Integrating Landscape and Metapopulation Modeling Approaches: Viability of the Sharp-Tailed Grouse in a Dynamic Landscape

Abstract:  The lack of management experience at the landscape scale and the limited feasibility of experiments at this scale have increased the use of scenario modeling to analyze the effects of different management actions on focal species. However, current modeling approaches are poorly suited for the analysis of viability in dynamic landscapes. Demographic (e.g., metapopulation) models of species living in these landscapes do not incorporate the variability in spatial patterns of early successional habitats, and landscape models have not been linked to population viability models. We link a landscape model to a metapopulation model and demonstrate the use of this model by analyzing the effect of forest management options on the viability of the Sharp-tailed Grouse (  Tympanuchus phasianellus ) in the Pine Barrens region of northwestern Wisconsin (U.S.A.). This approach allows viability analysis based on landscape dynamics brought about by processes such as succession, disturbances, and silviculture. The landscape component of the model (LANDIS) predicts forest landscape dynamics in the form of a time series of raster maps. We combined these maps into a time series of patch structures, which formed the dynamic spatial structure of the metapopulation component (RAMAS). Our results showed that the viability of Sharp-tailed Grouse was sensitive to landscape dynamics and demographic variables such as fecundity and mortality. Ignoring the landscape dynamics gave overly optimistic results, and results based only on landscape dynamics (ignoring demography) lead to a different ranking of the management options than the ranking based on the more realistic model incorporating both landscape and demographic dynamics. Thus, models of species in dynamic landscapes must consider habitat and population dynamics simultaneously.     

LANDIS and forest landscape models

This paper provides contextual documentation of the LANDIS model development to provide a framework for the other papers in this special issue. The LANDIS model of forest landscape disturbance and succession was developed since the early 1990s as a research and management tool that optimizes the possible landscape extent (100 s ha to 1000 s km²), while providing mechanistic detail adequate for a broad range of potential problems. LANDIS is a raster model, and operates on landscapes mapped as cells, containing tree species age classes. Spatial processes, such as seed dispersal, and disturbances such as fire, wind, and harvesting can occur. LANDIS development benefited from the modelling and research progress of the 1960s to the1980s, including the growth of landscape ecology during the 1980s. In the past decade the model has been used by colleagues across North America, as well as in Europe and China. This has been useful to those not able to undertake the cost and effort of developing their own model, and it has provided a growing diverse set of test landscapes for the model. These areas include temperate, southern, and boreal forests of eastern North America, to montane and boreal western forests, coastal California forest and shrub systems, boreal Finnish forests, and montane forests in Switzerland and northeastern China. The LANDIS model continues to be refined and developed. Papers in this special issue document recent work. Future goals include integration within a larger land use change model, and applications to landscape and regional global change projection based on newly incorporated biomass and carbon dynamics.     

Examining the effects of alternative management strategies on landscape-scale forest patterns in northeastern Minnesota using LANDIS

Spatial modeling of forest patterns can provide information on the potential impact of various management strategies on large landscapes over long time frames. We used LANDIS, a stochastic, spatially-explicit, ecological landscape model to simulate 120 years of forest change on the Nashwauk Uplands, a 328,000 ha landscape in northeastern Minnesota that lies in the transition between boreal and temperate forests. We ran several forest management scenarios including current harvesting practices, no harvests, varied rotation ages, varied clearcut sizes, clustered clearcuts, and landowner coordination. We examined the effects of each scenario on spatial patterns of forests by covertype, age class, and mean and distribution of patch sizes. All scenarios reveal an increase in the spruce-fir (Picea-Abies) covertype relative to the economically paramount aspen-birch (Populus-Betula) covertype. Our results also show that most covertypes occur in mostly small patches <5 ha in size and the ability of management to affect patch size is limited by the highly varied physiography and landuse patterns on the landscape. However, coordination among landowners, larger clearcuts, and clustered clearcuts were all predicted to increase habitat diversity by creating some larger patches and older forest patches. These three scenarios along with the no harvest scenario also create more old forest than current harvesting practices, by concentrating harvesting on some portion of the landscape. The no harvest scenario retained large, fire-regenerated aspen-birch patches. Harvests fragment large aspen-birch patches by changing the age structure and releasing the shade-tolerant understory species. More sapling forest, and larger sapling patches resulted from the shortened rotation scenario.     

