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Understanding Landscapes Through Spatial Modeling
Abstract
This chapter outlines how landscape simulation models can be used to support forest landscape restoration. In the first type of application, landscape models of disturbance and forest succession were used to estimate historical variability in landscape composition and configuration. An example is given based on a study in the Oregon Coast Range of USA which showed the present day forest patterns are outside the range of historical variability. Problems with this approach lie in deciding the landscape metrics to use and, in this particular case, in assembling reliable data on historical fire regimes. A second common application of landscape simulation models is to project future landscapes under alternative landscape restoration scenarios. These types of simulation experiments with landscape models focus less on making predictions of historical or future landscape conditions but, rather, place more emphasis on exploring general hypotheses about pattern-process relationships. One important insight is that changes in landscape composition and configuration often lag behind shifts in disturbance regimes, and that temporal as well as spatial landscape heterogeneity is important to consider when assessing ecological responses to changing disturbance regimes.
Supplementary resource (1)
... Initially we consider stand-level designs; these are mostly scalable to the landscape-level. Additional considerations may be necessary, however, in restoration designs for landscapes Wimberly et al., 2012;Oliver, 2014). ...
... Spatial patterning of patches with similar composition is important too, as these are affected by natural and socioeconomic attributes related to land ownership, tenure, and use. Clearly the landscape mosaic and its component patches are defined in the context of the way it is approached and spatial modeling is one way to understand landscape level vegetation dynamics, disturbances, and management activities such as restoration (Shinneman et al., 2012;Wimberly et al., 2012). Landscape classification should be more detailed than simply forest/non-forest (Lindenmayer et al., 2008), consider trade-offs among livelihoods and conservation options (Bradford and D'Amato, 2011;Boedhihartono and Sayer, 2012;Sayer et al., 2013), and identify suitable sites for intervention, prioritizing among sites for allocating scarce resources , and for guiding the monitoring design and determining success (Ruiz-Jaén and Aide, 2005b;Bestelmeyer et al., 2006;Holl and Aide, 2011). ...
... Allocation methods include geospatial approaches ranging from relatively informal techniques to considerable, formal planning (Klimas et al., 2009;Pullar and Lamb, 2012;Wimberly et al., 2012). The idea behind any prioritization approach is to maximize benefits gained from use of limited resources. ...
The forest restoration challenge (globally 2 billion ha) and the prospect of changing climate with increasing frequency of extreme events argues for approaching restoration from a functional and landscape perspective. Because the practice of restoration utilizes many techniques common to silviculture, no clear line separates ordinary forestry practices from restoration. The distinction may be that extra-ordinary activities are required in the face of degraded, damaged, or destroyed ecosystems. Restoration is driven by the desire to increase sustainability of ecosystems and their services and restoration is likely to have multiple goals arising from the motivations of those involved. The process of setting restoration objectives translates vague goals into feasible, measurable targets and ultimately actions on the ground. Our objective for this review is to synthesize the science underpinning contemporary approaches to forest restoration practice. We focus on methods and present them within a coherent terminology of four restoration strategies: rehabilitation, reconstruction, reclamation, and replacement. While not a consensus terminology, these terms have a logical foundation. Rehabilitation restores desired species composition, structure, or processes to a degraded ecosystem. Reconstruction restores native plant communities on land recently in other resource uses, such as agriculture. Reclamation restores severely degraded land generally devoid of vegetation, often the result of resource extraction, such as mining. Replacement of species (or their locally-adapted genotypes) with new species (or new genotypes) is a response to climate change. Restoration methods are presented as available tools; because adding vegetation is an effective restoration technique, the discussion of methods begins with a description of available plant materials. We then discuss altering composition under different initial overstory conditions, including deployment methods depending upon whether or not an overstory is present, how much of the landscape will be restored, and the complexity of the planting design. We present some major approaches for altering structure in degraded forest stands, and describe approaches for restoration of two key ecosystem processes, fire and flooding. Although we consider stand-level designs, what we describe is mostly scalable to the landscape-level. No restoration project is undertaken in a social vacuum; even stand-level restoration occurs within a system of governance that regulates relationships among key agents. Gathering information and understanding the social dimensions of a restoration project is as necessary as understanding the biophysical dimensions. Social considerations can trump biophysical factors.
... On the other hand, most forest changes that arise from interactions between human and natural systems are complex (Liu et al. 2007). Spatial simulation modeling is an important technique for exploring the effects of coupled natural and human processes in forested landscapes (Wimberly et al. 2012). Forest landscape models (FLMs) and land change models (LCMs) are two key classes of models that can be used to analyze natural and anthropogenic disturbances . ...
Context
Subtropical forests have and will continue to face tremendous pressure from various disturbances, which have the potential to alter forest composition, structure, and function. Forest dynamics relate to spatial patterns, ecological processes, and their interactions. However, integrating forest ecosystems and land systems has seldom been attempted in southern China.
Objectives
We explore the spatiotemporal response and trajectories of forest dynamics at different scales under climate change, harvesting, and land-use disturbances in the near future.
