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This paper proposes a method of controlled trend surface to simultaneously account for large-scale spatial trends and non-spatial local effects. With this method, a geospatial model of forest dynamics was developed for the Alaska boreal forest from 446 constantly monitored permanent sample plots. The geospatial component of this model represented large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of validation plots which represented temporal and spatial extensions of the current sample coverage. The results suggest that the controlled trend surface model was generally more accurate than both the non-spatial and conventional trend surface models. With this model, we mapped the forest dynamics of the entire Alaska boreal region by aggregating predicted stand states across the region. It was predicted that under current conditions of climate and natural disturbances, most of the Alaska boreal forest region may undergo a major shift from deciduous-dominant to conifer-dominant, with an average increase of 0.33m2 hayear−1 in basal area over the Twenty-First Century. [Copyright &y& Elsevier]

Across forest ecosystems worldwide, alternative silvicultural practices such as partial or “structural retention” harvesting are gaining increasing use as means to balance economic and ecological management goals. Recent studies have documented highly elevated rates of residual-tree mortality and growth, both of which are likely to influence post-harvest stand development. Explicit consideration of residual-tree responses to partial harvest is therefore required to make accurate growth and yield predictions. In this paper we incorporate empirically based, spatially explicit tree growth and mortality predictors into a forest simulation model in order to quantify stand dynamics following a range of simulated partial harvests. We consider lowland black spruce boreal forests and use a common strip-cutting technique, Harvest with Advance Regeneration Protection, as a reference against which to compare alternative scenarios. Predicted stand development proceeded most rapidly in scenarios with reduced skidding impacts and relatively high levels of retention, since these treatments were associated with lower residual-tree mortality rates and larger growing stocks respectively. Stand development was also influenced on a proportional basis by residual-tree growth rates, which increased with declining neighbourhood competition. Across a range of harvest scenarios with equivalent retention levels (20%), differences in residual-tree responses among treatments led to a 35-year range in projected basal area return intervals (70–105 years). Our results demonstrate that short-term responses of residual trees affect stand development rates over long (>100-year) time scales, and show that post-harvest stand recovery rates are influenced not only by the retention level but also by the specific parameters of partial harvest prescriptions, including the layout of skid trails and the spatial arrangement of residual trees. Results from this study provide essential information for evaluating partial harvests in the black spruce boreal forest and supply modelling tools for assessing alternative silvicultural treatments in other forest ecosystems. [Copyright &y& Elsevier]

Fire regimes result from reciprocal interactions between vegetation and fire that may be further affected by other disturbances, including climate, landform, and terrain. In this paper, we describe fire and fuel extensions for the forest landscape simulation model, LANDIS-II, that allow dynamic interactions among fire, vegetation, climate, and landscape structure, and incorporate realistic fire characteristics (shapes, distributions, and effects) that can vary within and between fire events. We demonstrate the capabilities of the new extensions using two case study examples with very different ecosystem characteristics: a boreal forest system from central Labrador, Canada, and a mixed conifer system from the Sierra Nevada Mountains (California, USA). In Labrador, comparison between the more complex dynamic fire extension and a classic fire simulator based on a simple fire size distribution showed little difference in terms of mean fire rotation and potential severity, but cumulative burn patterns created by the dynamic fire extension were more heterogeneous due to feedback between fuel types and fire behavior. Simulations in the Sierra Nevada indicated that burn patterns were responsive to topographic features, fuel types, and an extreme weather scenario, although the magnitude of responses depended on elevation. In both study areas, simulated fire size and resulting fire rotation intervals were moderately sensitive to parameters controlling the curvilinear response between fire spread and weather, as well as to the assumptions underlying the correlation between weather conditions and fire duration. Potential fire severity was more variable within the Sierra Nevada landscape and also was more sensitive to the correlation between weather conditions and fire duration. The fire modeling approach described here should be applicable to questions related to climate change and disturbance interactions, particularly within locations characterized by steep topography, where temporally or spatially dynamic vegetation significantly influences spread rates, where fire severity is variable, and where multiple disturbance types of varying severities are common. [Copyright &y& Elsevier]

