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.     

Six principles for managing forests as ecologically sustainable ecosystems

Managing a landscape for its natural resources while attempting to ensure an ecologically sustainable future is a truly complex and challenging task. We present six general principles for sustainable forest landscape management derived from insights in an array of natural and commodity production ecosystems in south-eastern Australia but which are likely to have broad applicability to many forested ecosystems worldwide. These principles are: (1) Landscape management problems are typically underpinned by human-use drivers that over-commit natural resources and undermine the ecosystem services which support the replenishment of those resources. (2) Not all parts of a landscape are equal in their contribution to species persistence and ecological processes. Special steps are needed to secure the ecological integrity of these disproportionately important areas. (3) Managing connectivity is critical, but it is essential to determine what kind of connectivity is desirable, and for what species and processes. (4) Land use practices can produce spatial and temporal cumulative effects with negative impacts on biodiversity and ecological processes. (5) Land use decisions on the land sparing–land sharing spectrum are highly scale and context dependent. (6) Our understanding of landscape-scale processes is shaped by our conceptual model of the landscape. It is therefore important to check if a given mental model is appropriate for a given landscape and the species or ecological processes of concern. These six principles should not be applied uncritically. Rather, it is best to treat them as a checklist of considerations that will help guide our thinking about landscape change, so that we can orient toward more ecologically sustainable landscape management.     

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.     

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.     

Landscape dynamics in crown fire ecosystems

Crown fires create broad-scale patterns in vegetation by producing a patch mosaic of stand age classes, but the spread and behavior of crown fires also may be constrained by spatial patterns in terrain and fuels across the landscape. In this review, we address the implications of landscape heterogeneity for crown fire behavior and the ecological effects of crown fires over large areas. We suggest that fine-scale mechanisms of fire spread can be extrapolated to make broad-scale predictions of landscape pattern by coupling the knowledge obtained from mechanistic and empirical fire behavior models with spatially-explicit probabilistic models of fire spread. Climatic conditions exert a dominant control over crown fire behavior and spread, but topographic and physiographic features in the landscape and the spatial arrangement and types of fuels have a strong influence on fire spread, especially when burning conditions (e.g., fuel moisture and wind) are not extreme. General trends in crown fire regimes and stand age class distributions can be observed across continental, latitudinal, and elevational gradients. Crown fires are more frequent in regions having more frequent and/or severe droughts, and younger stands tend to dominate these landscapes. Landscapes dominated by crown fires appear to be nonequilibrium systems. This nonequilibrium condition presents a significant challenge to land managers, particularly when the implications of potential changes in the global climate are considered. Potential changes in the global climate may alter not only the frequency of crown fires but also their severity. Crown fires rarely consume the entire forest, and the spatial heterogeneity of burn severity patterns creates a wide range of local effects and is likely to influence plant reestablishment as well as many other ecological processes. Increased knowledge of ecological processes at regional scales and the effects of landscape pattern on fire dynamics should provide insight into our understanding of the behavior and consequences of crown fires.     

Impacts of selective logging on tree diversity across a rainforest landscape: the importance of spatial scale

Selective logging of tropical forests imposes spatial pattern on the landscape by creating a mosaic of patches affected by different intensities of disturbance. To understand the ecological impacts of selective logging it is therefore necessary to explore how patterns of tree species composition are affected by this patchy disturbance. This study examines the impacts of selective logging on species composition and spatial patterns of vegetation structure and tree diversity in Sabah, Borneo. We compare tree diversity between logged and unlogged forest at three scales: species richness within plots, species turnover among plots, and total species richness and composition of plots combined. Logging had no effect on tree diversity measured at the smallest scale. Logged forest had a greater rate of species turnover with distance, so at a large spatial scale it supported more tree species than the relatively homogeneous unlogged area. Tree species composition also differed significantly between the two types of forest, with more small dipterocarps and large pioneers in logged forest, and more large dipterocarps in unlogged forest. Our results emphasize the importance of sampling at a sufficiently large scale to represent patterns of biodiversity within tropical forest landscapes. Large areas of production forest in SE Asia are threatened with conversion to commercial crops; our findings show that selectively logged forest can retain considerable conservation value.     

