spruce (P. glauca (Moench) Voss) from interior British Columbia, and two putative hybrid seedlots from the coast-interior introgression zone in British Columbia. The cpDNA patterns generated by Bam-HI and Bc1-I from individual trees of Sitka spruce, white spruce, western white spruce (P. glauca var. albertiana (S. Brown)), and Engelmann spruce (P. engelmanni (Parry)) were species-specific. They were used as reference patterns for comparisons. In addition, two controlled crosses between white and Sitka spruce were analyzed to demonstrate the paternal inheritance of cpDNA in spruces. The cpDNA restriction patterns for the five seedlots were obtained from composite samples of seedlings from each lot and compared to the typical cpDNA patterns of each species. Restriction patterns for the two Sitka spruce seedlots agreed with those from the Sitka spruce tree, while patterns for the white spruce seedlots from British Columbia agreed with those from the white spruce tree, lacking evidence of any Engelmann spruce component in the sample. On the other hand, one putative hybrid seedlot showed cpDNA patterns similar to white spruce while the other showed fragments unique to both Sitka and white spruce, indicating that this was a hybrid seedlot. The analysis of cpDNA restriction polymorphism has proven to be an effective tool for classifying seedlots in regions of introgression. To our knowledge, these results provide the first demonstration of the use of cpDNA analysis for solving practical forestry problems.     

Inter-species interactions and ecosystem effects of non-indigenous invasive and native tree-killing bark beetles

Frequent bark beetle outbreaks cause biome-scale impacts in boreal and temperate forests worldwide. Despite frequent interceptions at ports of entry, the most aggressive bark beetle species of Ips and Dendroctonus in North America and Eurasia have failed to establish outside their original home continents. Our experiments showed that Ips typographus can breed in six North American spruce species: Engelmann spruce, white spruce¸ Sitka spruce, Lutz spruce, black spruce and red spruce. This suggests that differences between the Eurasian historical host and North American spruce species are not an insurmountable barrier to establishment of this tree-killing species in North America. However, slightly diminished quality of offspring beetles emerged from the North American spruces could reduce the chance of establishment through an Allee effect. The probabilistic nature of invasion dynamics suggests that successful establishments can occur when the import practice allows frequent arrivals of non-indigenous bark beetles (increased propagule load). Model simulations of hypothetical interactions of Dendroctonus rufipennis and I. typographus indicated that inter-species facilitations could result in more frequent and severe outbreaks than those caused by I. typographus alone. The potential effects of such new dynamics on coniferous ecosystems may be dramatic and extensive, including major shifts in forest structure and species composition, increased carbon emissions and stream flow, direct and indirect impacts on wildlife and invertebrate communities, and loss of biodiversity.     

Inheritance of chloroplast and mitochondrial DNA in Picea and composition of hybrids from introgression zones

Summary The cloning of white spruce (Picea glauca) mitochondrial DNA homologous to the cytochrome oxidase II and ATPase genes of maize is described. These probes were used to define restriction fragment length polymorphisms which distinguish the white, Engelmann (P. engelmannii) and Sitka spruce (P. sitchensis) populations that occur in British Columbia. Analysis of progeny from crosses between the species revealed that mitochondrial DNA was maternally inherited in all cases (32 progeny from five independent crosses). The inheritance of chloroplast DNA was determined using a probe described previously; in this case, all progeny exhibited paternal inheritance (27 progeny from four crosses). Mitochondrial and chloroplast probes were used to test trees from zones of introgression between coastal (Sitka) and interior spruces (white and Engelmann). In most cases mitochondria and chloroplasts within individuals were contributed by different species. The data shows that there is a significant Sitka spruce component in trees east of the coastal watershed in British Columbia.     

DEMOGRAPHIC ASPECTS OF COEXISTENCE IN ENGELMANN SPRUCE AND SUBALPINE FIR

The mechanisms for the maintenance of coexistence of Engelmann spruce and subalpine fir in subalpine forests of the Colorado Front Range were examined by comparing age, size, and spatial distributions of spruce and fir in two adjacent, previously logged sites of differing moisture availability. Adult tree ages were calculated from stem cores, while seedling ages were calculated from a multiple regression equation based on diameter, height, and number of branch whorls. Tree size was measured by height and diameter; spatial distributions were described by Morisita's index of dispersion. Cumulative age and size distributions were significantly different in the two species, with greater longevity and a larger overall size in spruce than fir. Both species showed a significant linear relationship between size and age, while fir showed a faster height growth rate than spruce. The linear relationship beween age and size was much closer in seedlings than in adults. Seedling spatial distribution was highly clumped in both species, but mature trees showed little or no clumping. Because both species are mainly wind dispersed, the greater clumping in spruce than in fir seedlings suggests that spruce have more specific establishment requirements than fir. Colonization patterns indicated that spruce seedlings were primarily found in forest gaps or associated with fir canopy trees, while fir seedlings were more commonly found in the forest, associated with either spruce or fir canopy trees. Tree density, growth rates, and mortality rates were higher in the wet site, with spruce showing the largest between site differences. These data suggest a new hypothesis for coexistence stating that Engelmann spruce and subalpine fir are maintained as codominants because the greater longevity and size of spruce is balanced by the faster height growth and more flexible seedling establishment requirements of fir.     

