Is bird incidence in Atlantic forest fragments influenced by landscape patterns at multiple scales?

The degree to which habitat fragmentation affects bird incidence is species specific and may depend on varying spatial scales. Selecting the correct scale of measurement is essential to appropriately assess the effects of habitat fragmentation on bird occurrence. Our objective was to determine which spatial scale of landscape measurement best describes the incidence of three bird species (Pyriglena leucoptera, Xiphorhynchus fuscus and Chiroxiphia caudata) in the fragmented Brazilian Atlantic forest and test if multi-scalar models perform better than single-scalar ones. Bird incidence was assessed in 80 forest fragments. The surrounding landscape structure was described with four indices measured at four spatial scales (400-, 600-, 800- and 1,000-m buffers around the sample points). The explanatory power of each scale in predicting bird incidence was assessed using logistic regression, bootstrapped with 1,000 repetitions. The best results varied between species (1,000-m radius for P. leucoptera; 800-m for X. fuscus and 600-m for C. caudata), probably due to their distinct feeding habits and foraging strategies. Multi-scale models always resulted in better predictions than single-scale models, suggesting that different aspects of the landscape structure are related to different ecological processes influencing bird incidence. In particular, our results suggest that local extinction and (re)colonisation processes might simultaneously act at different scales. Thus, single-scale models may not be good enough to properly describe complex pattern–process relationships. Selecting variables at multiple ecologically relevant scales is a reasonable procedure to optimise the accuracy of species incidence models.     

Nest site use by crested ibis: dependence of a multifactor model on spatial scale

The crested ibis (Nipponia nippon), a species at the brink of extinction in 1981, remain restricted to a small (25 km radius) area of temperate forests in central China. To improve the chances of successful reintroduction into new areas we developed a multifactor logistic regression model of habitat association at multiple scales. Using habitat variables, i.e. vegetation, human impact, elevation, and wetland, we compared occupied and unoccupied sites at grain sizes ranging from 1 to 6400 ha. The goodness-of-fit of the habitat suitability model depended on grain size, with the best fit (most information) at a grain size of 2 ha. Semivariograms showed the habitat variables at control sites have a gradient pattern, yet the crested ibis had their specific habitat preferences, and only selected a narrow range from the available gradient. Our results indicated that spatial scale needs to be considered in developing habitat models for applications such as conservation planning.     

The Importance of Spatial Scale for Conservation and Assessment of Anuran Populations in Coastal Wetlands of the Western Great Lakes,USA

Distributions of pond-breeding amphibians may be influenced by habitat factors at different spatial scales. We used anuran calling surveys to investigate the association between 5 anuran species and habitat variables measured within 100, 500, 1000, and 3000 m of sampling points at 63 coastal wetlands along the US shores of Lake Michigan and Lake Huron. Stepwise logistic regression was used to create predictive models for each species at each spatial scale. Our results confirm the view that habitat variables at multiple scales influence frog distributions, but the strength of predictive models was significantly affected by the spatial scale at which habitat variables were derived. Remotely sensed habitat variables within a 3000 m radius were among the most effective predictors of occurrence for American toad (Bufo americanus), eastern gray treefrog (Hyla versicolor), spring peeper (Pseudacris crucifer), and green frog (Rana clamitans melanota). The western chorus frog (Pseudacris triseriata) was predicted most effectively by variables derived within a 500 m radius. For the most part, these anurans exhibited species-specific responses to habitat variables; however the suite of landscape-scale variables associated with urban land use appeared in all species’ regression models. Associations with landscape-scale variables coupled with well-documented habitat needs at local breeding sites suggest that conservation and assessment of frogs and toads in coastal wetlands should consider the influence of habitat variables at multiple spatial scales.     

Historic landscape change and habitat loss: the case of black grouse in Lower Saxony,Germany

The declines of many specialist bird species in the agricultural landscapes of Central Europe have resulted in small and isolated populations. In the case of the black grouse, a ground-nesting bird species with large spatial requirements, empiric evidence about underlying landscape changes is scarce. In this study, we examined land cover and land cover changes in a farmland-forest mosaic in eastern Lower Saxony, Germany and how they affect occurrence and persistence of black grouse. Spatial information came from historic topographic maps from 1958 to 1975. The results show profound conversions of habitat to forest and farmland but also an increase in settlement area. Habitat conversions and suburbanization were negative correlates of black grouse persistence. Habitat models from before and after a decline period differed in some of the predictors and suggest black grouse habitat to be more diverse before the land cover changes. Our study confirms that land use factors at a landscape scale extent contribute to explain black grouse occurrence and thus can complement important small scale factors like the quality and size of individual habitat patches. Results also show that landscape factors affect black grouse distribution predominantly from an area much greater than an individual black grouse home range. Our models may be further evaluated on present-day landscapes and might be used to evaluate large-scale habitat availability for black grouse.     

