Context

Forest landscapes are increasingly managed for fire resilience, particularly in the western US which has recently experienced drought and widespread, high-severity wildfires. Fuel reduction treatments have been effective where fires coincide with treated areas. Fuel treatments also have the potential to reduce drought-mortality if tree density is uncharacteristically high, and to increase long-term carbon storage by reducing high-severity fire probability.

Objective

Assess whether fuel treatments reduce fire intensity and spread and increase carbon storage under climate change.

Methods

We used a simulation modeling approach that couples a landscape model of forest disturbance and succession with an ecosystem model of carbon dynamics (Century), to quantify the interacting effects of climate change, fuel treatments and wildfire for carbon storage potential in a mixed-conifer forest in the western USA.

Results

Our results suggest that fuel treatments have the potential to ‘bend the C curve’, maintaining carbon resilience despite climate change and climate-related changes to the fire regime. Simulated fuel treatments resulted in reduced fire spread and severity. There was partial compensation of C lost during fuel treatments with increased growth of residual stock due to greater available soil water, as well as a shift in species composition to more drought- and fire-tolerant Pinus jeffreyi at the expense of shade-tolerant, fire-susceptible Abies concolor.

Conclusions

Forest resilience to global change can be achieved through management that reduces drought stress and supports the establishment and dominance of tree species that are more fire- and drought-resistant, however, achieving a net C gain from fuel treatments may take decades.

Context

Quantitative models of forest dynamics have followed a progression toward methods with increased detail, complexity, and spatial extent.

Objectives

We highlight milestones in the development of forest dynamics models and identify future research and application opportunities.

Methods

We reviewed milestones in the evolution of forest dynamics models from the 1930s to the present with emphasis on forest growth and yield models and forest landscape models We combined past trends with emerging issues to identify future needs.

Results

Historically, capacity to model forest dynamics at tree, stand, and landscape scales was constrained by available data for model calibration and validation; computing capacity; model applicability to real-world problems; and ability to integrate biological, social, and economic drivers of change. As computing and data resources improved, a new class of spatially explicit forest landscape models emerged.

Conclusions

We are at a point of great opportunity in development and application of forest dynamics models. Past limitations in computing capacity and in data suitable for model calibration or evaluation are becoming less restrictive. Forest landscape models, in particular, are ready to transition to a central role supporting forest management, planning, and policy decisions.

Recommendations

Transitioning forest landscape models to a central role in applied decision making will require greater attention to evaluating performance; building application support staffs; expanding the included drivers of change, and incorporating metrics for social and economic inputs and outputs.

Context

Interactions between landscape-scale processes and fine-grained habitat heterogeneity are usually invoked to explain species occupancy in fragmented landscapes. In variegated landscapes, however, organisms face continuous variation in micro-habitat features, which makes necessary to consider ecologically meaningful estimates of habitat quality at different spatial scales.

Objectives

We evaluated the spatial scales at which forest cover and tree quality make the greatest contribution to the occupancy of the long-horned beetle Microplophorus magellanicus (Coleoptera: Cerambycidae) in a variegated forest landscape.

Methods

We used averaged data of tree quality (as derived from remote sensing estimates of the decay stage of single trees) and spatially independent pheromone-baited traps to model the occurrence probability as a function of multiple cross-scale combinations between forest cover and tree quality (with scales ranging between 50 and 400 m).

Results

Model support and performance increased monotonically with the increasing scale at which tree quality was measured. Forest cover was not significant, and did not exhibit scale-specific effects on the occurrence probability of M. magellanicus. The interactive effect between tree quality and forest cover was stronger than the independent (additive) effects of tree quality and particularly forest cover. Significant interactions included tree quality measured at spatial scales ≥200 m, but cross-scale interactions occurred only in four of the seven best-supported models.

Conclusions

M. magellanicus respond to the high-quality trees available in the landscape rather than to the amount of forest per se. Conservation of viable metapopulations of M. magellanicus should consider the quality of trees at spatial scales >200 m.

Context

Habitat destruction is the leading threat to terrestrial biodiversity, isolating remnant habitat in a matrix of modified vegetation.

Objectives

Our goal was to determine how species richness in several broad taxonomic groups from remnant forest was influenced by matrix quality, which we characterized by comparing plant biomass in forest and the surrounding matrix.

