An ecological classification of forest landscape simulation models: tools and strategies for understanding broad-scale forested ecosystems

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 configuration. 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.     

The challenges of forest modeling given climate change

Forest landscape modeling encompasses many core principles of landscape ecology: spatial resolution and extent, spatially explicit local and regional context, disturbance dynamics, integration of human activity, and explicit links to management and policy. Models of forest change inform land managers about strategies to adapt to the effects of an altered or changing environment across large, forested landscapes. Despite past successes, major challenges remain for landscape ecologists representing the dynamics of complex systems with a computer model, particularly given climate change. Here, I review major modeling challenges unique to climate change and suggest paths forward as climate change increasingly becomes a focus of landscape modeling efforts.     

Recovery dynamics and climate change effects to future New England forests

Context

Forests throughout eastern North America continue to recover from broad-scale intensive land use that peaked in the nineteenth century. These forests provide essential goods and services at local to global scales. It is uncertain how recovery dynamics, the processes by which forests respond to past forest land use, will continue to influence future forest conditions. Climate change compounds this uncertainty.

Objectives

We explored how continued forest recovery dynamics affect forest biomass and species composition and how climate change may alter this trajectory.

Methods

Using a spatially explicit landscape simulation model incorporating an ecophysiological model, we simulated forest processes in New England from 2010 to 2110. We compared forest biomass and composition from simulations that used a continuation of the current climate to those from four separate global circulation models forced by a high emission scenario (RCP 8.5).

Results

Simulated forest change in New England was driven by continued recovery dynamics; without the influence of climate change forests accumulated 34 % more biomass and succeed to more shade tolerant species; Climate change resulted in 82 % more biomass but just nominal shifts in community composition. Most tree species increased AGB under climate change.

Conclusions

Continued recovery dynamics will have larger impacts than climate change on forest composition in New England. The large increases in biomass simulated under all climate scenarios suggest that climate regulation provided by the eastern forest carbon sink has potential to continue for at least a century.

     

Do small-grain processes matter for landscape scale questions? Sensitivity of a forest landscape model to the formulation of tree growth rate

Process-based forest landscape models are valuable tools for testing basic ecological theory and for projecting how forest landscapes may respond to climate change and other environmental shifts. However, the ability of these models to accurately predict environmentally-induced shifts in species distributions as well as changes in forest composition and structure is often contingent on the phenomenological representation of individual-level processes accurately scaling-up to landscape-level community dynamics. We use a spatially explicit landscape forest model (LandClim) to examine how three alternative formulations of individual tree growth (logistic, Gompertz, and von Bertalanffy) influence model results. Interactions between growth models and landscape characteristics (landscape heterogeneity and disturbance intensity) were tested to determine in what type of landscape simulation results were most sensitive to growth model structure. We found that simulation results were robust to growth function formulation when the results were assessed at a large spatial extent (landscape) and when coarse response variables, such as total forest biomass, were examined. However, results diverged when more detailed response variables, such as species composition within elevation bands, were considered. These differences were particularly prevalent in regions that included environmental transition zones where forest composition is strongly driven by growth-dependent competition. We found that neither landscape heterogeneity nor the intensity of landscape disturbances accentuated simulation sensitivity to growth model formulation. Our results indicate that at the landscape extent, simulation results are robust, but the reliability of model results at a finer resolution depends critically on accurate tree growth functions.     

The past and future of modeling forest dynamics: from growth and yield curves to forest landscape models

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.

     

Forest fragmentation, climate change and understory fire regimes on the Amazonian landscapes of the Xingu headwaters

Understory fire modeling is a key tool to investigate the cornerstone concept of landscape ecology, i.e. how ecological processes relate to landscape structure and dynamics. Within this context, we developed FISC??a model that simulates fire ignition and spread and its effects on the forest carbon balance. FISC is dynamically coupled to a land-use change model to simulate fire regimes on the Amazonian landscapes of the Xingu Headwaters under deforestation, climate change, and land-use management scenarios. FISC incorporates a stochastic cellular automata approach to simulate fire spread across agricultural and forested lands. CARLUC, nested in FISC, simulates fuel dynamics, forest regrowth, and carbon emissions. Simulations of fire regimes under modeled scenarios revealed that the major current and future driver of understory fires is forest fragmentation rather than climate change. Fire intensity proved closely related to the landscape structure of the remaining forest. While climate change may increase the percentage of forest burned outside protected areas by 30% over the next four decades, deforestation alone may double it. Nevertheless, a scenario of forest recovery and better land-use management would abate fire intensity by 18% even in the face of climate change. Over this time period, the total carbon balance of the Xingu??s forests varies from an average net sink of 1.6?ton?ha^?1?year^?1 in the absence of climate change, fire and deforestation to a source of ?0.1?ton?ha^?1?year^?1 in a scenario that incorporates these three processes.     

