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Traditionally, forest management has focused on forestry-related practices whereas other industries have been managed separately. Forest management requires the integration of all natural resource development activities, along with other anthropogenic and natural forest disturbances (e.g., climate change, pollution, wildfire, pest disturbance) to understand how human activities can change forested ecosystems. The term cumulative effects has been used to describe these attempts to integrate all disturbances to develop an understanding of past, current, and future impacts on environmental, social, and economic components of the system. In this review, we focus on the science required to understand the past, current, and future impacts of the cumulative effects of anthropogenic and natural disturbances on forested ecosystems or their components. We have primarily focused on the terrestrial system with an emphasis on northern forests in Canada. Our paper is not intended to be a comprehensive review of all cumulative effects science but a synthesis of the challenges and approaches currently being used. Central repositories were identified as an approach to deal with issues of availability of remotely sensed data on anthropogenic and natural disturbances. Data integration projects, open data, and well-designed large-scale data collection efforts are needed to provide sufficient data on environmental responses to cumulative effects. As well, large-scale integrated, modularized ecosystem models are needed to bring stressor and environmental response data together to explore responses to, and interactions between, multiple stressors to project these effects into the future and to identify future data collection needs. [ABSTRACT FROM AUTHOR]

Much of Canada's terrestrial biodiversity is supported by boreal forests. Natural resource development in boreal forests poses risks to this biodiversity. This paper reviews the scientific literature to assess the effects of natural resource development on terrestrial biodiversity in Canadian boreal forests. We address four questions: (1) To what extent have Canadian boreal forests changed due to natural resource development? (2) How has biodiversity responded to these changes? (3) Will the biodiversity of second-growth forests converge with that of primary boreal forests? (4) Are we losing species from boreal forests? We focus on trees, understory plants, insects, fungi, selected mammals, and songbirds because these groups have been most studied. We review more than 600 studies and found that changes in community composition are prevalent in response to large-scale conversion of forest types, changes in stand structures and age distributions, and altered landscape structure resulting from forest management and habitat loss associated with other developments such as oil and gas, hydroelectric, and mining. The southern boreal forest has been more highly impacted than the north due to more extensive forest management and the cumulative effects of multiple forms of development. There is abundant evidence that most species are not in danger of being extirpated from the boreal forest due to these anthropogenic changes. A few species, including woodland caribou ( Rangifer tarandus) and grizzly bear ( Ursus arctos), have, however, undergone long-term range contractions. Significant gaps in our ability to assess the effects of natural resource development on biodiversity in the boreal zone are the lack of long-term spatial and population data to monitor the impact of forest changes on ecosystems and species. [ABSTRACT FROM AUTHOR]

Spatial tree data are required for the development of spatially explicit models and for the estimation of summary statistics such as Ripley’s K function. Such data are rare and expensive to gather. This paper presents an efficient method of synthesizing spatial tree point patterns from nearest neighbour summary statistics (NNSS) sampled in small circular subwindows, which uses a stochastic optimization technique based on simulated annealing and conditional simulation. This nonparametric method was tested by comparing tree point patterns, reconstructed from sample data, with the original woodland patterns of three structurally different tree populations. Analysis and validation show that complex spatial woodland structures, including long-range tree interactions, can be successfully reconstructed from NNSS despite the limited range of the subwindows and statistics. The influence of the NNSS varies depending on the woodland under study. In some cases, the sampling results can be improved by reconstruction. Furthermore, it is clearly shown that it is possible to estimate second-order characteristics such as Ripley’s K function from small circular subwindows through the reconstruction technique. The results offer new opportunities for adding value to woodland surveys by making raw data available for further work such as growth projections, visualization, and modelling. [ABSTRACT FROM AUTHOR]

A common approach for incorporating opening constraints into harvest scheduling is through the area-restricted model. This model is used to select which stands to include in each opening while simultaneously determining an optimal harvest schedule over multiple time periods. In this paper we use optimal benchmarks from a range of harvest scheduling problem instances to test a metaheuristic algorithm, simulated annealing, that is commonly used to solve these problems. Performance of the simulated annealing algorithm was assessed over a range of problem attributes such as the number of forest polygons, age-class distribution, and opening size. In total, 29 problem instances were used, ranging in size from 1269 to 36 270 binary decision variables. Overall, the mean objective function values found with simulated annealing ranged from approximately 87% to 99% of the optima after 30 min of computing time, and a moderate downward trend of the relationship between problem size and solution quality was observed. [ABSTRACT FROM AUTHOR]

This paper considers the question of whether sustainable forest management (SFM) should continue to incorporate sustained yield (SY) requirements, as it currently does in many jurisdictions. We evaluate the extent to which SY and SFM are consistent with notions of weak and (or) strong sustainability. Strong sustainability implies placing constraints on the reduction of stocks of natural capital to prevent irreversibility and (or) protect flows of services that have public good characteristics. In contrast, weak sustainability may allow market forces to draw down stocks of natural capital so long as levels of total capital (including human-made and natural capital) are maintained. We argue that with SY policies, we have probably chosen to attach strong sustainability policies to the only forest resource that does not need such protection (i.e., timber), while we have excluded other resources that could well need such protection (e.g., biodiversity) for pursuing SFM. Thus, the concept of allowable annual cuts could be dropped from SFM to be replaced by safe minimum standards on components of forest capital that are subject to irreversibility and (or) that have public good features. In other words, if we truly wish to pursue SFM, it may be necessary to leave SY behind. [ABSTRACT FROM AUTHOR]

Forest inventory data are often summarized in tabular format where rows and columns represent levels of categorical variables. It is generally desirable to constrain tables based on different categories to sum to common totals. It may also be desirable to develop a system that incorporates stratification. Weights can be assigned to inventory plots to achieve these goals with weighted estimators. The justification for weighting is presented here along with approaches for defining reasonable weights. A weighted estimator is developed to constrain tables derived from mapped plot data to add to common totals. [ABSTRACT FROM AUTHOR]