Landscape history, fragmentation, and patch occupancy: models for a forest bird with limited dispersal.

We developed and tested patch occupancy models for an endemic understory bird with limited dispersal ability, the Chucao Tapaculo (Scelorchilus rubecula), in two South American temperate rain forest landscapes that differed in levels and duration of forest loss. We assessed cover changes since 1961 in each landscape and surveyed patches for Chucao Tapaculo occupancy. We then developed incidence-based predictive models independently for each landscape and tested each model reciprocally in the alternative study area. We thereby assessed the domain of model applicability and identified those predictor variables with general effects and those that varied between the two landscapes. The two models were consistent regarding variable selection, and predictive accuracy of each model was high in the landscape where training data were collected. However, the models differed substantially in the magnitudes of effects related to patch size, with larger unoccupied patches observed in the landscape with the more advanced stage of fragmentation. Due to this discrepancy, each model performed poorly when applied to the alternative landscape, potentially reflecting the contrasting stages of habitat loss. Although it was impossible to dissociate effects of level and duration of forest loss, we viewed the landscapes as representing two extremes along a continuum of fragmentation, providing insights into potential trajectories for portions of the biome where deforestation is occurring. Further, our data suggest that static equilibrium models developed from distribution patterns in recently fragmented landscapes may overestimate persistence when used as a forecasting tool, or when extrapolated to alternative landscapes where fragmentation is more advanced. Thus, we suggest that landscapes used as standards for model building should be selected with caution. We recommend that distribution patterns be obtained from landscapes where fragmentation is advanced, preferably with histories of fragmentation long enough that time-delayed extinctions already would have occurred.     

Wildfire, landscape diversity and the Drossel-Schwabl model

How simple can a model be that still captures essential aspects of wildfire ecosystems at large spatial and temporal scales? The Drossel-Schwabl model (DSM) is a metaphorical forest-fire model developed to reproduce only one pattern of real systems: a frequency distribution of fire sizes resembling a power law. Consequently, and because it appears oversimplified, it remains unclear what bearings the DSM has in reality. Here, we test whether the DSM is capable of reproducing a pattern that was not considered in its design, the hump-shaped relation between the diversity of succession stages and average annual area burnt. We found that the model, once reformulated to represent succession, produces realistic landscape diversity patterns. We investigated four succession scenarios of forest-fire ecosystems in the USA and Canada. In all scenarios, landscape diversity is highest at an intermediate average annual area burnt as predicted by the intermediate disturbance hypothesis. These results show that a model based solely on the dynamics of the fuel mosaic has surprisingly high predictive power with regard to observed statistical properties of wildfire systems at large spatial scales. Parsimonious models, such as the DSM can be used as starting points for systematic development of more structurally realistic but tractable wildfire models. Due to their simplicity they allow analytical approaches that further our understanding under increasing complexity.     

The Application of Neutral Landscape Models in Conservation Biology

Neutral landscape models, derived from percolation theory in the field of landscape ecology, are grid-based maps in which complex habitat distributions are generated by random or fractal algorithms. This grid-based representation of landscape structure is compatible with the raster-based format of geographical information systems (GIS), which facilitates comparisons between theoretical and real landscapes. Neutral landscape models permit the identification of critical thresholds in connectivity, which can be used to predict when landscapes will become fragmented. The coupling of neutral landscape models with generalized population models, such as metapopulation theory, provides a null model for generating predictions about population dynamics in fragmented landscapes. Neutral landscape models can contribute to the following applications in conservation: (1) incorporation of complex spatial patterns in (meta)population models; (2) identification of species' perceptions of landscape structure; (3) determination of landscape connectivity; (4) evaluation of the consequences of habitat fragmentation for population subdivision; (5) identification of the domain of metapopulation dynamics; (6) prediction of the occurrence of extinction thresholds; ( 7) determination of the genetic consequences of habitat fragmentation; and (8) reserve design and ecosystem management. This generalized, spatially explicit framework bridges the gap between spatially implicit, patch-based models and spatially realistic GIS applications which are usually parameterized for a single species in a specific landscape. Development of a generalized, spatially explicit framework is essential in conservation biology because we will not be able to develop individual models for every species of management concern.     

