Sensitivity of ecosystem goods and services projections of a forest landscape model to initialization data

Projections of indicators of forest ecosystem goods and services (EGS) based on process-based landscape models are critical for adapting forest management to climate change. However, the scarcity of fine-grained, spatially explicit forest data means that initializing these models is both a challenge and a source of uncertainty. To test how different initialization approaches influence the simulation of forest dynamics and EGS indicators we initialized the forest landscape model LandClim with fine resolution empirical data, coarse empirical data, and simulation-derived data, and evaluated the results at three spatial scales (stand, management area and landscape). Simulations were performed for a spruce (Picea abies) dominated landscape in the Black Forest, Germany, under current climate and a climate change scenario. We found that long-term (>150 years) projections are robust to initialization uncertainty. In contrast, shorter-term projections are sensitive to initialization uncertainty, with sensitivity increasing when EGS are assessed at smaller spatial scales, and when the EGS indicators depend on the spatial distribution of individual species. EGS dynamics are strongly influenced by interactions between the density, species composition, and age structure of initialized forests and simulated forest management. If EGS dynamics are strongly influenced by climate change, such as when climate change induces mortality in drought-sensitive species, some of the initialization uncertainty can be masked. We advocate for initializing landscape models with fine-grained data in applications that focus on spatial management problems in heterogeneous landscapes, and stress that the scale of analysis must be in accordance with the accuracy that is warranted by the initialization data.     

Spatial spread of an alien tree species in a heterogeneous forest landscape: a spatially realistic simulation model

The effect of environmental heterogeneity on spatial spread of invasive species has received little attention in the literature. Altering landscape heterogeneity may be a suitable strategy to control invaders in man-made landscapes. We use a population-based, spatially realistic matrix model to explore mechanisms underlying the observed invasion patterns of an alien tree species, Prunus serotina Ehrh., in a heterogeneous managed forest. By altering several parameters in the simulation, we test for various hypotheses regarding the role of several mechanisms on invasion dynamics, including spatial heterogeneity, seed dispersers, site of first introduction, large-scale natural disturbances, and forest management. We observe that landscape heterogeneity makes the invasion highly directional resulting from two mechanisms: (1) irregular jumps, which occur rarely via long-distance dispersers and create new founder populations in distant suitable areas, and (2) regular, continuous diffusion toward adjacent cells via short- and mid-distance vectors. At the landscape scale, spatial heterogeneity increases the invasion speed but decreases the final invasion extent. Hence, natural disturbances (such as severe storms) appear to facilitate invasion spread, while forest management can have contrasting effects such as decreasing invasibility at the stand scale by increasing the proportion of light interception at the canopy level. The site of initial introduction influences the invasion process but without altering the final outcome. Our model represents the real landscape and incorporates the range of dispersal modes, making it a powerful tool to explore the interactions between environmental heterogeneity and invasion dynamics, as well as for managing plant invaders. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Multi-scale predictive habitat suitability modeling based on hierarchically delineated patches: an example for yellow-billed cuckoos nesting in riparian forests,California, USA

The discipline of landscape ecology recognizes the importance of measuring habitat suitability variables at spatial scales relevant to specific organisms. This paper uses a novel multi-scale hierarchical patch delineation method, PatchMorph, to measure landscape patch characteristics at two distinct spatial scales and statistically relate them to the presence of state-listed endangered yellow-billed cuckoos (Coccyzus americanus occidentalis) nesting in forest patches along the Sacramento River, California, USA. The landscape patch characteristics calculated were: patch thickness, area of cottonwood forest, area of riparian scrub, area of other mixed riparian forest, and total patch area. A third, regional spatial variable, delineating the north and south portions of study area was also analyzed for the effect of regional processes. Using field surveys, the landscape characteristics were related to patch occupancy by yellow-billed cuckoos. The area of cottonwood forest measured at the finest spatial scale of patches was found to be the most important factor determining yellow-billed cuckoo presence in the forest patches, while no patch characteristics at the larger scale of habitat patches were important. The regional spatial variable was important in two of the three analysis techniques. Model validation using an independent data set of surveys (conducted 1987–1990) found 76–82% model accuracy for all the statistical techniques used. Our results show that the spatial scale at which habitat characteristics are measured influences the suitability of forest patches. This multi-scale patch and model selection approach to habitat suitability analysis can readily be generalized for use with other organisms and systems.     