Does the scale of our observational window affect our conclusions about correlations between endangered salmon populations and their habitat?

Differences in the strength of species-habitat relationships across scales provide insights into the mechanisms that drive these relationships and guidance for designing in situ monitoring programs, conservation efforts and mechanistic studies. The scale of our observation can also impact the strength of perceived relationships between animals and habitat conditions. We examined the relationship between geographic information system (GIS)-based landscape data and Endangered Species Act-listed anadromous Pacific salmon (Oncorhynchus spp.) populations in three subbasins of the Columbia River basin, USA. We characterized the landscape data and ran our models at three spatial scales: local (stream reach), intermediate (6th field hydrologic units directly in contact with a given reach) and catchment (entire drainage basin). We addressed three questions about the effect of scale on relationships between salmon and GIS representations of landscape conditions: (1) at which scale does each predictor best correlate with salmon redd density, (2) at which scale is overall model fit maximized, and (3) how does a mixed-scale model compare with single scale models (mixed-scale meaning models that contain variables characterized at different spatial scales)? We developed mixed models to identify relationships between redd density and candidate explanatory variables at each of these spatial scales. Predictor variables had the strongest relationships with redd density when they were summarized over the catchment scale. Meanwhile strong models could be developed using landscape variables summarized at only the local scale. Model performance did not improve when we used suites of potential predictors summarized over multiple scales. Relationships between species abundance and land use or intrinsic habitat suitability detected at one scale cannot necessarily be extrapolated to other scales. Therefore, habitat restoration efforts should take place in the context of conditions found in the associated watershed or landscape.     

Landscape characteristics explain large-scale variation in demographic traits in forest grouse

The effects of landscape composition on species and populations have become increasingly important due to large and rapid habitat changes worldwide. In particular, concern is raised for several forest-dwelling species such as capercaillie and black grouse, because their habitats are continuously changing and deteriorating from human development. Conservation of these species is linked to sustainable forest management that seeks to benefit multiple species, which demands knowledge about demographic rates in relation to forest composition and structure. We related the spatial variation in adult density and chick production of capercaillie and black grouse to landscape characteristics from 13 areas within the boreal forest of Norway. Linear mixed effects models showed that black grouse and capercaillie had similar associations to landscape characteristics. Adult density of both species was positively related to the proportion of old forest (>80 years), but only if the area had large proportions of mid to high productive forests. Chick production was negatively related to the proportion of old forest, but positively to habitat diversity and more so for black grouse compared to capercaillie. However, the result for chick production suggest that other forest types also are important, and that forest grouse needs a variety of habitats during their life history stages. Management that seeks to simultaneously conserve populations of black grouse and capercaillie needs to ensure a matrix of various forest types. A special focus must be on the critical life history of local populations to successfully preserve viable populations, for black grouse and capercaillie this implies protection of old and mid to high productive forest while keeping a heterogeneous landscape.     

Prediction of the spatial distribution and relative abundance of ground-dwelling mammals using remote sensing imagery and simulation models

We present an approach that allows current, retrospective and future relative abundances of mammal species to be predicted across landscapes. A spatial generalized regression model of species relative abundance based on habitat quality and time since disturbance was combined with coverages of the spatial distribution of habitat quality derived from a simulation model which predicts the historical and future spatial arrangement of forest habitat. The strength of this approach is that the input habitat data can be derived as part of a standard forest inventory mapping program with the addition of high spatial resolution remote sensing imagery. Furthermore, it operates at the scale used for wildlife management in Australia, which makes it widely applicable. To demonstrate the approach we use data collected over 20 years on the long-nosed potoroo (Potorous tridactylus) and the large wallabies (red-necked wallaby, Macropus rufogriseus, and swamp wallaby, Wallabia bicolor) and their habitats following wildfire. Results indicate the relative abundance of the potoroo has increased, from initially sparse numbers of less than 0.5 % of plot-night occurrences to close to 3% approximately twenty years after a major fire event. The large wallabies by contrast decreased in relative abundance from about 20% since the major fire event. Presently the relative abundance of large wallabies was modelled at 2% of plot-nights with tracks which was very low. Predictions of future relative abundance without additional disturbance were low, with the region likely to be unsuitable for the species in the next 5 years. These models offer tools for investigating the current and historical abundances of key species which can provide data to forest managers for wildlife management thereby translating current scientific understanding into tools suitable for every-day use by forest managers. This revised version was published online in July 2006 with corrections to the Cover Date.     