Gradient modeling of conifer species using random forests

Landscape ecology often adopts a patch mosaic model of ecological patterns. However, many ecological attributes are inherently continuous and classification of species composition into vegetation communities and discrete patches provides an overly simplistic view of the landscape. If one adopts a niche-based, individualistic concept of biotic communities then it may often be more appropriate to represent vegetation patterns as continuous measures of site suitability or probability of occupancy, rather than the traditional abstraction into categorical community types represented in a mosaic of discrete patches. The goal of this paper is to demonstrate the high effectiveness of species-level, pixel scale prediction of species occupancy as a continuous landscape variable, as an alternative to traditional classified community type vegetation maps. We use a Random Forests ensemble learning approach to predict site-level probability of occurrence for four conifer species based on climatic, topographic and spectral predictor variables across a 3,883 km² landscape in northern Idaho, USA. Our method uses a new permutated sample-downscaling approach to equalize sample sizes in the presence and absence classes, a model selection method to optimize parsimony, and independent validation using prediction to 10% bootstrap data withhold. The models exhibited very high accuracy, with AUC and kappa values over 0.86 and 0.95, respectively, for all four species. The spatial predictions produced by the models will be of great use to managers and scientists, as they provide vastly more accurate spatial depiction of vegetation structure across this landscape than has previously been provided by traditional categorical classified community type maps.     

The consequences of interactions between dispersal distance and resolution of habitat clustering for dispersal success

Habitat clustering results from processes of habitat loss and fragmentation, which operate at different resolutions and with different intensities, e.g. forest clear-cutting or thinning. Individual movements also vary at different spatial scales according to landscape structure and species dispersal strategies. Disentangling the relative impact of habitat loss and fragmentation on the long-term survival of species requires understanding how clustering at one resolution interacts with the amount of habitat, dispersal distance and clustering at other resolutions, to affect dispersal success. We addressed this problem by quantifying the magnitude of these interactions and how they were affected by the intensity of habitat removal. Individual-based simulations were conducted on artificial fractal landscapes where the intensity of habitat removal and the amount of clustering were varied independently at two nested resolutions, while the total amount of habitat in the landscape was controlled for. We show that the way the amount of habitat, the dispersal distance and the amount of clustering affect dispersal success depends on the resolution at which habitat clustering occurs, the intensity at which habitat is removed, and the strength of habitat selection. Our findings highlight: (a) the importance of explicitly considering scale-dependent biological responses to landscape change; and (b) the need to identify the appropriate scale at which to manage fragmentation, thus avoiding mismatches between the scale of ecological processes and the scale of management.     

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.     

Multi-scale responses of bird species to tree cover and development in an urbanizing landscape

Landscape change is an ongoing process for even the most established landscapes, especially in context to urban intensification and growth. As urbanization increases over the next century, supporting bird species’ populations within urbanizing areas remains an important conservation challenge. Fundamental elements of the biophysical structure of urban environments in which bird species likely respond include tree cover and human infrastructure. We broadly examine how tree cover and urban development structure bird species distributions along the urban-rural gradient across multiple spatial scales. We established a regional sampling design within the Oak Openings Region of northwestern, Ohio, USA, to survey bird species distributions across an extensive urbanization gradient. Through occupancy modeling, we obtained standardized effects of bird species response to local and landscape-scale predictors and found that landscape tree cover influenced the most species, followed by landscape impervious surface, local building density, and local tree cover. We found that responses varied according to habitat affiliation and migratory distance of individual bird species. Distributions of short-distance, edge habitat species located towards the rural end of the gradient were explained primarily by low levels of urbanization and potential vegetative and supplemental resources associated with these areas, while forest species distributions were primarily related to increasing landscape tree cover. Our findings accentuate the importance of scale relative to urbanization and help target where potential actions may arise to benefit bird diversity. Management will likely need to be implemented by municipal governments and agencies to promote tree cover at landscape scale, followed by residential land management education for private landowners. These approaches will be vital in sustaining biodiversity in urbanizing landscapes as urban growth expands over the next century.     