Disturbance propagation by bark beetles as an episodic landscape phenomenon

Landscapes are the resultant of ecological processes and events operating on many different space-time scales. Large scale disturbance is recognized as a major influence on landscape patterns, but the impact of small scale events is often overlooked. We develop an hierarchical framework to relate lightning and bark beetle population dynamics to the southern pine forest landscape using the concepts of disturbance propagation and amplification. The low level lightning disturbance can be propagated to the landscape level when weather and forest stand structure facilitate bark beetle epidemics. We identify epidemics as biotically-driven episodes that alter landscape structure. The concept of the landscape as the spatial dimension of these episodes is represented in a conceptual model linking insect-host and landscape mosaic interactions.     

Landscape phenology: an integrative approach to seasonal vegetation dynamics

This brief report addresses the theory and methodology of landscape phenology (LP), along with synopsis of a case study conducted in the northern Wisconsin temperate mixed forest. LP engages questions related to ecosystem phenology, landscape genetics, and vegetation change science across multiple scales, which have rarely been addressed by existing studies. Intensive in situ observations, remote sensing data, and spatiotemporal analysis are employed for understanding patterns and processes within the complexity of seasonal landscape dynamics. A hierarchical upscaling approach is also introduced. Results from the case study suggest that plot-scale phenology lacks spatial autocorrelation and varies individualistically, with genetic heterogeneity overriding small microenvironmental gradients. However, at the landscape level, forest phenology responds coherently to weather fluctuations. The resultant LP index confirms the relative reliability of moderate resolution imaging spectroradiometer (MODIS)-based land surface phenology (LSP). Due to technological advancement in spatial data acquisition and analysis, LP has the ability to connect conventional plant phenology studies back to their intricate ecological context, and provides a new approach to validating coarse-scale monitoring and modeling of LSP and other seasonal ecosystem processes.     

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.     

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.     

Temporal (1958–1993) and spatial patterns of land use changes in Haut-Saint-Laurent (Quebec, Canada) and their relation to landscape physical attributes

In the last few years, landscape researchers have sought to understand temporal and spatial patterns of landscape changes in order to develop comprehensive models of land cover dynamics. To do so, most studies have used similar methods to quantify structural patterns, usually by comparing various landscape structural indices through time. Whereas the necessity for complementary approaches which might provide insights into landscape dynamics at some finer scale relevant to local managers has been expressed, few studies have proposed alternative methodologies. Moreover, the important relationship between the physical constraints of the landscape and land use dynamics has been seldom emphasized. Here we propose a methodological outline which was applied to the study of a rural landscape of Southern Quebec, Canada, to detect spatial and temporal (1958 to 1993) patterns of land cover changes at field, patch and landscape level. We then relate these patterns to the underlying physical structure of landscape elements using GIS and canonical correspondence analyses. We use the different geomorphological deposit types as stable discriminant factors which may constrain land use.Canonical correspondence analyses showed relations of land use and land use changes to the physical attributes of the landscape elements, whereas spatial analyses revealed very dynamic patterns at finer spatial and temporal scales. They highlighted the fact that not only the physical attributes of the landscape elements but also their spatial configuration were important determinants of land use dynamics in this area. Thus more land use changes occurred at the boundary between geomorphological deposit types than in any other locations. This trend is apparent for specific small-size changes (e.g. forest to crop), but not for the large-size ones (e.g. abandoned land to forest). Although land use changes are triggered by socioeconomic forces in this area, these changes are nevertheless constrained by the underlying physical landscape structure. A thorough comprehension of historical changes will enhance our capability to predict future landscape dynamics and devise more effective landscape management strategies.     

Combining holding-level economic goals with spatial landscape-level goals in the planning of multiple ownership forestry

In Finland, management of biological diversity at the landscape level is complicated by the relatively small size of the holdings. To alleviate this problem, this study presents a hierarchical planning model that aims at combining spatial landscape-level ecological goals with holding-level owner-specific goals. The influence of ecological objectives extends across holding borders, but their impact is greatest in areas where they are least in conflict with the owners goals. This feature, which results in minimum losses to individual landowners, can be called ecological efficiency. In the case study, the ecological objective was to cluster the breeding and foraging areas of flying squirrel (Pteromys volans). Other sets of objectives were related to individual holdings according to the various preferences of the forest owners. The forest plan produced by the presented planning model was compared with two other forest plans: 1) a combination of independent forest holding level plans, which were assumed to represent the outcome of the current planning tradition, and 2) an area-level plan, where the holding borders and holding-specific objectives were not taken into account. The same objective variables and objective weights were used in all plans. All the plans were produced for six planning areas (ranging from 404.6 to 984.9 ha) and 110 forest holdings (ranging from 0.6 to 449.8 ha) within these areas. The case-study results were promising: with the model presented here, the spatial structure of flying squirrel breeding and foraging areas could be improved with only minor losses in holding-level objectives. The spatial structure of the landscape after the 60-year planning period was very close to the area-level plan. This outcome was made possible by synchronizing the treatment proposals across forest-holding borders. The outcome of the model seems promising also from the practical standpoint: because the variation in the objectives of forest owners is efficiently taken into account in optimization, only rarely do the solutions suggest that the holding-level targets be compromised.This revised version was published online in May 2005 with corrections to the Cover Date.     