Methods

We coupled data on species-area relationships (SARs) in forest remnants from 45 previously published studies with an index of matrix quality calculated using new estimates of plant biomass derived from satellite imagery.

Results

The effect size of SARs was greatest in landscapes with low matrix quality and little forest cover. SARs were generally stronger for volant than for non-volant species. For the terrestrial taxa included in our analysis, matrix quality decreased as the proportion of water, ice, or urbanization in a landscape increased.

Conclusions

We clearly demonstrate that matrix quality plays a major role in determining patterns of species richness in remnant forest. A key implication of our work is that activities that increase matrix quality, such as active and passive habitat restoration, may be important conservation measure for maintaining and restoring biodiversity in modified landscapes.

Context

Patterns of forest diversity are less well known in the boreal forest of interior Alaska than in most ecosystems of North America. Proactive forest planning requires spatially accurate information about forest diversity. Modeling is a cost-efficient way of predicting key forest diversity measures as a function of human and environmental factors.

Objectives

Investigate and predict the patterns and processes in tree species and tree size-class diversity within the boreal forest of Alaska for a first mapped quantitative baseline.

Methods

For the boreal forest of Alaska, USA, we employed Random Forest Analysis (machine learning) and the Boruta algorithm in R to predict tree species and tree size-class diversity for the entire region using a combination of forest inventory data and a suite of 30 predictors from public open-access data archives that included climatic, distance, and topographic variables. We developed prediction maps in a GIS for the current levels (Year 2012) of tree size-class and species diversity.

Results

The method employed here yielded good accuracy for the huge Alaskan landscape despite the exclusion of spectral reflectance data. It’s the first quantified GIS prediction baseline. The results indicate that the geographic pattern of tree species diversity differs from the pattern of tree size-class diversity across this forest type.

Conclusions

The results suggest that human factors combined with topographical factors had a large impact on predicting the patterns of diversity in the boreal forest of interior Alaska.

Context

Global climate change impacts forest growth and methods of modeling those impacts at the landscape scale are needed to forecast future forest species composition change and abundance. Changes in forest landscapes will affect ecosystem processes and services such as succession and disturbance, wildlife habitat, and production of forest products at regional, landscape and global scales.

Objectives

LINKAGES 2.2 was revised to create LINKAGES 3.0 and used it to evaluate tree species growth potential and total biomass production under alternative climate scenarios. This information is needed to understand species potential under future climate and to parameterize forest landscape models (FLMs) used to evaluate forest succession under climate change.

Methods

We simulated total tree biomass and responses of individual tree species in each of the 74 ecological subsections across the central hardwood region of the United States under current climate and projected climate at the end of the century from two general circulation models and two representative greenhouse gas concentration pathways.

Results

Forest composition and abundance varied by ecological subsection with more dramatic changes occurring with greater changes in temperature and precipitation and on soils with lower water holding capacity. Biomass production across the region followed patterns of soil quality.

Conclusions

Linkages 3.0 predicted realistic responses to soil and climate gradients and its application was a useful approach for considering growth potential and maximum growing space under future climates. We suggest Linkages 3.0 can also can used to inform parameter estimates in FLMs such as species establishment and maximum growing space.

Context

Global temperatures are projected to increase and affect forests and wildlife populations. Forest management can potentially mitigate climate-induced changes through promoting carbon sequestration, forest resilience, and facilitated change.

Objectives

We modeled direct and indirect effects of climate change on avian abundance through changes in forest landscapes and assessed impacts on bird abundances of forest management strategies designed to mitigate climate change effects.

Methods

We coupled a Bayesian hierarchical model with a spatially explicit landscape simulation model (LANDIS PRO) to predict avian relative abundance. We considered multiple climate scenarios and forest management scenarios focused on carbon sequestration, forest resilience, and facilitated change over 100 years.

Results

Management had a greater impact on avian abundance (almost 50% change under some scenarios) than climate (<3% change) and only early successional and coniferous forest showed significant change in percent cover across time. The northern bobwhite was the only species that changed in abundance due to climate-induced changes in vegetation. Northern bobwhite, prairie warbler, and blue-winged warbler generally increased in response to warming temperatures but prairie warbler exhibited a non-linear response and began to decline as summer maximum temperatures exceeded 36 °C at the end of the century.