Spatial resilience of forested landscapes under climate change and management

Context

Resilience, the ability to recover from disturbance, has risen to the forefront of scientific policy, but is difficult to quantify, particularly in large, forested landscapes subject to disturbances, management, and climate change.

Objectives

Our objective was to determine which spatial drivers will control landscape resilience over the next century, given a range of plausible climate projections across north-central Minnesota.

Methods

Using a simulation modelling approach, we simulated wind disturbance in a 4.3 million ha forested landscape in north-central Minnesota for 100 years under historic climate and five climate change scenarios, combined with four management scenarios: business as usual (BAU), maximizing economic returns (‘EcoGoods’), maximizing carbon storage (‘EcoServices’), and climate change adaption (‘CCAdapt’). To estimate resilience, we examined sites where simulated windstorms removed >70% of the biomass and measured the difference in biomass and species composition after 50 years.

Results

Climate change lowered resilience, though there was wide variation among climate change scenarios. Resilience was explained more by spatial variation in soils than climate. We found that BAU, EcoGoods and EcoServices harvest scenarios were very similar; CCAdapt was the only scenario that demonstrated consistently higher resilience under climate change. Although we expected spatial patterns of resilience to follow ownership patterns, it was contingent upon whether lands were actively managed.

Conclusions

Our results demonstrate that resilience may be lower under climate change and that the effects of climate change could overwhelm current management practices. Only a substantial shift in simulated forest practices was successful in promoting resilience.

     

Bird response to future climate and forest management focused on mitigating climate change

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.

     

From monocultures to mixed-species forests: is tree diversity key for providing ecosystem services at the landscape scale?

Context

Converting monocultures to mixed-species stands is thought to be a promising approach to increase forest productivity and resilience, while additionally providing other ecosystem goods and services (EGS). However, the importance of tree species composition and structure remains unclear, particularly beyond the stand scale due to the difficulty of conducting comprehensive, long-term experiments.

Objectives

To compare the ability of different tree species mixtures to provide various EGS at the landscape scale.

Methods

We used a dynamic forest landscape model to simulate all possible combinations of dominant tree species for two landscapes; a high-elevation alpine region (Dischma valley, Switzerland) and a lowland valley (Mt. Feldberg, Germany). We evaluated multiple EGS, including protection from gravitational hazards, aboveground biomass, and habitat quality, and examined trade-offs and synergies between them.

Results

Mixed-species forests were usually better in providing multiple EGS, although monocultures were often best for single EGS. The simulation results also demonstrated how changing environmental conditions along an elevational gradient had a strong impact on the structure of different species combinations and therefore on the provisioning of EGS.

Conclusion

Tree species diversity alone is not a good predictor of multifunctionality. Mixtures should be selected based on local environmental conditions, complementary functional traits, and the ability to provide the EGS of interest. Although our work focused on current climatic conditions, we discuss how the modelling framework could be employed to consider the impacts of climate change and disturbances to improve our understanding of how mixed-species stands could be used to cope with these challenges.

     

Climate change adaptation strategies for federal forests of the Pacific Northwest,USA: ecological,policy, and socio-economic perspectives

Conserving biological diversity in a changing climate poses major challenges for land managers and society. Effective adaptive strategies for dealing with climate change require a socio-ecological systems perspective. We highlight some of the projected ecological responses to climate change in the Pacific Northwest, U.S.A and identify possible adaptive actions that federal forest managers could take. The forest landscape, ownership patterns and recent shift toward ecologically based forest management provide a good starting place for conserving biological diversity under climate change. Nevertheless, undesirable changes in species and ecosystems will occur and a number of adaptive actions could be undertaken to lessen the effects of climate change on forest ecosystems. These include: manipulation of stand and landscape structure to increase ecological resistance and resilience; movement of species and genotypes; and engaging in regional, multi-ownership planning to make adaptive actions more effective. Although the language and goals of environmental laws and policies were developed under the assumption of stable climate and disturbance regimes, they appear to be flexible enough to accommodate many adaptive actions. It is less certain, however, if sufficient social license and economic capacity exist to undertake these actions. Given the history of contentious and litigious debate about federal forest management in this region, it is likely that some of these actions will be seen as double-edge swords, spurring social resistance, especially where actions involve cutting trees. Given uncertainties and complexity, collaborative efforts that promote learning (e.g. adaptive management groups) must be rejuvenated and expanded.     

