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Understanding the spatial patterns of fire occurrence and its response to climate change is vital to fire risk mitigation and vegetation management. Focusing on boreal forests in Northeast China, we used spatial point pattern analysis to model fire occurrence reported from 1965 to 2009. Our objectives were to quantitate the relative importance of biotic, abiotic, and human influences on patterns of fire occurrence and to map the spatial distribution of fire occurrence density (number of fires occurring over a given area and time period) under current and future climate conditions. Our results showed human-caused fires were strongly related to human activities (e.g. landscape accessibility), including proximity to settlements and roads. In contrast, fuel moisture and vegetation type were the most important controlling factors on the spatial pattern of lightning fires. Both current and future projected spatial distributions of the overall (human-+ lightning-caused) fire occurrence density were strongly clustered along linear components of human infrastructure. Our results demonstrated that the predicted change in overall fire occurrence density is positively related to the degree of temperature and precipitation change, although the spatial pattern of change is expected to vary spatially according to proximity to human ignition sources, and in a manner inconsistent with predicted climate change. Compared to the current overall fire occurrence density (median value: 0.36 fires per 1000 km 2 per year), the overall fire occurrence density is projected to increase by 30% under the CGCM3 B1 scenario and by 230% under HadCM3 A2 scenario in 2081-2100, respectively. Our results suggest that climate change effects may not outweigh the effects of human influence on overall fire occurrence over the next century in this cultural landscape. Accurate forecasts of future fire-climate relationships should account for anthropogenic influences on fire ignition density, such as roads and proximity to settlements.

The lack of management experience at the landscape scale and the limited feasibility of experiments at this scale have increased the use of scenario modeling to analyze the effects of different management actions on focal species. However, current modeling approaches are poorly suited for the analysis of viability in dynamic landscapes. Demographic (e.g., metapopulation) models of species living in these landscapes do not incorporate the variability in spatial patterns of early successional habitats, and landscape models have not been linked to population viability models. We link a landscape model to a metapopulation model and demonstrate the use of this model by analyzing the effect of forest management options on the viability of the Sharp-tailed Grouse ( Tympanuchus phasianellus) in the Pine Barrens region of northwestern Wisconsin (U.S.A.). This approach allows viability analysis based on landscape dynamics brought about by processes such as succession, disturbances, and silviculture. The landscape component of the model (LANDIS) predicts forest landscape dynamics in the form of a time series of raster maps. We combined these maps into a time series of patch structures, which formed the dynamic spatial structure of the metapopulation component (RAMAS). Our results showed that the viability of Sharp-tailed Grouse was sensitive to landscape dynamics and demographic variables such as fecundity and mortality. Ignoring the landscape dynamics gave overly optimistic results, and results based only on landscape dynamics (ignoring demography) lead to a different ranking of the management options than the ranking based on the more realistic model incorporating both landscape and demographic dynamics. Thus, models of species in dynamic landscapes must consider habitat and population dynamics simultaneously.Integrando Métodos Basados en Modelos de Paisaje y Metapoblaciones: Viabilidad de Tympanuchus phasianellus en un Paisaje Dinámico Resumen: La falta de experiencia de gestión a nivel de paisaje y la limitada factibilidad de experimentos a esta escala han incrementado el uso de modelos de escenarios para analizar los efectos de diferentes acciones de gestión sobre especies locales. Sin embargo, los métodos de modelaje actuales son poco adecuados para el análisis de viabilidad en paisajes dinámicos. Modelos demográficos (por ejemplo, metapoblaciones) de especies que habitan estos paisajes no incorporan la variabilidad de los patrones espaciales de hábitats en sucesión temprana, y los modelos de paisaje no se han vinculado con modelos de viabilidad poblacional. Vinculamos un modelo de paisaje con uno metapoblacional y demostramos el uso de este modelo analizando el efecto de opciones de gestión forestal sobre la viabilidad de Tympanuchus phasianellus en la región de Pine Barrens al noreste de Wisconsin (E.U.A.). Este método permite el análisis de viabilidad con base en la dinámica del paisaje Akçakaya et al. Integrating Landscape and Metapopulation Models 527debido a procesos como sucesión, perturbación y silvicultura. ...

Aim Predictions of ecosystem responses to climate warming are often made using gap models, which are among the most effective tools for assessing the effects of climate change on forest composition and structure. Gap models do not generally account for broad-scale effects such as the spatial configuration of the simulated forest ecosystems, disturbance, and seed dispersal, which extend beyond the simulation plots and are important under changing climates. In this study we incorporate the broad-scale spatial effects (spatial configurations of the simulated forest ecosystems, seed dispersal and fire disturbance) in simulating forest responses to climate warming. We chose the Changbai Natural Reserve in China as our study area. Our aim is to reveal the spatial effects in simulating forest responses to climate warming and make new predictions by incorporating these effects in the Changbai Natural Reserve.Location Changbai Natural Reserve, north-eastern China.Method We used a coupled modelling approach that links a gap model with a spatially explicit landscape model. In our approach, the responses (establishment) of individual species to climate warming are simulated using a gap model (linkages) that has been utilized previously for making predictions in this region; and the spatial effects are simulated using a landscape model (LANDIS) that incorporates spatial configurations of the simulated forest ecosystems, seed dispersal and fire disturbance. We used the recent predictions of the Canadian Global Coupled Model (CGCM2) for the Changbai Mountain area (4.6°C average annual temperature increase and little precipitation change). For the area encompassed by the simulation, we examined four major ecosystems distributed continuously from low to high elevations along the northern slope: hardwood forest, mixed Korean pine hardwood forest, spruce-fir forest, and sub-alpine forest. ResultsThe dominant effects of climate warming were evident on forest ecosystems in the low and high elevation areas, but not in the mid-elevation areas. This suggests that the forest ecosystems near the southern and northern ranges of their distributions will have the strongest response to climate warming. In the mid-elevation areas, environmental controls exerted the dominant influence on the dynamics of these forests (e.g. spruce-fir) and their resilience to climate warming was suggested by the fact that the fluctuations of species trajectories for these forests under the warming scenario paralleled those under the current climate scenario.Main conclusions With the spatial effects incorporated, the disappearance of tree species in this region due to the climate warming would not be expected within the 300-year period covered by the simulation. Neither Korean pine nor spruce-fir was completely replaced by broadleaf species during the simulation period. Even for the sub-alpine forest, mountain birch did not become extinct