Conclusion

Linking empirical models with process-based landscape change models can be an effective way to predict climate change and management impacts on wildlife, but time frames greater than 100 years may be required to see climate related effects. We suggest that future research carefully consider species-specific effects and interactions between management and climate.

Context

Landscape patterns created by natural disturbance such as windstorms can affect forest regeneration, carbon cycling, and other ecological processes.

Objectives

We develop a method for remotely measuring tornado damage severity and describe landscape-scale patterns of tornado damage. We examine the extent and distribution of damage severity and gaps created by tornadoes, and examine how topographic variation can influence tornado damage severity.

Methods

Focusing on two April 2011 tornadoes that struck the Chattahoochee National Forest (CNF) in Georgia and the Great Smoky Mountains (GSM) in Tennessee, we used supervised classification of aerial photographs to map damage severity. We report the extent and distribution of damage severity from each track and characterize patterns of damage using FragStats. Using topographic overlays, we test hypotheses regarding how physiographic features such as valleys and ridges affect tornado damage severity.

Results

Tornado damage severity estimates were significantly correlated with ground-truth measurements. The 64-km CNF track damaged 1712 ha (>25 % severity), while the 26-km GSM track damaged 1407 ha. Tornado damage severity was extremely variable and frequency of gap sizes drastically decreased with size, with many small gaps and few very large gaps, consistent with other types of wind damage. Damage severity declined as tornadoes ascended ridges and increased as they descended ridges. This effect was more consistent on shallow slopes relative to steeper slopes.

Conclusions

This study outlines an objective methodology for remotely characterizing tornado damage severity. The results from this study fill an important gap in ecological understanding of the spatial components of the forest tornado disturbance regime.

Context

A challenging issue in landscape ecology is the evaluation of changes in a forest landscape following a disturbance. This evaluation usually entails examining changes in the forest inventory, which represents the best information available for a given forest region.

Objectives

Our aim was to extend existing methods used to evaluate forest inventory to include additional variables, such as value-based forest product options, wood fibre attributes, and ecosystem services. Inclusion of such variables in forest inventory evaluations would allow research results to be presented from an economic perspective, which is often required for policy development and forest management decision-making.

Methods

We developed a value-based framework to evaluate forest inventory and implemented it in the wood fibre value simulation model. We then used a local data set from Manitoba, Canada, to show how the model can be applied to the mapping of new inventory layers to facilitate the evaluation of landscape changes.

Results

Five new inventory layers are mapped including bioenergy and heating value that can be directly used for evaluating landscape changes, and wood density, fibre length, and pulp yield, which can be combined with total wood volume to derive new variables or indices to express changes in landscape conditions.

Conclusions

Our model can contribute to the assessment of landscape changes by indicating the values a forest can have when it is used for different conservation or utilization purposes. The model can also support improved decision-making with respect to the management of forest resources.

Context

Forest loss and fragmentation negatively affect biodiversity. However, disturbances in forest canopy resulting from repeated deforestation and reforestation are also likely important drivers of biodiversity, but are overlooked when forest cover change is assessed using a single time interval.

Objectives

We investigated two questions at the nexus of plant diversity and forest cover change dynamics: (1) Do multitemporal forest cover change trajectories explain patterns of plant diversity better than a simple measure of overall forest change? (2) Are specific types of forest cover change trajectories associated with significantly higher or lower levels of diversity?

Methods

We sampled plant biodiversity in forests spanning the Charlotte, NC, region. We derived forest cover change trajectories occurring within nested spatial extents per sample site using a time series of aerial photos from 1938 to 2009, then classified trajectories by spatio-temporal patterns of change. While accounting for landscape and environmental covariates, we assessed the effects of the trajectory classes as compared to net forest cover change on native plant diversity.

Results

Our results indicated that forest stand diversity is best explained by forest change trajectories, while the herb layer is better explained by net forest cover change. Three distinct forest change trajectory classes were found to influence the forest stand and herb layer.

Conclusions

The influence of forest dynamics on biodiversity can be overlooked in analyses that use only net forest cover change. Our results illustrate the utility of assessing how specific trajectories of past land cover change influence biodiversity patterns in the present.