Revision and application of the LINKAGES model to simulate forest growth in central hardwood landscapes in response to climate change

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.

     

Contrasting the ability of data to make inferences regarding dispersal: case study of the Red-cockaded woodpecker (Picoides borealis)

Dispersal is a critical biological process that contributes to the persistence of species in complex and dynamic landscapes. However, little is known about the ability of different types of data to reveal how species interact with landscape patterns during dispersal. Further, application of process-based, landscape-scale models able to capture the influence of land use and climate change are limited by this lack of dispersal knowledge. Here we highlight a method for building such models when dispersal parameters are unknown, but information on the mating system and survival are available. We applied a common statistical framework, rooted in information theory, to contrast the ability of abundance, movement, and genetic data to estimate dispersal parameters for endangered Red-cockaded woodpecker (RCW), using an individual-based, spatially-explicit population model. Dispersal was modeled as a multifaceted process in which foray distance, long-distance dispersal, competition for mates, and landscape permeability were treated as uncertain. We found that movement data are three-times more powerful than abundance data collected at the same spatial and temporal scales. However, habitat occupancy data collected over much a shorter time scale but at regional spatial scales were very effective for estimating dispersal. We also found that one-year of abundance data provided a similar reduction in uncertainty as genetic differences among breeding groups estimated using a 24-year pedigree. Substituting population genetic data for movement and abundance data often led to the same parameter values, but not always. Our study highlights important differences in the information content of data commonly collected in the field.     

Predicting land use change: comparison of models based on landowner surveys and historical land cover trends

To make informed planning decisions, community leaders, elected officials, scientists, and natural resource managers must be able to evaluate potential effects of policies on land use change. Many land use change models use remotely-sensed images to make predictions based on historical trends. One alternative is a survey-based approach in which landowners’ stated intentions are modeled. The objectives of our research were to: (1) develop a survey-based landowner decision model (SBM) to simulate future land use changes, (2) compare projections from the SBM with those from a trend-based model (TBM), and (3) demonstrate how two alternative policy scenarios can be incorporated into the SBM and compared. We modeled relationships between land management decisions, collected from a mail survey of private landowners, and the landscape, using remotely-sensed imagery and ownership parcel data. We found that SBM projections were within the range of TBM projections and that the SBM was less affected by errors in image classification. Our analysis of alternative policies demonstrates the importance of understanding potential effects of targeted land use policies. While policies oriented toward increasing enrollment in the Conservation Reserve Program (CRP) resulted in a large (11–13%) increase in CRP lands, policies targeting increased forest thinning on private non-industrial lands increased low-density forest projections by only 1%. The SBM approach is particularly appropriate for landscapes including many landowners, because it reflects the decision-making of the landowners whose individual actions will result in collective landscape change.     

Effects of landscape urbanization on magpie occupancy dynamics in France

Responses of species to landscape modifications are generally documented through their distribution at a given time along an intensity gradient of land transformation. By focusing on patterns, we are limited to infer ecological processes occurring within a system and its response to environmental disturbances which can further change over time. Using diachronic datasets at the scale of France, we analyzed the spatial responses of the black-billed magpie, which has recently colonized cities, to landscape urbanization. This study applied recently developed statistical approaches incorporating detection uncertainty of the magpie, based on the capture-recapture statistical framework. We tested whether, and how, extinction and colonization mechanisms influenced variations of magpie occupancy from 2001 to 2005. In addition, we assessed the importance of the recent urbanization of the French countryside in determining population dynamics. Overall, our analysis proved that the proportion of urban areas and recent urbanization in France led to an increase in the probability of magpie occupancy. Unexpectedly, the species is concomitantly disappearing from the countryside, leading to a rapid change in the distribution of the species. This study stressed the importance of incorporating detection uncertainty in inference process about spatial dynamics. Overall, we show how useful it is to account for the dynamic evolution of the landscape in ecological studies.     