Utility of Dynamic-Landscape Metapopulation Models for Sustainable Forest Management

Abstract:  We evaluated the utility of combining metapopulation models with landscape-level forest-dynamics models to assess the sustainability of forest management practices. We used the Brown Creeper ( Certhia americana ) in the boreal forests of northern Ontario as a case study. We selected the Brown Creeper as a potential indicator of sustainability because it is relatively common in the region but is dependent on snags and old trees for nesting and foraging; hence, it may be sensitive to timber harvesting. For the modeling we used RAMAS Landscape, a software package that integrates RAMAS GIS, population-modeling software, and LANDIS, forest-dynamics modeling software. Predictions about the future floristic composition and structure of the landscape under a variety of management and natural disturbance scenarios were derived using LANDIS. We modeled eight alternative forest management scenarios, ranging in intensity from no timber harvesting and a natural fire regime to intensive timber harvesting with salvage logging after fire. We predicted the response of the Brown Creeper metapopulation over a 160-year period and used future population size and expected minimum population size to compare the sustainability of the various management scenarios. The modeling methods were easy to apply and model predictions were sensitive to the differences among management scenarios, indicating that these methods may be useful for assessing and ranking the sustainability of forest management options. Primary concerns about the method are the practical difficulties associated with incorporating fire stochasticity in prediction uncertainty and the number of model assumptions that must be made and tested with sensitivity analysis. We wrote new software to help quantify the contribution of landscape stochasticity to model prediction uncertainty.     

Fire and forest landscapes in the Georgia Piedmont: an assessment of spatial modeling assumptions

Landscape simulation models are widely used to study the behavior of ecological systems. As computing power has increased, these models have become more complex and incorporated more realistic spatial representations of landscape patterns and ecological processes. The goal of this research was to examine the sensitivity of simulated landscape patterns to fundamental spatial modeling assumptions. The LANDIS simulator was parameterized for forests of the Georgia Piedmont and used to model landscape-scale community dynamics at fire return intervals from 20 to 100 years. A base scenario incorporating localized seed dispersal along with landform-related variation in species establishment rates and disturbance regimes was contrasted with three alternative scenarios. The uniform habitat scenario applied the same set of species establishment coefficients across all landforms. The uniform dispersal scenario removed the effects of seed source abundance and pattern on species establishment. The uniform disturbance scenario assumed identical disturbance regimes on all landforms.At the shortest fire return intervals, fire severities were low and the stand age distribution was dominated by older forests. At longer fire return intervals, fire severities were high and the stand age distribution was skewed toward younger forests. Species composition generally followed a gradient from fire-resistant species at short fire return intervals to fire-sensitive species at longer fire return intervals. However, some species exhibited bimodal distributions with high abundances at both short and long fire return intervals. Landscape responses to fire were similar in the uniform habitat scenario and the base scenario. Communities were less sensitive to fire return interval and had more fire-sensitive species in the uniform dispersal scenario than in the base scenario. Species composition in the uniform disturbance scenario was similar to the base scenario for the longest fire-intervals, but was more sensitive to changes in the fire regime at shorter fire return intervals. In models of Piedmont forest landscapes, accurate spatial representations of dispersal and fire regime heterogeneity are essential for predicting landscape-scale species composition under changing fire regimes. In contrast, the precise spatial representation of species–habitat relationships may be considerably less important.     

Fire Mosaics and Reptile Conservation in a Fire‐Prone Region

Fire influences the distribution of fauna in terrestrial biomes throughout the world. Use of fire to achieve a mosaic of vegetation in different stages of succession after burning (i.e., patch‐mosaic burning) is a dominant conservation practice in many regions. Despite this, knowledge of how the spatial attributes of vegetation mosaics created by fire affect fauna is extremely scarce, and it is unclear what kind of mosaic land managers should aim to achieve. We selected 28 landscapes (each 12.6 km²) that varied in the spatial extent and diversity of vegetation succession after fire in a 104,000 km² area in the semiarid region of southeastern Australia. We surveyed for reptiles at 280 sites nested within the 28 landscapes. The landscape‐level occurrence of 9 of the 22 species modeled was associated with the spatial extent of vegetation age classes created by fire. Biogeographic context and the extent of a vegetation type influenced 7 and 4 species, respectively. No species were associated with the diversity of vegetation ages within a landscape. Negative relations between reptile occurrence and both extent of recently burned vegetation (≤10 years postfire, n = 6) and long unburned vegetation (>35 years postfire, n = 4) suggested that a coarse‐grained mosaic of areas (e.g. >1000 ha) of midsuccessional vegetation (11–35 years postfire) may support the fire‐sensitive reptile species we modeled. This age class coincides with a peak in spinifex cover, a keystone structure for reptiles in semiarid and arid Australia. Maintaining over the long term a coarse‐grained mosaic of large areas of midsuccessional vegetation in mallee ecosystems will need to be balanced against the short‐term negative effects of large fires on many reptile species and a documented preference by species from other taxonomic groups, particularly birds, for older vegetation. Mosaicos de Fuego y la Conservación de Reptiles en una Región Propensa al Fuego     

