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Transdisciplinary landscape ecology research (in which all stakeholders co-develop landscape plans) requires innovations to support communication and consensus building. From the early stage of the discipline's development, landscape ecologists have been collaborating with researchers from neighboring fields (Kienast et al. [9]), embracing frameworks and approaches of interdisciplinarity. Recent trends indicate a convergence towards new research directions within Landscape Ecology that emphasizes sustainability science and research on social-ecological systems (Li et al. [10]; Wu [19]). Concluding remarks Landscape ecology has profoundly transformed landscape research by its inter- and transdisciplinary nature. [Extracted from the article]

Context: Exploratory modeling in forestry uses a variety of approaches to simulate forest management. One important assumption that every approach makes is about the deep uncertainty—the lack of the knowledge required for making an informed decision—that future forest management will face. This assumption can strongly influence simulation results and their interpretation but is rarely studied. Objectives: Our objective was to explore how differences in modeling approaches influence the deep uncertainty faced in simulated forest management. Methods: We used SOSIEL Harvest, a new agent-based extension to a landscape-change model, LANDIS-II, to simulate three approaches to modeling forest management. For each, we used the same forest and management data from Michigan, US, which isolated the differences among approaches as the only variable factor. We then used a new method, also introduced here, to measure and compare the deep uncertainty faced during simulated management. Finally, we used a typology of sources of uncertainty to categorize the sources responsible for this deep uncertainty. Results: The simulated forest management in the three modeling approaches faced substantially different degrees of deep uncertainty, which translated into considerable differences in simulation results. There was an overall negative relationship between deep uncertainty and the ability of the management to respond to forest change and adapt decisions accordingly. Conclusions: While inherent deep uncertainty faced in simulated forest management can be substantial, it is overestimated by exploratory models that underestimate management's ability to respond to forest change. Reducing such model-related uncertainty will allow for more realistic results from exploratory studies of forest management. [ABSTRACT FROM AUTHOR]

Emerald ash borer (EAB; Agrilus planipennis Farimaire) has been found in 35 US states and five Canadian provinces. This invasive beetle is causing widespread mortality to ash trees (Fraxinus spp.), which are an important timber product and ornamental tree, as well as a cultural resource for some Tribes. The damage will likely continue despite efforts to impede its spread. Further, widespread and rapid ash mortality as a result of EAB is expected to alter forest composition and structure, especially when coupled with the regional effects of climate change in post-ash forests. Thus, we forecasted the long-term effects of EAB-induced ash mortality and preemptive ash harvest (a forest management mitigation strategy) on forested land across a 2-million-hectare region in northern Wisconsin. We used a spatially explicit and spatially interactive forest simulation model, LANDIS-II, to estimate future species dominance and biodiversity assuming continued widespread ash mortality. We ran forest disturbance and succession simulations under historic climate conditions and three downscaled CMIP5 climate change projections representing the upper bound of expected changes in precipitation and temperature. Our results suggest that although ash loss from EAB or harvest resulted in altered biodiversity patterns in some stands, climate change will be the major driver of changes in biodiversity by the end of century, causing increases in the dominance of southern species and homogenization of species composition across the landscape. [ABSTRACT FROM AUTHOR]

Context: Resilience is a concept central to the field of ecology, but our understanding of resilience is not sufficient to predict when and where large changes in species composition might occur following disturbances, particularly under climate change. Objectives: Our objective was to estimate how wind disturbance shapes landscape-level patterns of engineering resilience, defined as the recovery of total biomass and species composition after a windstorm, under climate change in central Wisconsin. Methods: We used a spatially-explicit, forest simulation model (LANDIS-II) to simulate how windstorms and climate change affect forest succession and used boosted regression tree analysis to isolate the important drivers of resilience. Results: At mid-century, biomass fully recovered to current conditions, but neither biomass nor species composition completely recovered at the end of the century. As expected, resilience was lower in the south, but by the end of the century, resilience was low throughout the landscape. Disturbance and species' characteristics (e.g., the amount of area disturbed and the number of species) explained half of the variation in resilience, while temperature and soil moisture comprised only 17% collectively. Conclusions: Our results illustrate substantial spatial patterns of resilience at landscape scales, while documenting the potential for overall declines in resilience through time. Species diversity and windstorm size were far more important than temperature and soil moisture in driving long term trends in resilience. Finally, our research highlights the utility of using machine learning (e.g., boosted regression trees) to discern the underlying mechanisms of landscape-scale processes when using complex spatially-interactive and non-deterministic simulation models. [ABSTRACT FROM AUTHOR]