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.     

The protean relationship between boreal forest landscape structure and red squirrel distribution at multiple spatial scales

This paper investigates two fundamental questions in landscape ecology: what influence does landscape context, or the composition of the matrix, have on an animals’ response to landscape structure, and how does this relationship extrapolate between landscapes? We investigate how the distribution of North American red squirrels (Tamiasciurus hudsonicus) in the boreal mixedwood forest is influenced by anthropogenically (forest harvest) and naturally (forest fire) derived landscape structure. We studied the presence and absence of red squirrels over two years in three landscape types: one managed for timber harvest, one recently burned by wildfire, and a third unburned unmanaged landscape. Landscape composition and configuration, measured at several spatial scales, predicted red squirrel’s distribution in all three landscapes, but the significant landscape variables changed across spatial scales, across time, and across landscapes. These findings emphasize the variability in landscape structure/animal distribution relationships, and enforce the need to link pattern-finding studies, such as this one, with searches for the mechanisms behind the observed pattern.     

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.

     

Associations between soil carbon and ecological landscape variables at escalating spatial scales in Florida,USA

The spatial distribution of soil carbon (C) is controlled by ecological processes that evolve and interact over a range of spatial scales across the landscape. The relationships between hydrologic and biotic processes and soil C patterns and spatial behavior are still poorly understood. Our objectives were to (i) identify the appropriate spatial scale to observe soil total C (TC) in a subtropical landscape with pronounced hydrologic and biotic variation, and (ii) investigate the spatial behavior and relationships between TC and ecological landscape variables which aggregate various hydrologic and biotic processes. The study was conducted in Florida, USA, characterized by extreme hydrologic (poorly to excessively drained soils), and vegetation/land use gradients ranging from natural uplands and wetlands to intensively managed forest, agricultural, and urban systems. We used semivariogram and landscape indices to compare the spatial dependence structures of TC and 19 ecological landscape variables, identifying similarities and establishing pattern–process relationships. Soil, hydrologic, and biotic ecological variables mirrored the spatial behavior of TC at fine (few kilometers), and coarse (hundreds of kilometers) spatial scales. Specifically, soil available water capacity resembled the spatial dependence structure of TC at escalating scales, supporting a multi-scale soil hydrology-soil C process–pattern relationship in Florida. Our findings suggest two appropriate scales to observe TC, one at a short range (autocorrelation range of 5.6 km), representing local soil-landscape variation, and another at a longer range (119 km), accounting for regional variation. Moreover, our results provide further guidance to measure ecological variables influencing C dynamics.     

Scaling Local Species-habitat Relations to the Larger Landscape with a Hierarchical Spatial Count Model

Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species.     

Modeling multiscale effects of light limitations and edge-induced mortality on carbon stores in forest landscapes

Analyses of carbon (C) dynamics at broad scales usually do not consider spatial interactions. The assumption is that C dynamics can be modeled within homogenous (i.e., even-aged) patches and then summed to predict broad-scale dynamics (an additive approach). The goal of this paper is to elucidate the scales over which this additive approach is sufficient to explain observed C dynamics at broad scales. We define emergent behaviors (vs. emergent properties) as those behaviors that cannot be predicted solely from the additive properties of units at a finer scale. We used a forest process model to check for possible emergent behaviors due to pattern-process interactions at multiple levels, from the patch to the landscape. Specifically, using artificial forest landscapes with various spatial structures, we estimated the relative effects of edge-induced, tree mortality (mainly due to wind) and light limitations on C dynamics. Emergent behaviors were observed at all levels examined, indicating that emergent behaviors did not cease as one proceeded from the patch to the landscape level, as we had expected. However, the magnitude of the emergent behaviors depended on the level of spatial interaction considered as well as the type and intensity of the processes included. In all simulations, interactions of light and wind processes resulted in significant emergent behaviors only when parameters controlling wind mortality were set to the highest levels observed in the literature. In one simulation, the magnitude of emergent behaviors differed among the landscapes, indicating that interactions among patches may not be accounted for by an additive correction for edge effects unless spatial interactions are addressed. The implication is that some C dynamics in fragmented landscapes may not be captured at broad-scales using an additive approach, whereas in other cases spatial interactions are small enough to be ignored.This revised version was published online in May 2005 with corrections to the Cover Date.     