Spatial occurrence of a habitat-tracking saproxylic beetle inhabiting a managed forest landscape.

Because of the dynamic nature of many managed habitats, proper evaluation of conservation efforts calls for models that take into account both spatial and temporal habitat dynamics. We develop a metapopulation model for successional-type systems, in which habitat quality changes over time in a predictable fashion. The occupancy and recruitment of the predatory saproxylic (dependent on dead wood) beetle Harminius undulatus was studied in a managed boreal forest landscape, covering 24,449 ha, in central Sweden. In a first step, we analyzed the beetle's occupancy pattern in relation to stand characteristics, and the amounts of present and past habitat in the surrounding landscape. Managed forest is suitable habitat when > or =60 years old, and immediately after cutting, but not between the ages of 10 and 60 years. The observed occupancy of H. undulatus was positively correlated with the stand's age as habitat. We used a metapopulation model to predict the current probability of occurrence in each forest stand, given the spatiotemporal distribution of suitable forest stands during the last 50 years. Metapopulation parameters were estimated by matching predicted spatial distributions with observed spatial distributions. The model predicted observed spatial distributions better than a similar model that assumed constant habitat quality of each forest stand. Thus, metapopulation models for successional-type systems, such as dead wood dependent organisms in managed forest landscapes, should include habitat dynamics. An estimated 82% of the landscape-wide recruitment took place in managed stands, which covered 87% of the forest area, in comparison with 18% in unmanaged stands, which covered 13% of the forest area. Among the managed stand types, > or =60-year-old stands and 3-7-year-old clear-cuttings contributed to 79% of the total recruitment while 8-59-year-old stands only contributed 3%. The results suggest the following guidelines to improve conditions for H. undulatus and other species with similar habitat requirements: (1) the proportion of the landscape constituted by younger stands should not be allowed to grow too large, (2) the rotation period of managed stands should not be allowed to be too short, and (3) dead wood should be retained and created at final cutting.     

A Multispecies Framework for Landscape Conservation Planning

Abstract: Rapidly changing landscapes have spurred the need for quantitative methods for conservation assessment and planning that encompass large spatial extents. We devised and tested a multispecies framework for conservation planning to complement single‐species assessments and ecosystem‐level approaches. Our framework consisted of 4 elements: sampling to effectively estimate population parameters, measuring how human activity affects landscapes at multiple scales, analyzing the relation between landscape characteristics and individual species occurrences, and evaluating and comparing the responses of multiple species to landscape modification. We applied the approach to a community of terrestrial birds across 25,000 km² with a range of intensities of human development. Human modification of land cover, road density, and other elements of the landscape, measured at multiple spatial extents, had large effects on occupancy of the 67 species studied. Forest composition within 1 km of points had a strong effect on occupancy of many species and a range of negative, intermediate, and positive associations. Road density within 1 km of points, percent evergreen forest within 300 m, and distance from patch edge were also strongly associated with occupancy for many species. We used the occupancy results to group species into 11 guilds that shared patterns of association with landscape characteristics. Our multispecies approach to conservation planning allowed us to quantify the trade‐offs of different scenarios of land‐cover change in terms of species occupancy.     