Species,Climate and Landscape Physiography Drive Variable Growth Trends in Subalpine Forests

Forests around the world are undergoing rapid changes due to changing climate and increasing physiological stress, but forest response to climate at the ecosystem scale can be highly variable due to the mixed responses of different trees across heterogeneous landscapes. To determine the response of ecosystems in the Rocky Mountains to climate stress, we investigated the response of subalpine fir (Abies lasiocarpa) and Engelmann spruce (Picea engelmannii), two widely distributed subalpine forest species of Rocky Mountains, to climate warming across a region characterized by gradients of elevation, aspect and soil type. We investigated the growth trend of individual trees through time, determined the climate variables most important for driving growth and quantified the interactions between climate and topography that influence long-term growth trends and potential ecological changes across the study region. Growth trends of these two species are similar through the first part of the century, but diverge during the last several decades. Since 1975, subalpine fir growth decreased through time, while Engelmann spruce growth increased. We find that aspect and warm summer temperatures are the most important factors determining growth in subalpine fir, and subalpine fir growth declines are greatest on east- and south-facing aspects. In contrast, Engelmann spruce growth is uniformly unresponsive to climate. In addition to highlighting the importance of species-level differences in growth response to climate, our results also identify interactions between climate and local physiography as controls on long-term growth trends and suggest that the local landscape physiography can mediate climate-related stress in forested ecosystems. This work advances our understanding of how forest stress is mitigated by landscape factors at the ecosystem scale, and how interactions of species, landscape and climate will control future ecosystem composition and forest growth dynamics.     

Searching for thresholds in climate–radial growth relationships of Engelmann spruce and subalpine fir,Jasper National Park,Alberta, Canada

The relationship between monthly climate predictors and radial growth of Engelmann spruce (Picea engelmanni Parry) and subalpine fir (Abies lasiocarpa (Hook.) Nutt) were explored using both a standard dendroclimatological approach and a multiple adaptive regressions splines (MARS) framework. Consistent with previous research, the radial growth of fir and spruce was related to temperature variables over the time period of the instrumental record. We identify important temporal instability in the statistical relationships between climate variables and the radial growth of both subalpine fir and Engelmann spruce. Using a 30-year running window, only four of the climate variables related to the radial growth of either spruce or fir did not show a switch in the sign of the correlation. A multiple adaptive regressions spline method was then used to gain insight into thresholds that may relate to radial growth–climate instabilities. Using MARS, we were able to identify knots and non-monotonic relationships between radial growth and climate predictors that may be indicators of ecological thresholds. This combination of dendroclimatic methods provides valuable insight into the complex nonlinear responses that both subalpine fir and Engelmann spruce have been growing under in the past centuries.     

Generalized variance component models for clustered categorical response variables

A generalized variance component model is proposed for the analysis of a categorical response variable with extra-multinomial variation. Categorical data obtained from research designs such as randomized multicenter clinical trials or complex sample surveys with clustering frequently exhibit extra-variation resulting from intracluster correlation. General correlation patterns are accounted for by utilizing a mixed-effects modelling approach, estimating the cluster variance components through the method of moments and modelling functions of the observed proportions through the use of estimating equations. A flexible set of assumptions characterizing the underlying covariance structure for the proportions can be accommodated. The importance of accounting for extra-variation when performing hypothesis tests is highlighted with an application to data from a multi-investigator clinical trial.     

Development of microsatellite markers for white spruce (Picea glauca) and related species

We report the development of 13 primer pairs that allow the unambiguous amplification of 15 microsatellite (SSR) loci in white spruce (Picea glauca). Fourteen of these loci were polymorphic in trees sampled at three geographically separated regions of western Canada. Segregation analysis carried out on these loci confirmed a Mendelian inheritance pattern for all except two, which showed significant segregation distortion. All of these primer pairs amplified SSR loci in at least one of the other Picea species tested [black spruce (P. mariana), red spruce (P. rubens), Norway spruce (P. abies), Colorado spruce (P. pungens), sitka spruce (P. sitchensis) and Engelmann spruce (P. engelmannii)]. Given the important commercial and ecological roles of these species, this set of markers will be invaluable for their management, the improvement of commercially important traits, and the study of their ecology and genetics. Received: 18 August 2000 / Accepted: 28 September 2000