Methods
We simulated forest landscape dynamics by integrating a forest landscape model (LANDIS-II), an ecosystem model (PnET-II), and a land change model (CA-Markov) for 2010 to 2050. We identified changes in forest composition, aboveground biomass, and landscape patterns under individual and integrated scenarios, including a control scenario, climate change, harvesting, and land-use change for tree species, ecoregions, and forest types.
Results
For forest composition, the forest area continued to increase, and coniferous forests increased approximately 3.7 times that of broad-leaved forests. Harvesting reduced aboveground biomass, with a reduction of 30.3% in comparison to the control scenario. The integrated disturbances showed a greater impact on the forest landscape. Landscape fragmentation increased, showing that the patch density increased by 52.3% (control scenario), 46.2% (climate change), 118.4% (harvest), 55.0% (land use change) and 139.5% (integrated scenarios), respectively.
Conclusions
Our results suggest that climate change will contribute to forest growth, especially for coniferous forests. Harvesting will reduce forest area and aboveground biomass. The interaction between human activities and climate change contributes to diminished forest expansion and increased landscape fragmentation.
The global human population is projected to increase from 7.2 billion in 2013 to 9.6 billion in 2050 (United Nations Department of Economic and Social Affairs 2013). Increasing numbers of people and households are placing escalating pressure on global forests through demand for wood and other forest resources. In addition, the geographic expansion of human populations results in deforestation and subsequent conversion of forested areas to agricultural and developed land uses. These human impacts interact with changing climate and natural forest disturbances such as wildfires and insect outbreaks to create a complex system of interacting processes that drive forest dynamics and affect ecosystem services such as timber production, wildlife habitat water quality, and carbon sequestration. Spatial simulation modeling of forest landscape change is an important technique for exploring the potential outcomes of these interactions over large areas and long time periods. Landscape simulation models are widely used for reconstructing historical landscape patterns driven by natural disturbance regimes, projecting future landscape trajectories under alternative forest management scenarios, and conducting simulation experiments to examine how multiple processes and their interactions affect landscape patterns and trajectories of change (Wimberly et al. 2012).
High-resolution analysis of macroscopic charcoal in sediment cores from Little Lake was used to reconstruct the fire history of the last 9000 years. Variations in sediment magnetism were examined to detect changes in allochthonous sedimentation associated with past fire occurrence. Fire intervals from ca. 9000 to 6850 calendar years BP averaged 110 +/- 20 years, when the climate was warmer and drier than today and xerophytic vegetation dominated. From ca. 6850 to 2750 calendar years BP the mean fire interval lengthened to 160 +/- 20 years in conjunction with the onset of cool humid conditions. Fire-sensitive species, such as Thuja plicata Donn ex D. Don, Tsuga heterophylla (Raf.) Sarg., and Picea sitchensis (Bong.) Carr., increased in abundance. At ca. 4000 calendar years BP, increases in allochthonous sedimentation increased the delivery of secondary charcoal to the site. From ca. 2750 calendar years BP to present, the mean fire interval increased to 230 +/- 30 years as cool humid conditions and mesophytic taxa prevailed. The Little Lake record suggests that fire frequency has varied continuously on millennial time scales as a result of climate change and the present-day fire regime has been present for no more than 1000 years.
The range and variation of historical landscape dynamics could provide a useful reference for designing fuel treatments on today's landscapes. Simulation modeling is a vehicle that can be used to estimate the range of conditions experienced on historical landscapes. A landscape fire succession model called LANDSUMv4 (LANDscape SUccession Model version 4.0) is presented here as a tool for estimating historical range and variation (HRV) of landscape characteristics. The model simulates fire and succession on fine scale landscapes for land management applications. It simulates vegetation development as a deterministic process by changing the species composition and stand structure assigned to a polygon. Disturbance initiation is modeled stochastically and disturbance effects are based on the current vegetation conditions of the polygon. Details of all model algorithms are discussed and the model is demonstrated for two applications. Results of an extensive sensitivity and model behavior analysis are also presented.
To understand the potential effects of forest policies on sustaining biological diversity at broad scales, we used spatial simulation models to evaluate current and potential future habitat availability over 100 yr for three focal species: Pacific Fisher (Martes pennanti), Pileated Woodpecker (Dryocopus pileatus), and Warbling Vireo (Vireo gilvus). The habitats of these species represent a broad range of spatial scales and forest types. Area of habitat for fishers and Pileated Woodpeckers is predicted to increase over time under curreat forest land management policies. Habitat for Warbling Vireos is predicted to decline. These patterns are consistent with past analyses that predicted declines in diverse early successional foersts and hardwood forests and increases in late-successional forests under current and two alternative policies. Land ownership influenced the spatial arrangement of habitat for all three focal species. Public lands subsidized habitat for wide-ranging species on adjacent private lands. A land use policy that required greater green tree retention on private lands seemed to result in modest increases in habitat quality over 100 yr for Pileated Woodpeckers. Thinning of plantations on federal lands had little effect on these focal species. Policy analyses such as these highlight incongruities between historic habitat patterns and contemporary spatial and temporal scales of habitat in managed landscapes. This information can be used to assess risks and inform the policy debates surrounding biodiversity conservation.