Thresholds of species loss in Amazonian deforestation frontier landscapes

In the Brazilian Amazon, private land accounts for the majority of remaining native vegetation. Understanding how land‐use change affects the composition and distribution of biodiversity in farmlands is critical for improving conservation strategies in the face of rapid agricultural expansion. Working across an area exceeding 3 million ha in the southwestern state of Rondônia, we assessed how the extent and configuration of remnant forest in replicate 10,000‐ha landscapes has affected the occurrence of a suite of Amazonian mammals and birds. In each of 31 landscapes, we used field sampling and semistructured interviews with landowners to determine the presence of 28 large and medium sized mammals and birds, as well as a further 7 understory birds. We then combined results of field surveys and interviews with a probabilistic model of deforestation. We found strong evidence for a threshold response of sampled biodiversity to landscape level forest cover; landscapes with <30–40% forest cover hosted markedly fewer species. Results from field surveys and interviews yielded similar thresholds. These results imply that in partially deforested landscapes many species are susceptible to extirpation following relatively small additional reductions in forest area. In the model of deforestation by 2030 the number of 10,000‐ha landscapes under a conservative threshold of 43% forest cover almost doubled, such that only 22% of landscapes would likely to be able to sustain at least 75% of the 35 focal species we sampled. Brazilian law requires rural property owners in the Amazon to retain 80% forest cover, although this is rarely achieved. Prioritizing efforts to ensure that entire landscapes, rather than individual farms, retain at least 50% forest cover may help safeguard native biodiversity in private forest reserves in the Amazon. Umbrales de Pérdida de Especies en los Paisajes Fronterizos de Deforestación en el Amazonas Ochoa‐Quintero     

Continuous versus binary representations of landscape heterogeneity in spatially-explicit models of mobile populations

How a landscape is represented is an important structural assumption in spatially-explicit simulation models. Simple models tend to specify just habitat and non-habitat (binary), while more complex models may use multiple levels or a continuum of habitat quality (continuous). How these different representations influence model projections is unclear. To assess the influence of landscape representation on population models, I developed a general, individual-based model with local dispersal and examined population persistence across binary and continuous landscapes varying in the amount and fragmentation of habitat. In binary and continuous landscapes habitat and non-habitat were assigned a unique mean suitability. In continuous landscapes, suitability of each individual site was then drawn from a normal distribution with fixed variance. Populations went extinct less often and abundances were higher in continuous landscapes. Production in habitat and non-habitat was higher in continuous landscapes, because the range of habitat suitability sampled by randomly dispersing individuals was higher than the overall mean habitat suitability. Increasing mortality, dispersal distance, and spatial heterogeneity all increased the discrepancy between continuous and binary landscapes. The effect of spatial structure on the probability of extinction was greater in binary landscapes. These results show that, under certain circumstances, model projections are influenced by how variation in suitability within a landscape is represented. Care should be taken to assess how a given species actually perceives the landscape when conducting population viability analyses or empirical validation of theory.     

Spatial uncertainty analysis of population models

This paper describes an approach for conducting spatial uncertainty analysis of spatial population models, and illustrates the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial population models typically simulate birth, death, and migration on an input map that describes habitat. Typically, only a single “reference” map is available, but we can imagine that a collection of other, slightly different, maps could be drawn to represent a particular species’ habitat. As a first approximation, our approach assumes that spatial uncertainty (i.e., the variation among values assigned to a location by such a collection of maps) is constrained by characteristics of the reference map, regardless of how the map was produced. Our approach produces lower levels of uncertainty than alternative methods used in landscape ecology because we condition our alternative landscapes on local properties of the reference map. Simulated spatial uncertainty was higher near the borders of patches. Consequently, average uncertainty was highest for reference maps with equal proportions of suitable and unsuitable habitat, and no spatial autocorrelation. We used two population viability models to evaluate the ecological consequences of spatial uncertainty for landscapes with different properties. Spatial uncertainty produced larger variation among predictions of a spatially explicit model than those of a spatially implicit model. Spatially explicit model predictions of final female population size varied most among landscapes with enough clustered habitat to allow persistence. In contrast, predictions of population growth rate varied most among landscapes with only enough clustered habitat to support a small population, i.e., near a spatially mediated extinction threshold. We conclude that spatial uncertainty has the greatest effect on persistence when the amount and arrangement of suitable habitat are such that habitat capacity is near the minimum required for persistence.     