Elasticity and loop analyses: tools for understanding forest landscape response to climatic change in spatial dynamic models

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.     

Mapping sources,sinks, and connectivity using a simulation model of northern spotted owls

Source-sink dynamics are an emergent property of complex species–landscape interactions. A better understanding of how human activities affect source-sink dynamics has the potential to inform and improve the management of species of conservation concern. Here we use a study of the northern spotted owl (Strix occidentalis caurina) to introduce new methods for quantifying source-sink dynamics that simultaneously describe the population-wide consequences of changes to landscape connectivity. Our spotted owl model is mechanistic, spatially-explicit, individual-based, and incorporates competition with barred owls (Strix varia). Our observations of spotted owl source-sink dynamics could not have been inferred solely from habitat quality, and were sensitive to landscape connectivity and the spatial sampling schemes employed by the model. We conclude that a clear understanding of source-sink dynamics can best be obtained from sampling simultaneously at multiple spatial scales. Our methodology is general, can be readily adapted to other systems, and will work with population models ranging from simple and low-parameter to complex and data-intensive.     

Old-growth forest landscape transitions from pre-European settlement to present

We conducted a multi-temporal spatial analysis of forest cover for a 9600 ha landscape in northern Wisconsin, U.S.A., using data from pre-European settlement (1860s), post-settlement (1931), and current (1989) periods. Using GIS we have shown forest landscape changes and trajectories that have been generally described in aggregate for the norther Great Lake States region. We created the pre-European settlement map from the witness tree data of the original federal General Land Office survey notes. The 1931 cover was produced from the Wisconsin Land Economic Inventory, and the 1989 cover map was based on color infrared photography. We used GIS to analyze 1) land area occupied by different forest types at different dates, 2) temporal transitions between dates and their driving proceses, and 3) successional trajectories with landforms and spatial associations of forest types. Over the 120 year period, forest cover has changed from a landscape dominated by old-growth hemlock (Tsuga canadensis) and hardwood forests (Acer saccharum, Betula alleghaniensis) to largely second-growth hardwoods and conifers. The former dominant hemlock is largely eliminated from the landscape. From 1860 to 1931, large-scale disturbances associated with logging were the dominant processes on the landscape. Early successional forest types covered much of the landscape by the 1930s. From 1931 to 1989, succession was the dominant process driving forest transitions as forest types succeeded to a diverse group of upland hardwood and conifer forest types. If successional trajectories continue, a more homogeneous landscape may develop comprised of both a northern hardwood type dominated by sugar maple, and a boreal conifer/hardwood forest.     

Influence of high-resolution data on the assessment of forest fragmentation

Context

Remote sensing has been a foundation of landscape ecology. The spatial resolution (pixel size) of remotely sensed land cover products has improved since the introduction of landscape ecology in the United States. Because patterns depend on spatial resolution, emerging improvements in the spatial resolution of land cover may lead to new insights about the scaling of landscape patterns.

Objective

We compared forest fragmentation measures derived from very high resolution (1 m²) data with the same measures derived from the commonly used (30 m?×??30 m; 900 m²) Landsat-based data.

Methods

We applied area-density scaling to binary (forest; non-forest) maps for both sources to derive source-specific estimates of dominant (density ≥?60%), interior (≥?90%), and intact (100%) forest.

Results

Switching from low- to high-resolution data produced statistical and geographic shifts in forest spatial patterns. Forest and non-forest features that were “invisible” at low resolution but identifiable at high resolution resulted in higher estimates of dominant and interior forest but lower estimates of intact forest from the high-resolution source. Overall, the high-resolution data detected more forest that was more contagiously distributed even at larger spatial scales.

Conclusion

We anticipate that improvements in the spatial resolution of remotely sensed land cover products will advance landscape ecology through re-interpretations of patterns and scaling, by fostering new landscape pattern measurements, and by testing new spatial pattern-ecological process hypotheses.