Small-scale effects of historical land use and topography on post-cultural tree species composition in an Alpine valley in southern Switzerland

Investigations of spatial patterns in forest tree species composition are essential in the understanding of landscape dynamics, especially in areas of land-use change. The specific environmental factors controlling the present patterns, however, vary with the scale of observation. In this study we estimated abundance of adult trees and tree regeneration in a Southern Alpine valley in Ticino, Switzerland. We hypothesized that, at the present scale, spatial pattern of post-cultural tree species does not primarily depend on topographic features but responds instead to small-scale variation in historical land use. We used multivariate regression trees to relate species abundances to environmental variables. Species matrices were comprised of single tree species abundance as well as species groups. Groups were formed according to common ecological species requirements with respect to shade tolerance, soil moisture and soil nutrients. Though species variance could only be partially explained, a clear ranking in the relative importance of environmental variables emerged. Tree basal area of formerly cultivated Castanea sativa (Mill.) was the most important factor accounting for up to 50% of species’ variation. Influence of topographic attributes was minor, restricted to profile curvature, and partly contradictory in response. Our results suggest the importance of biotic factors and soil properties for small-scale variation in tree species composition and need for further investigations in the study area on the ecological requirements of tree species in the early growing stage.     

Linkages beyond borders: targeting spatial processes in fragmented urban landscapes

Management of ecosystems often focuses on specific species chosen for their habitat demand, public appeal, or levels of threat. We propose a complementary framework for choosing focal species, the mobile link concept, which allows managers to focus on spatial processes and deal with multi-scale ecological dynamics. Spatial processes are important for three reasons: maintenance, re-organization, and restoration of ecological values. We illustrate the framework with a case study of the Eurasian Jay, a mobile link species of importance for the oak forest regeneration in the Stockholm National Urban Park, Sweden, and its surroundings. The case study concludes with a conceptual model for how the framework can be applied in management. The model is based on a review of published data complemented with a seed predation experiment and mapping of Jay territories to reduce the risk of applying non-urban site-specific information in an urban setting. Our case study shows that the mobile link approach has several advantages: (1) Reducing the vulnerability of ecological functions to disturbances and fluctuations in resources allocated to management, (2) Reducing management costs by maintaining natural processes, and (3) Maintaining gene flow and genetic diversity at a landscape level. We argue that management that includes mobile link organisms is an important step towards the prevention of ecosystem degradation and biodiversity loss in increasingly fragmented landscapes. Identifying and managing mobile links is a way to align management with the ecologically relevant scales in any landscape.     

Modeling the spatially dynamic distribution of humans in the Oregon (USA) Coast Range

A common approach to land use change analyses in multidisciplinary landscape-level studies is to delineate discrete forest and non-forest or urban and non-urban land use categories to serve as inputs into sets of integrated sub-models describing socioeconomic and ecological processes. Such discrete land use categories, however, may be inappropriate when the socioeconomic and ecological processes under study are sensitive to a range of human habitation. In this paper, we characterize the spatial dynamic distribution of humans throughout the forest landscape of western Oregon (USA). We develop an empirical model describing the spatial distribution and rate of change in historic building densities as a function of a gravity index of development pressure, existing building densities, slope, elevation, and existing land use zoning. We use the empirical model to project changes in building densities that are applied to a 1995 base map of building density to describe future spatial distributions of buildings over time. The projected building density maps serve as inputs into a multidisciplinary landscape-level analysis of socioeconomic and ecological processes in Oregon's Coast Range Mountains. This revised version was published online in July 2006 with corrections to the Cover Date.     

The Importance of Spatial Scale in Habitat Models: Capercaillie in the Swiss Alps

The role of scale in ecology is widely recognized as being of vital importance for understanding ecological patterns and processes. The capercaillie (Tetrao urogallus) is a forest grouse species with large spatial requirements and highly specialized habitat preferences. Habitat models at the forest stand scale can only partly explain capercaillie occurrence, and some studies at the landscape scale have emphasized the role of large-scale effects. We hypothesized that both the ability of single variables and multivariate models to explain capercaillie occurrence would vary with the spatial scale of the analysis. To test this hypothesis, we varied the grain size of our analysis from 1 to just over 1100 hectares and built univariate and multivariate habitat suitability models for capercaillie in the Swiss Alps. The variance explained by the univariate models was found to vary among the predictors and with spatial scale. Within the multivariate models, the best single-scale model (using all predictor variables at the same scale) worked at a scale equivalent to a small annual home range. The multi-scale model, in which each predictor variable was entered at the scale at which it had performed best in the univariate model, did slightly better than the best single-scale model. Our results confirm that habitat variables should be included at different spatial scales when species-habitat relationships are investigated.     