The importance of spatial autocorrelation,extent and resolution in predicting forest bird occurrence

Concerns about declines in forest biodiversity underscore the need for accurate estimates of the distribution and abundance of organisms at large scales and at resolutions that are fine enough to be appropriate for management. This paper addresses three major objectives: (i) to determine whether the resolution of typical air photo-derived forest inventory is sufficient for the accurate prediction of site occupancy by forest birds. We compared prediction success of habitat models using air photo variables to models with variables derived from finer resolution, ground-sampled vegetation plots. (ii) To test whether incorporating spatial autocorrelation into habitat models via autologistic regression increases prediction success. (iii) To determine whether landscape structure is an important factor in predicting bird distribution in forest-dominated landscapes. Models were tested locally (Greater Fundy Ecosystem [GFE]) using cross-validation, and regionally using an independent data set from an area located ca. 250 km to the northwest (Riley Brook [RB]). We found significant positive spatial autocorrelation in the residuals of at least one habitat model for 76% (16/21) of species examined. In these cases, the logistic regression assumption of spatially independent errors was violated. Logistic models that ignored spatial autocorrelation tended to overestimate habitat effects. Though overall prediction success was higher for autologistic models than logistic models in the GFE, the difference was only significantly improved for one species. Further, the inclusion of spatial covariates did little to improve model performance in the geographically discrete study area. For 62% (13/21) of species examined, landscape variables were significant predictors of forest bird occurrence even after statistically controlling for stand-level variability. However, broad spatial extents explained less variation than local factors. In the GFE, 76% (16/21) of air photo and 81% (17/21) of ground plot models were accurate enough to be of practical utility (AUC > 0.7). When applied to RB, both model types performed effectively for 55% (11/20) of the species examined. We did not detect an overall difference in prediction success between air photo and ground plot models in either study area. We conclude that air photo data are as effective as fine resolution vegetation data for predicting site occupancy for the majority of species in this study. These models will be of use to forest managers who are interested in mapping species distributions under various timber harvest scenarios, and to protected areas planners attempting to optimize reserve function.     

The effects of forest harvest intensity in combination with wind disturbance on carbon dynamics in Lake States Mesic Forests

Total forest carbon (C) storage is determined by succession, disturbances, climate, and the edaphic properties of a site or region. Forest harvesting substantially affects C dynamics; these effects may be amplified if forest harvesting is intensified to provide biofuel feedstock. We tested the effects of harvest intensity on landscape C using a simulation modeling approach that included C dynamics, multiple disturbances, and successional changes in composition. We developed a new extension for the LANDIS-II forest landscape disturbance and succession model that incorporates belowground soil C dynamics derived from the CENTURY soil model. The extension was parameterized and calibrated using data from an experimental forest in northeastern Wisconsin, USA. We simulated a 9800 ha forested landscape over 400 years with wind disturbance combined with no harvesting, harvesting with residual slash left on site (‘standard harvest’), and whole-tree harvesting. We also simulated landscapes without wind disturbance and without eastern hemlock (Tsuga canadensis) to examine the effects of detrital quantity and quality on C dynamics. We estimated changes in live C, detrital C, soil organic C, total C, and forest composition. Overall, the simulations without harvesting had substantially greater total C and continued to sequester C. Standard harvest simulations had more C than the whole tree harvest simulations. Under both harvest regimes, C accrual was not evident after 150 years. Without hemlock, SOC was reduced due to a decline in detritus and a shift in detrital chemistry. In conclusion, if the intensity of harvesting increases we can expect a corresponding reduction in potential C storage. Compositional changes due to historic circumstances (loss of hemlock) may also affect forest C although to a lesser degree than harvesting. The modeling approach presented enabled us to consider multiple, interacting drivers of landscape change and the subsequent changes in forest C.     

Independent effects of fragmentation on forest songbirds: an organism-based approach.