Climate-driven increases in wildfires, drought conditions, and insect outbreaks are critical threats to forest carbon stores. In particular, bark beetles are important disturbance agents although their long-term interactions with future climate change are poorly understood. Droughts and the associated moisture deficit contribute to the onset of bark beetle outbreaks although outbreak extent and severity is dependent upon the density of host trees, wildfire, and forest management. Our objective was to estimate the effects of climate change and bark beetle outbreaks on ecosystem carbon dynamics over the next century in a western US forest. Specifically, we hypothesized that (a) bark beetle outbreaks under climate change would reduce net ecosystem carbon balance (NECB) and increase uncertainty and (b) these effects could be ameliorated by fuels management. We also examined the specific tree species dynamics—competition and release—that determined NECB response to bark beetle outbreaks. Our study area was the Lake Tahoe Basin (LTB), CA and NV, USA, an area of diverse forest types encompassing steep elevation and climatic gradients and representative of mixed-conifer forests throughout the western United States. We simulated climate change, bark beetles, wildfire, and fuels management using a landscape-scale stochastic model of disturbance and succession. We simulated the period 2010-2100 using downscaled climate projections. Recurring droughts generated conditions conducive to large-scale outbreaks; the resulting large and sustained outbreaks significantly increased the probability of LTB forests becoming C sources over decadal time scales, with slower-than-anticipated landscape-scale recovery. Tree species composition was substantially altered with a reduction in functional redundancy and productivity. Results indicate heightened uncertainty due to the synergistic influences of climate change and interacting disturbances. Our results further indicate that current fuel management practices will not be effective at reducing landscape-scale outbreak mortality. Our results provide critical insights into the interaction of drivers (bark beetles, wildfire, fuel management) that increase the risk of C loss and shifting community composition if bark beetle outbreaks become more frequent. [ABSTRACT FROM AUTHOR]

Climate change will alter forest ecosystems and their provisioning of services. Forests in the Carpathian Mountains store high amounts of carbon and provide livelihoods to local people; however, no study has yet assessed their future long-term dynamics under climate change. Therefore, we selected a representative area of 1340 km2 to investigate the effects of changing climate and disturbance regimes on (i) the spatial dynamics of the dominant tree species and forest types and (ii) the trajectories of the associated aboveground live carbon (ALC). We simulated 500 years of change under four Representative Concentration Pathway (RCP) scenarios, incorporating wind and bark beetle disturbances using the LANDIS-II forest change model. Our simulations revealed a lagged adaptation of the forest landscape to climate change. While Picea abies dominance declined in all scenarios, Carpinus betulus expanded at low elevations and Acer pseudoplatanus at mid-elevations. We also found a slow but continuous expansion of Quercus petraea and Q. robur at low elevations and of Fagus sylvatica at mid and high elevations. This change in species composition was accompanied by a significant reduction of ALC: on average over the simulation period, unmitigated climate change reduced ALC between − 2.1% (RCP2.6) and − 14.0% (RCP8.5), while disturbances caused an additional reduction of ALC between − 4.5% (RCP2.6) and − 6.6% (RCP8.5). Therefore, foresighted management strategies are needed to facilitate vegetation adaptation to climate change, with the goal of stabilizing carbon storage and maintaining economic value of future Carpathian forests. [ABSTRACT FROM AUTHOR]

Spatially explicit dynamic forest landscape models have been important tools to study large-scale forest landscape response under global climatic change. However, the quantification of relative importance of different transition pathways among different forest types to forest landscape dynamics stands as a significant challenge. In this study, we propose a novel approach of elasticity and loop analyses to identify important transition pathways contributing to forest landscape dynamics. The elasticity analysis calculates the elasticity to measure the importance of one-directional transitions (transition from one forest type directly to another forest type); while the loop analysis is employed to measure the importance of different circular transition pathways (transition from one forest type through other forest types back to itself). We apply the proposed approach to a spatially explicit dynamic model, LANDIS-II, in a study of forest landscape response to climatic change in the Boundary Waters Canoe Area (BWCA) incorporating the uncertainties in climatic change predictions. Our results not only corroborate the findings of the previous studies on the most likely future forest compositions under simulated climatic variability, but also, through the novel application of the elasticity and loop analyses concepts, provide a quantitative assessment of the specific mechanisms leading to particular forest compositions, some of which might remain undetected with conventional model evaluation methods. By quantifying the importance of specific processes (transitions among forest types) to forest composition dynamics, the proposed approach can be a valuable tool for a more quantitative understanding of the relationship between processes and landscape composition/patterns. [ABSTRACT FROM AUTHOR]