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.

     

Landscape structure effects on carabid beetles spatial patterns in western France

Analysis of carabids spatial distribution in a hedgerow network landscape in western France, pinpoints the role of the landscape among other levels of ecological organization.Dispersion of forest species differs among core forest species, peninsula forest species and corridor forest species. Abundance of forest carabid species in a particular hedgerow is related to the positive effect of a dense herbaceous layer and the presence of a tree layer which is enhanced by the presence of two parallel hedgerows, especially along lanes.At the landscape level distance from the largest forest determines abundance of forest species within the first kilometer out of it. Beyond that, abundance is independent of distance from the source forest and the discriminant ecological factors are: hedgerow structure, presence of lanes bordered by two hedgerows.     

Spatial,temporal, and life history assumptions influence consistency of landscape effects on species distributions

Models describing relationships between landscape features and species distribution patterns often display inter-study inconsistencies. Identifying factors contributing to these inconsistencies is a vital step in clarifying the ecological importance of landscape features and synthesizing an effective knowledge base for use in conservation contexts. We examined the influence of several spatial, temporal, and life history assumptions on the outcomes of distribution versus landscape models (DLMs) relating wetland bird communities at 29 Massachusetts (USA) sites to independent urbanization, wetland, forest, and agricultural landscape gradients. We considered a bird specialization index as well as obligate and facultative species richness as response variables. Landscape gradients were quantified at 10 landscape extents (0–1000 m in 100 m increments) and three time periods (1971, 1985, 2005). Univariate models indicated that our specialization index showed: (1) the strongest response to landscape gradients at small extents (200 m); (2) a negative, threshold response to urbanization was superior to a linear fit; and (3) no evidence of time-lagged effects of landscape change. Interestingly, the form of our model (i.e. linear versus threshold) influenced the extent at which strongest effects were detected. Multivariate models relating the specialization index as well as obligate and facultative species richness to landscape gradients showed evidence of annual variability (i.e. composition, parameter estimates, and variability explained) that did not depend upon an organism’s degree of specialization. Our results provide evidence that violations of common assumptions (e.g. selection of appropriate extent, lack of time-lagged effects, etc.) can impact the outcome of DLMs, which could lead to inter-study inconsistencies.     

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.     

When relationships estimated in the past cannot be used to predict the future: using mechanistic models to predict landscape ecological dynamics in a changing world

Researchers and natural resource managers need predictions of how multiple global changes (e.g., climate change, rising levels of air pollutants, exotic invasions) will affect landscape composition and ecosystem function. Ecological predictive models used for this purpose are constructed using either a mechanistic (process-based) or a phenomenological (empirical) approach, or combination. Given the accelerating pace of global changes, it is becoming increasingly difficult to trust future projections made by phenomenological models estimated under past conditions. Using forest landscape models as an example, I review current modeling approaches and propose principles for developing the next generation of landscape models. First, modelers should increase the use of mechanistic components based on appropriately scaled “first principles” even though such an approach is not without cost and limitations. Second, the interaction of processes within a model should be designed to minimize a priori constraints on process interactions and mimic how interactions play out in real life. Third, when a model is expected to make accurate projections of future system states it must include all of the major ecological processes that structure the system. A completely mechanistic approach to the molecular level is not tractable or desirable at landscape scales. I submit that the best solution is to blend mechanistic and phenomenological approaches in a way that maximizes the use of mechanisms where novel driver conditions are expected while keeping the model tractable. There may be other ways. I challenge landscape ecosystem modelers to seek new ways to make their models more robust to the multiple global changes occurring today.