Extinction risk of wood-living model species in forest landscapes as related to forest history and conservation strategy

Dead wood is a critical resource for biodiversity in boreal forests. We analysed the persistence of five model species inhabiting dead wood. By parameterising a metapopulation model (the incidence function model), the model species were all assigned characteristics that makes it likely that they have disappeared from some (20%) forest landscapes with a long history of forest management. In the metapopulation model, a forest stand (5 ha) was regarded as a habitat patch. The amount of habitat in each patch was obtained from models of dead wood dynamics of Norway spruce in central Sweden. Dead wood generated by altered management over the entire landscape was found to be less efficient in reducing extinction risks in comparison to the same amount of dead wood generated by protecting reserves. Because generation of dead wood by altered management is often less expensive than setting aside reserves, it is difficult to determine which conservation measure is most cost-efficient. In a landscape subjected to forestry for the first time, it was better to preserve a few large reserves than many small ones. However, in a managed, highly fragmented forest landscape it was better to set aside many small reserves. The reason for this was that small plots with high habitat quality could be selected, while large reserves originally contained habitats both of high and low quality, and the rate of habitat quality increase was low. A strategy for biodiversity conservation in a managed forest landscape should include information about the history of the landscape, the current amount and spatial distribution of forest habitats, and the potential for rapid restoration of forest habitats, both on managed and unmanaged forest land.     

Forest fragmentation and regrowth in an institutional mosaic of community, government and private ownership in Nepal

This study analyzes forest change in an area of Nepal that signifies a delicate balance between sustaining the needs and livelihood of a sizable human population dependent on forest products, and an effort to protect important wildlife and other natural resources. The study area, a portion of the Chitwan valley district of Nepal, represents what may be becoming a common institutional mosaic in many countries of the world who have a population reliant on forest products for their livelihood: (1) a national park; (2) a designated park buffer involving participatory forest management programs; (3) scattered patches of designated community forest; and (4) large areas of adjacent landscape made up of mostly private landholdings under agricultural practices. Utilizing Landsat images from 1989 and 2000, we analyze land cover change in each of these management zones using landscape ecology metrics and quantifying proportional distributions of land cover categories. Our results show significant differences in terms of land cover dynamics and landscape spatial pattern between these land ownership classes. These findings indicate that community-based institutions (participatory management programs in the park buffer and the designated community forests) are capable of halting or even reversing trends in deforestation and forest fragmentation.     

Changes in forest biomass and tree species distribution under climate change in the northeastern United States

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.

     

Plant and animal diversity in a region of the Southern Alps: the role of environmental and spatial processes

Different organisms respond to landscape configuration and spatial structure in different terms and across different spatial scales. Here, regression models with variation partitioning were applied to determine relative influence of the three groups of variables (climate, land use and environmental heterogeneity) and spatial structure variables on plant, bird, orthopteran and butterfly species richness in a region of the Southern Alps, ranging in elevation from the sea level to 2,780 m. Grassland and forest cover were positively correlated with species richness in both taxonomic groups, whilst species richness decreased with increasing urban elements and arable land. The variation was mainly explained by the shared component between the three groups in plants and between landscape and environmental heterogeneity in birds. The variation was related to independent land use effect in insects. The distribution in species richness was spatially structured for plants, birds and orthopterans, whilst in butterflies, no spatial structure was detected. Plant richness was associated with linear trend variation and broad-scale spatial structure in the northern part of the region, whilst bird richness with broad-scale variation which occurs on the external Alpine ridge. Orthopteran diversity was strongly related to fine-scale spatial structure, generated by dynamic processes or by unmeasured spatially structured abiotic factors. Although the study was carried out in relatively small area, the four taxonomic groups seem to respond to biodiversity drivers in a surprisingly different way. This has considerable implications for conservation planning as it restricts the usefulness of simple indicators in prioritizing areas for conservation purposes.     

Between a rock and a hard place: the impacts of climate change and housing development on breeding birds in California

Although the effects of climate change on species distributions have received considerable attention, land-use change continues to threaten wildlife by contributing to habitat loss and degradation. We compared projected spatial impacts of climate change and housing development across a range of housing densities on California’s birds to evaluate the relative potential impacts of each. We used species-distribution models in concert with current and future climate projections and spatially explicit housing-development density projections in California. We compared their potential influence on the distributions of 64 focal bird species representing six major vegetation communities. Averaged across GCMs, species responding positively to climate change were projected to gain 253,890 km² and species responding negatively were projected to lose 335,640 km². Development accounted for 32 % of the overall reductions in projected species distributions. In terms of land area, suburban and exurban development accounted for the largest portion of land-use impacts on species’ distributions. Areas in which climatic suitability and housing density were both projected to increase were concentrated along the foothills of the Sierra Nevada and areas of the north coast. Areas of decreasing climatic suitability and increasing housing density were largely concentrated within the Central Valley. Our analyses suggest that the cumulative effects of future housing development and climate change will be large for many bird species, and that some species projected to expand their distributions with climate change may actually lose ground to development. This suggests that a key climate change adaptation strategy will be to minimize the impacts of housing development. To do this effectively, comprehensive policies to guide land use decisions are needed at the broader scales of climate change.