Context

Field inventory plots which usually have small sizes of around 0.25–1 ha can only represent a sample of the much larger surrounding forest landscape. Based on airborne laser scanning (LiDAR) it has been shown for tropical forests that the bias in the selection of small field plots may hamper the extrapolation of structural forest attributes to larger spatial scales.

Objectives

We conducted a LiDAR study on tropical montane forest and evaluated the representativeness of chosen inventory plots with respect to key structural attributes.

Methods

We used six forest inventory and their surrounding landscape plots on Mount Kilimanjaro in Tanzania and analyzed the similarities for mean top-of-canopy height (TCH), aboveground biomass (AGB), gap fraction, and leaf-area index (LAI). We also analyzed the similarity in gap-size frequencies for the landscape plots.

Results

Mean biases between inventory and landscape plots were large reaching as much as 77% for gap fraction, 22% for LAI or 15% for AGB. Despite spatial heterogeneity of the landscape, gap-size frequency distributions were remarkably similar between the landscape plots.

Conclusions

The study indicates that biases in field studies of forest structure may be strong. Even when mean values were similar between inventory and landscape plots, the mostly non-normally distributed probability densities of the forest variable indicated a considerable sampling error of the small field plot to approximate the forest variable in the surrounding landscape. This poses difficulties for the spatial extrapolation of forest structural attributes and for assessing biomass or carbon fluxes at larger regional scales.

Context

Forest landscapes at the southern boreal forest transition zone are likely to undergo great alterations due to projected changes in regional climate.

Objectives

We projected changes in forest landscapes resulting from four climate scenarios (baseline, RCP 2.6, RCP 4.5 and RCP 8.5), by simulating changes in tree growth and disturbances at the southern edge of Canada’s boreal zone.

Methods

Projections were performed for four regions located on an east–west gradient using a forest landscape model (LANDIS-II) parameterized using a forest patch model (PICUS).

Results

Climate-induced changes in the competitiveness of dominant tree species due to changes in potential growth, and substantial intensification of the fire regime, appear likely to combine in driving major changes in boreal forest landscapes. Resulting cumulative impacts on forest ecosystems would be manifold but key changes would include (i) a strong decrease in the biomass of the dominant boreal species, especially mid- to late-successional conifers; (ii) increases in abundance of some temperate species able to colonize disturbed areas in a warmer climate; (iii) increases in the proportions of pioneer and fire-adapted species in these landscapes and (iv) an overall decrease in productivity and total biomass. The greatest changes would occur under the RCP 8.5 radiative forcing scenario, but some impacts can be expected even with RCP 2.6.

Conclusions

Western boreal forests, i.e., those bordering the prairies, are the most vulnerable because of a lack of species adapted to warmer climates and major increases in areas burned. Conservation and forest management planning within the southern boreal transition zone should consider both disturbance- and climate-induced changes in forest communities.

Context

Multi-objective management can mitigate conflicts among land-use objectives. However, the effectiveness of a multi-objective solution depends on the spatial scale at which land-use is optimized. This is because the ecological variation within the planning region influences the potential for site-specific prioritization according to the different objectives.

Objectives

We optimized the allocation of forest management strategies to maximize the joint production of two conflicting objectives, timber production and carbon storage, at increasing spatial scales. We examined the impacts of the extent of the planning region on the severity of the conflict, the potential for its mitigation, and the strategies that were identified as optimal.

Methods

Using forecasted data from a forest simulator, we constructed Pareto frontiers optimizing the joint provision of the objectives in production forests in Finland. Optimization was conducted within increasing hierarchical spatial scales and outcomes were compared in terms of the severity of the conflict and the solution to mitigate it.

Results

The trade-offs between timber production and carbon storage appeared less severe and could be mitigated more effectively the larger the planning regions were, but the improvements became minor beyond the scale of ‘large forest holding’. The results thus indicate that this scale, approximately 100 stands or 200 ha, is large enough to effectively mitigate the conflict between timber production and carbon storage.

Conclusions

Management planning over relatively small forest areas (200 ha) can mitigate ecosystem service trade-offs effectively. Thus the effective use of multi-objective optimization tools may be feasible even in small-scale forestry.

