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Tree mortality plays a fundamental role in the dynamics of forest ecosystems, yet it is one of the most difficult phenomena to accurately predict. Various modeling strategies have been developed to improve individual tree mortality predictions. One less explored strategy is the use of a multistage modeling approach. Potential improvements from this approach have remained largely unknown. In this study, we developed a novel multistage approach and compared its performance in individual tree mortality predictions with a more conventional approach using an identical individual tree mortality model formulation. Extensive permanent plot data (n = 9442) covering the Acadian Region of North America and over multiple decades (1965-2014) were used in this study. Our results indicated that the model behavior with the multistage approach better depicted the observed mortality and showed a notable improvement over the conventional approach. The difference between the observed and predicted numbers of dead trees using the multistage approach was much smaller when compared with the conventional approach. In addition, tree survival probabilities predicted by the multistage approach generally were not significantly different from the observations, whereas the conventional approach consistently underestimated mortality across species and overestimated tree survival probabilities over the large range of DBH in the data. The new multistage approach also predictions of zero mortality in individual plots, a result not possible in conventional models. Finally, the new approach was more tolerant of modeling errors because it based estimates on ranked tree mortality rather than error-prone predicted values. Overall, this new multistage approach deserves to be considered and tested in future studies. [ABSTRACT FROM AUTHOR]

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Thinning is expected to improve both individual tree- and stand-level growth efficiency since more environmental resources (growing space, light, water, and nutrients) become available to fewer trees. However, thinning can also promote asymmetric competition among residual trees, and potentially increase mortality and growth stagnation by creating an immediate and often dramatic change in stand micro-environments. To strengthen our understanding of stand-level responses to thinning, we used long-term and replicated experiments for the three most commercially important softwood forest types in the North America, including: shade-intolerant loblolly pine ( Pinus taeda L.), moderately shade-tolerant Douglas-fir ( Pseudotsuga menziesii Mirbel), and shade-tolerant red spruce ( Picea rubens Sarg.) and balsam fir ( Abies balsamea L.). The primary objectives of this study were to quantify the stand-level and dominant tree (100 largest trees ha −1 ) response to various thinning treatments in terms of relative ( RVG ) and cumulative volume growth ( CVG ), while evaluating the effects of stand conditions, timing/intensity of thinning, and key stand-level biotic factors. Our results showed relatively limited differences between the stand-level and dominant-tree responses. Thinning generally increased the RVG of all three forest types, but the effect was dependent on time since treatment for spruce-fir. When compared to unthinned stands, thinning increased the overall RVG , but the pattern of change over time since thinning was negative for both loblolly pine and Douglas-fir. CVG was generally higher in unthinned than thinned stands across the three forest types. Thinning intensity had a positive effect on the RVG of Douglas-fir and loblolly pine, but negative on RVG of spruce-fir forest type. Relative age (based on age of maximum periodic annual increment) and stand density at time of thinning had negative effects on the RVG of dominant trees for all species examined, except spruce-fir. Overall, our results highlight a range of responses to thinning among three distinct softwood forest types, and revealed that thinning does not always improve the growth efficiency of dominant trees, and that the responses are governed largely by a variety of stand characteristics at the time of thinning. [ABSTRACT FROM AUTHOR]

Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner’s management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of ‘harvest readiness’ and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Equations that relate individual tree diameter at breast height (d.b.h.) and total height (HT) are important because HT is not widely measured and is often needed to estimate stem volume or predict HT growth. The primary goal of the study was to construct a regional HT to d.b.h. equation (H-D) for 15 tree species of the Acadian Region. Specific objectives were to (1) evaluate performance of the Forest Vegetation Simulator Northeast Variant (FVS-NE) equations, (2) explore suitable model forms and compare the influence of various tree- and stand-level variables on HT prediction and (3) develop species-specific equations that are unbiased across a broad geographic region. Data were available from an extensive database covering Maine, three provinces of the Canadian Maritimes and southern Québec. The study showed that the widely used FVS-NE model had significant prediction biases for all species in the region. The best model form among those evaluated was the von Bertalanffy–Richards (vB-R; commonly referred to as the Chapman–Richards), with added covariates that included crown competition factor, basal area in trees larger than subject tree and a climate-derived site index. [ABSTRACT FROM PUBLISHER]

Taper models to predict upper stem diameters, as well as total tree volume, are presented for 11 major conifer species in the Acadian Forest Region of North America. The Kozak (2004. My last words on taper equations. For. Chron. 80:507-514) Model 02 taper equation was used as the base model form. A nonlinear mixed-effects modeling approach was used to account for autocorrelation present among multiple stem analysis observations collected from the same tree. Results show that fitted taper equations can accurately predict both stem form and volume across a range of conditions. The taper models generally had slightly lower bias and root mean square error than the commonly used regional Honer refitted volume equations (1965. A new total cubic foot volume function. For. Chron. 41:476-493). The mean absolute bias was reduced up to 28% for certain species using the fitted taper equations compared with the refitted Honer (1965) equations, although the refitted Honer's models are also quite accurate where total stemwood volumes are needed. Independent validation data sets were used to further confirm reliability and accuracy of fitted taper models in predicting tree volume. These data sets indicated that the equations performed well, in general, but were slightly biased in certain thinned stands and in some New Brunswick ecoregions. Additional data are needed to confirm this and potentially improve model behavior. Overall, the models will be useful for predicting both stem form and merchantable and total volume. [ABSTRACT FROM AUTHOR]

Copyright of Forestry Chronicle is the property of Canadian Institute of Forestry and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Forest tree ingrowth is a highly variable and largely stochastic process. Consequently, predicting occurrence, frequency, and composition of ingrowth is a challenging task but of great importance in long-term forest growth and yield model projections. However, ingrowth data often require different statistical techniques other than traditional Gaussian regression, because these data are often bounded, skewed, and non-normal and commonly contain a large fraction of zeros. This study presents a set of regression models based on discrete Poisson and negative binomial probability distributions for ingrowth data collected from permanent sample plots in the Acadian Forest Region of North America. Models considered here include regular Poisson, zero-inflated Poisson (ZIP), zero-altered Poisson (ZAP; hurdle Poisson), regular negative binomial (NB), zero-inflated negative binomial (ZINB), and zero-altered negative binomial (ZANB; hurdle NB). Plot-level random effects were incorporated into each of these models. The ZINB model with random effects was found to provide the best fit statistics for modeling annualized occurrence and frequency of ingrowth. The key explanatory variables were stand basal area per hectare, percentage of hardwood basal area, number of trees per hectare, a measure of site quality, and the minimum measured diameter at breast height of each plot. A similar model was developed to predict species composition. All models showed logical behavior despite the high variability observed in the original data. [ABSTRACT FROM AUTHOR]