Statistical models relating habitat characteristics to species occurrences are increasingly used to evaluate the consequences of forest management activities and conservation plans over large spatial and temporal scales. In practice, such models do not always generalize to other locations, hence, they should be validated using independent data. In this paper, we assess the predictive ability of 16 songbird habitat models developed in the Calling Lake region of the boreal mixedwood forest of Alberta using both internal and external validation approaches. Internal validation relied on the same dataset used to develop the models while external validation utilised independent data collected within four validation landscapes in the same ecological region. Two aspects of predictive accuracy were evaluated: the agreement between observations and predicted values (calibration) and the models’ ability to classify locations into those in which species are present or absent (discrimination). Calibration was assessed using the Hosmer–Lemeshow (H–L) statistic and plots showing predicted versus observed probabilities of occurrence. Discrimination was assessed using receiver operating characteristic (ROC) curves and the associated area under the ROC curve. With internal validation, the calibration plots were reasonable for all species, however the H–L statistic indicated a good fit for only eight species. Model discrimination between occupied and unoccupied sites, on the other hand, was reasonable for 14 of 16 models. With external validation, both the calibration plots and the H–L statistic identified only three species with a reasonable fit. The remaining models generally over- or under-predicted probability of occurrence. External model discrimination was reasonable for 10 of 16 species. When we re-estimated the models using all available data, the calibration plots were again reasonable for all species, with the H–L statistic indicating good fit for 12 species. Similarly, model discrimination was reasonable for 14 of 16 species. Several factors may help to explain why model performance using external data was generally poorer and more variable than when using internal data. These include differences in landscape structure and disturbance history as well as differences in the frequency of occurrence of individual species. Overall, our analyses identified several species whose habitat models degraded considerably, especially as measured by calibration. By re-estimating the models, we increased the range of variation in our covariates which likely led to an improvement in model calibration. We discuss the importance of ongoing evaluation and refinement of habitat models that will be used in conservation planning or to evaluate management scenarios at large spatial and temporal scales. [Copyright &y& Elsevier]

Abstract: Carbon budget of Siberian boreal forests is one of the largest uncertainties in the global carbon cycle under changing environment and then climate prediction. A coupled carbon cycle and fire regime model, which is applicable to simulate carbon budget of a fire-prone boreal forest in eastern Siberia, was developed in this paper. The carbon model consists of 10 pools and represents carbon dynamics including biomass burning, on the basis of an ecophysiological carbon cycle model (Sim-CYCLE). The fire model simulates fire behavior (ignition, expansion, and extinction) at a landscape scale with a spatially explicit cellular automaton, in a stochastic manner. Fire spread and burning intensity are parameterized as functions of temperature, moisture, and fuel availability, and ground fire and crown fire are dealt with separately. Interactions between the carbon cycle and fire behavior models are included, such that the carbon model simulates fuel dynamics and post-fire vegetation growth and the fire model simulates biomass burning (carbon dioxide emission, detritus production, and charcoal formation). The model was calibrated at a deciduous needle-leaved (larch) forest near Yakutsk, Russia (62°N, 130°E), in which Japanese researchers conducted surveys of carbon dynamics. The long-term simulation (1200 years) indicated that the mean fire interval of the larch forest was as short as 64 years, and most fires (94% of burnt area) occurred as ground fires. Although crown fires were less frequent (6% of burnt area), they exerted more severe impacts on carbon storage than ground fires. On average, the biomass burning released about 12% of carbon fixed by plant photosynthesis directly and resulted in acceleration of carbon cycling of the boreal forest. Young post-fire forests exhibited higher photosynthetic activity and compensated for the loss of old stands. Sensitivity of the model simulation to variation in parameter values and environmental conditions was examined. Finally, the simulation analysis confirmed that the fire regime is an important ecosystem attribute, and that a coupled carbon and fire model is useful to investigate the carbon budget of boreal forest in eastern Siberia. [Copyright &y& Elsevier]