Context

In tropical landscapes, dominant land-use changes involve conversion of intact forest to an agricultural matrix with embedded fragments of remnant forest. However, most research to date has focused on how these land-use changes affect species within the fragmented ecosystem, rather than the flux of energy and nutrients within these different landscape elements.

Objectives

We examined how forest fragmentation and conversion to orange fields impact the potential for litter decomposition in a Costa Rican landscape, in particular via effects on macroinvertebrates (MIs) and microclimate.

Methods

We measured mass losses of a standard leaf litter in four habitats: orange fields, small forest fragments, large forest fragments and intact forest. Litter bags were constructed of mesh that either excluded or allowed MIs. Decomposition rates were measured in wet and dry seasons, and at different distances from the forest edge.

Results

Forest fragmentation and forest conversion had divergent effects on decomposition rates. Decomposition rates were 7 % slower in forest fragments during the dry season than in intact forest, and this result was mediated by forest fragmentation effects on MIs. Decomposition rates were 9 % higher in orange fields during the wet season, relative to intact forest, and this pattern was explained by effects of the litter microenvironment on leaching rates or smaller invertebrates. Fragment area and distance from forest edge had minor or undetectable effects on decomposition in fragments.

Conclusions

We conclude that land-use changes affect decomposition processes in both forest and agroecosystems, and these effects can vary in mechanism and direction across disturbed landscapes.

Context

Forest landscape models (FLMs) are important tools for simulating forest changes over broad spatial and temporal scales. The ability of FLMs to accurately predict forest changes may be significantly influenced by the formulations of site-scale processes including seedling establishment, tree growth, competition, and mortality.

Objective

The objectives of this study were to investigate the effects of site-scale processes and interaction effects of site-scale processes and harvest on landscape-scale forest change predictions.

Methods

We compared the differences in species’ distribution (quantified by species’ percent area), total aboveground biomass, and species’ biomass derived from two FLMs: (1) a model that explicitly incorporates stand density and size for each species age cohort (LANDIS PRO), and (2) a model that explicitly tracks biomass for each species age cohort (LANDIS-II with biomass succession extension), which are variants from the LANDIS FLM family with different formulations of site-scale processes.

Results

For early successional species, the differences in simulated distribution and biomass were small (mostly less than 5 %). For mid- to late-successional species, the differences in simulated distribution and biomass were relatively large (10–30 %). The differences in species’ biomass predictions were generally larger than those for species’ distribution predictions. Harvest mediated the differences on landscape-scale predictions.

Conclusions

The effects of site-scale processes on landscape-scale forest change predictions are dependent on species’ ecological traits such as shade tolerance, seed dispersal, and growth rates.

Context

Complex structural connectivity patterns can influence the distribution of animals in coastal landscapes, particularly those with relatively large home ranges, such as birds. To understand the nuanced nature of coastal forest avifauna, where there may be considerable overlap in assemblages of adjacent forest types, the concerted influence of regional landscape context and vegetative structural connectivity at multiple spatial scales warrants investigation.

Objectives

This study determined whether species compositions of coastal forest bird assemblages differ with regional landscape context or with forest type, and if this is influenced by structural connectivity patterns measured at multiple spatial scales.

Methods

Three replicate bird surveys were conducted in four coastal forest types at ten survey locations across two regional landscape contexts in northeast Australia. Structural connectivity patterns of 11 vegetation types were quantified at 3, 6, and 12 km spatial scales surrounding each survey location, and differences in bird species composition were evaluated using multivariate ordination analysis.

Results

Bird assemblages differed between regional landscape contexts and most coastal forest types, although Melaleuca woodland bird assemblages were similar to those of eucalypt woodlands and rainforests. Structural connectivity was primarily correlated with differences in bird species composition between regional landscape contexts, and correlation depended on vegetation type and spatial scale.

Conclusions

Spatial scale, landscape context, and structural connectivity have a combined influence on bird species composition. This suggests that effective management of coastal landscapes requires a holistic strategy that considers the size, shape, and configuration of all vegetative components at multiple spatial scales.

Context

Terrestrial ecosystems, including tropical forests, are hypothesized to have tipping points beyond which environmental change triggers rapid and radical shifts to novel alternative states.