Public forests are surrounded by land over which agency managers have no control, and whose owners expect the public forest to be a “good neighbor.” Fire risk abatement on multi-owner landscapes containing flammable but fire-dependent ecosystems epitomizes the complexities of managing public lands. We report a case study that applies a landscape disturbance and succession model (LANDIS) to evaluate the relative effectiveness of four alternative fire mitigation strategies on the Chequamegon-Nicolet National Forest (Wisconsin, USA), where fire-dependent pine and oak systems overlap with a rapidly developing wildland–urban interface (WUI). We incorporated timber management of the current forest plan and fire characteristics (ignition patterns, fire sizes, and fuel-specific fire spread rates) typical for the region under current fire suppression policies, using a combination of previously published fire analyses and interactive expert opinion from the national forest. Of the fire mitigation strategies evaluated, reduction of ignitions caused by debris-burning had the strongest influence on fire risk, followed by the strategic redistribution of risky forest types away from the high ignition rates of the WUI. Other treatments (fire breaks and reducing roadside ignitions) were less effective. Escaped fires, although rare, introduced significant uncertainty in the simulations and are expected to complicate fire management planning. Simulations also show that long-term maintenance of fire-dependent communities (that is, pine and oak) representing the greatest forest fire risk requires active management. Resolving conflict between the survival of fire-dependent communities that are regionally declining and continued rural development requires strategic planning that accounts for multi-owner activities. [ABSTRACT FROM AUTHOR]

Computer models are increasingly being used by forest ecologists and managers to simulate long-term forest landscape change. We review models of forest landscape change from an ecological rather than methodological perspective. We developed a classification based on the representation of three ecological criteria: spatial interactions, tree species community dynamics, and ecosystem processes. Spatial interactions are processes that spread across a landscape and depend upon spatial context and landscape con- figuration. Communities of tree species may change over time or can be defined a priori. Ecosystem process representation may range from no representation to a highly mechanistic, detailed representation. Our classification highlights the implicit assumptions of each model group and helps define the problem set for which each model group is most appropriate. We also provide a brief history of forest landscape simulation models, summarize the current trends in methods, and consider how forest landscape models may evolve and continue to contribute to forest ecology and management. Our classification and review can provide novice modelers with the ecological context for understanding or choosing an appropriate model for their specific hypotheses. In addition, our review clarifies the challenges and opportunities that confront practicing model users and model developers. [ABSTRACT FROM AUTHOR]

The Boundary Waters Canoe Area (BWCA) Wilderness of northern Minnesota, USA, ememplifies how fire management and natural disturbance determine forest composition and landscape structure at a broad scale. Historically, the BWCA (>400,000 ha) was subject to crown fires with a mean rotation period of 50–100 y. Fires often overlapped, creating a mosaic of differently aged stands with many stands burning frequently or, alternatively, escaping fire for several centuries. The BWCA may never have reached a steady-state (defined as a stable landscape age-class structure). In the early 1900s, a diminished fire regime began creating a more demographically diverse forest, characterized by increasingly uneven-aged stands. Shade-tolerant species typical of the region began replacing the shade-intolerant species that composed the fire-generated even-aged stands. Red pine ( Pinus resinosa) stands are relatively uncommon in the BWCA today and are of special concern. The replacement of early-to-midsuccessional species is occurring at the scale of individual gaps, producing mixed-species multiaged forests. We used LANDIS, a spatially explicit forest landscape model, to investigate the long-term consequences of fire reintroduction or continuing fire absence on forest composition and landscape structure. Fire reintroduction was evaluated at three potential mean fire rotation periods (FRP): 50,100, and 300 y. Our model scenarios predict that if fire reintroduction mimics the natural fire regime (bracketed by FRP = 50 and 100 y), it will be most successful at preserving the original species composition and landscape structure, although jack pine ( Pinus banksiana) may require special management. With limited fire reintroduction, all of the extant species are retained although species dominance and landscape structure will be substantially altered. If fire remains absent, many fire-dependent species will be lost as local dominants, including red pine. The landscape appears to be in a state of rapid change and a shift in management to promote fire may need to be implemented soon to prevent further deviation from historic, presettlement conditions. [ABSTRACT FROM AUTHOR]