The degree to which spatial patterns influence the dynamics and distribution of populations is a central question in ecology. This question is even more pressing in the context of rapid habitat loss and fragmentation, which threaten global biodiversity. However, the relative influence of habitat loss and landscape fragmentation, the spatial patterning of remaining habitat, remains unclear. If landscape pattern affects population size, managers may be able to design landscapes that mitigate habitat loss. We present the results of a mensurative experiment designed to test four habitat loss vs. fragmentation hypotheses. Unlike previous studies, we measured landscape structure using quantitative, spatially explicit habitat distribution models previously developed for two species: Blackburnian Warbler (Dendroica fusca) and Ovenbird (Seiurus aurocapilla). We used a stratified sampling design that reduced the confounding of habitat amount and fragmentation variables. Occurrence and reoccurrence of both species were strongly influenced by characteristics at scales greater than the individual territory, indicating little support for the random-sample hypothesis. However, the type and spatial extent of landscape influence differed. Both occurrence and reoccurrence of Blackburnian Warblers were influenced by the amount of poor-quality matrix at 300- and 2000-m spatial extents. The occurrence and reoccurrence of Ovenbirds depended on a landscape pattern variable, patch size, but only in cases when patches were isolated. These results support the hypothesis that landscape pattern is important for some species only when the amount of suitable habitat is low. Although theoretical models have predicted such an interaction between landscape fragmentation and composition, to our knowledge this is the first study to report empirical evidence of such nonlinear fragmentation effects. Defining landscapes quantitatively from an organism-based perspective may increase power to detect fragmentation effects, particularly in forest mosaics where boundaries between patches and matrix are ambiguous. Our results indicate that manipulating landscape pattern may reduce negative impacts of habitat loss for Ovenbird, but not Blackburnian Warbler. We emphasize that most variance in the occurrence of both species was explained by local scale or landscape composition variables rather than variables reflecting landscape pattern.     

Modelling the spatial distribution of montane and subalpine forests in the central Alps using digital elevation models

The analysis of complex interactions between spatial distribution patterns of site factors and vegetation types is crucial for understanding high mountain ecosystems, especially in the view of a changing climate. Therefore, in the present study, a GIS and remote sensing-based approach is followed to produce a vegetation map for a study area in the Western Alps (Switzerland). Two major forest alliances are chosen for analysis: subalpine coniferous forest Vaccinio-Piceion/Larici-Pinetum cembrae and montane oak forest Quercion pubescenti-petraeae. As spatial information on site factors is commonly lacking in mountain areas, the use of a digital elevation model (DEM) is a potential substitute for use in vegetation analyses: it highly correlates with temperature, moisture, geomorphological processes and disturbance factors. Thus, it is important to analyse the capabilities of a DEM for indicating habitat conditions in a landscape characterised by high topodiversity and a patchwork of microclimatic habitats.For the purpose of identifying the potential of landform parameters for the indication of forest habitat structures in the present study, 24 primary and secondary landform parameters have been derived, indicating temperature and moisture distribution, exposure towards wind, snow, etc. Quantitative analyses were performed using statistical means such as contingency correlation coefficients and principal components analysis. The results formed the basis for the development of parallel-epiped-vegetation models (PED) used to simulate the spatial distribution patterns of the subalpine coniferous and the montane oak forest. It can be shown that topographic variables derived from a DEM at a spatial resolution of 25 m are very useful for indicating habitats of large forest types. Additionally potential forest sites in the cultural landscape, removed by human logging, can be reconstructed.Inaccuracies within the simulation results can partly be attributed to the insufficient parameterisation of geomorphologic activity and to poor spatial resolution of the DEM as compared to the vegetation data. Although the lack of information on the human dimension leads to some uncertainties in the interpretation of spatial patterns of vegetation, the exclusive use of topographic variables in vegetation models for the indication of forest habitats is very promising.     

Appreciating Ecological Complexity: Habitat Contours as a Conceptual Landscape Model

Abstract:  Organisms respond to their surroundings at multiple spatial scales, and different organisms respond differently to the same environment. Existing landscape models, such as the "fragmentation model" (or patch-matrix-corridor model) and the "variegation model," can be limited in their ability to explain complex patterns for different species and across multiple scales. An alternative approach is to conceptualize landscapes as overlaid species-specific habitat contour maps. Key characteristics of this approach are that different species may respond differently to the same environmental conditions and at different spatial scales. Although similar approaches are being used in ecological modeling, there is much room for habitat contours as a useful conceptual tool. By providing an alternative view of landscapes, a contour model may stimulate more field investigations stratified on the basis of ecological variables other than human-defined patches and patch boundaries. A conceptual model of habitat contours may also help to communicate ecological complexity to land managers. Finally, by incorporating additional ecological complexity, a conceptual model based on habitat contours may help to bridge the perceived gap between pattern and process in landscape ecology. Habitat contours do not preclude the use of existing landscape models and should be seen as a complementary approach most suited to heterogeneous human-modified landscapes.