Objective

We explored the overarching hypothesis that fire-mediated alternative stable states exist in the semi-deciduous tropical forest zone of Ghana, and that increased fire activity has pushed some forests to a new state in which a novel ecosystem with low tree density is maintained by fire.

Methods

We combined a 30-year time series of remotely-sensed data with field measurements to assess land cover trends, the effects of fire on forest vegetation, and the reciprocal effects of vegetation change on fire regimes, in four forest reserves. We analyzed precipitation trends to determine if shifts in vegetation and fire regime reflected a shift to a drier climate.

Results

Two of the reserves experienced forest loss, were impacted by frequent fires, and transitioned to a vegetation community dominated by shrubs and grasses, which was maintained by fire–vegetation feedbacks. The other two reserves experienced less fire, retained higher levels of forest cover, and resisted fire encroachment from surrounding agricultural areas. Precipitation remained relatively stable, suggesting a hysteresis effect in which different vegetation states and fire regimes coexist within a similar climate.

Conclusion

There is potential for human land use and fire to create novel and persistent non-forest vegetation communities in areas that are climatically suitable for tropical forests. These disturbance-mediated regime shifts should be taken into account when assessing future trajectories of forest landscape change in West Africa.

Context

Forests in the northeastern United States are currently in early- and mid-successional stages recovering from historical land use. Climate change will affect forest distribution and structure and have important implications for biodiversity, carbon dynamics, and human well-being.

Objective

We addressed how aboveground biomass (AGB) and tree species distribution changed under multiple climate change scenarios (PCM B1, CGCM A2, and GFDL A1FI) in northeastern forests.

Methods

We used the LANDIS PRO forest landscape model to simulate forest succession and tree harvest under current climate and three climate change scenarios from 2000 to 2300. We analyzed the effects of climate change on AGB and tree species distribution.

Results

AGB increased from 2000 to 2120 irrespective of climate scenario, followed by slight decline, but then increased again to 2300. AGB averaged 10 % greater in the CGCM A2 and GFDL A1FI scenarios than the PCM B1 and current climate scenarios. Climate change effects on tree species distribution were not evident from 2000 to 2100 but by 2300 some northern hardwood and conifer species decreased in occurrence and some central hardwood and southern tree species increased in occurrence.

Conclusions

Climate change had positive effects on forest biomass under the two climate scenarios with greatest warming but the patterns in AGB over time were similar among climate scenarios because succession was the primary driver of AGB dynamics. Our approach, which simulated stand dynamics and dispersal, demonstrated that a northward shift in tree species distributions may take 300 or more years.

Context

Forecasting the expansion of forest into Alaska tundra is critical to predicting regional ecosystem services, including climate feedbacks such as carbon storage. Controls over seedling establishment govern forest development and migration potential. Ectomycorrhizal fungi (EMF), obligate symbionts of all Alaskan tree species, are particularly important to seedling establishment, yet their significance to landscape vegetation change is largely unknown.

Objective

We used ALFRESCO, a landscape model of wildfire and vegetation dynamics, to explore whether EMF inoculum potential influences patterns of tundra afforestation and associated flammability.

Methods

Using two downscaled CMIP3 general circulation models (ECHAM5 and CCCMA) and a mid-range emissions scenario (A1B) at a 1 km² resolution, we compared simulated tundra afforestation rates and flammability from four parameterizations of EMF effects on seedling establishment and growth from 2000 to 2100.

Results

Modeling predicted an 8.8–18.2 % increase in forest cover from 2000 to 2100. Simulations that explicitly represented landscape variability in EMF inoculum potential showed a reduced percent change afforestation of up to a 2.8 % due to low inoculum potential limiting seedling growth. This reduction limited fuel availability and thus, cumulative area burned. Regardless of inclusion of EMF effects in simulations, landscape flammability was lower for simulations driven by the wetter and cooler CCCMA model than the warmer and drier ECHAM5 model, while tundra afforestation was greater.

Conclusions

Results suggest abiotic factors are the primary driver of tree migration. Simulations including EMF effects, a biotic factor, yielded more conservative estimates of land cover change across Alaska that better-matched empirical estimates from the previous century.