Statistical models of landscape pattern metrics,with applications to regional scale dynamic forest simulations

Forest managers in Canada need to model landscape pattern or spatial configurationoverlarge (100,000 km²) regions. This presents a scalingproblem, as landscape configuration is measured at a high spatial resolution,but a low spatial resolution is indicated for regional simulation. We present astatistical solution to this scaling problem by showing how a wide range oflandscape pattern metrics can be modelled from low resolution data. Our studyarea comprises about 75,000 km² of boreal mixedwoodforest in northeast Alberta, Canada. Within this area we gridded a sample of 84digital forest cover maps, each about 9500 ha in size, to aresolution of 1 ha and used FRAGSTATS to compute a suite oflandscape pattern metrics for each map. We then used multivariate dimensionreduction techniques and canonical correlation analysis to model therelationship between landscape pattern metrics and simpler stand table metricsthat are easily obtained from non-spatial forest inventories. These analyseswere performed on four habitat types common in boreal mixedwood forests: youngdeciduous, old deciduous, white spruce, and mixedwood types. Using only threelandscape variables obtained directly from stand attribute tables (totalhabitatarea, and the mean and standard deviation of habitat patch size), ourstatistical models explained more than 73% of the joint variation in fivelandscape pattern metrics (representing patch shape, forest interior habitat,and patch isolation). By PCA, these five indices captured much of the totalvariability in the rich set of landscape pattern metrics that FRAGSTATS cangenerate. The predictor variables and strengths of association were highlyconsistent across habitat classes. We illustrate the potential use of suchstatistical relationships by simulating the regional, cumulative effects ofwildfire and forest management on the spatial arrangement of forest patches,using non-spatial stand attribute tables.This revised version was published online in May 2005 with corrections to the Cover Date.     

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.     

Predicting carnivore occurrence with noninvasive surveys and occupancy modeling

Terrestrial carnivores typically have large home ranges and exist at low population densities, thus presenting challenges to wildlife researchers. We employed multiple, noninvasive survey methods—scat detection dogs, remote cameras, and hair snares—to collect detection–nondetection data for elusive American black bears (Ursus americanus), fishers (Martes pennanti), and bobcats (Lynx rufus) throughout the rugged Vermont landscape. We analyzed these data using occupancy modeling that explicitly incorporated detectability as well as habitat and landscape variables. For black bears, percentage of forested land within 5 km of survey sites was an important positive predictor of occupancy, and percentage of human developed land within 5 km was a negative predictor. Although the relationship was less clear for bobcats, occupancy appeared positively related to the percentage of both mixed forest and forested wetland habitat within 1 km of survey sites. The relationship between specific covariates and fisher occupancy was unclear, with no specific habitat or landscape variables directly related to occupancy. For all species, we used model averaging to predict occurrence across the study area. Receiver operating characteristic (ROC) analyses of our black bear and fisher models suggested that occupancy modeling efforts with data from noninvasive surveys could be useful for carnivore conservation and management, as they provide insights into habitat use at the regional and landscape scale without requiring capture or direct observation of study species.     

How do local habitat management and landscape structure at different spatial scales affect fritillary butterfly distribution on fragmented wetlands?

Habitat fragmentation, patch quality and landscape structure are important predictors for species richness. However, conservation strategies targeting single species mainly focus on habitat patches and neglect possible effects of the surrounding landscape. This project assesses the impact of management, habitat fragmentation and landscape structure at different spatial scales on the distribution of three endangered butterfly species, Boloria selene, Boloria titania and Brenthis ino. We selected 36 study sites in the Swiss Alps differing in (1) the proportion of suitable habitat (i.e., wetlands); (2) the proportion of potential dispersal barriers (forest) in the surrounding landscape; (3) altitude; (4) habitat area and (5) management (mowing versus grazing). Three surveys per study site were conducted during the adult flight period to estimate occurrence and density of each species. For the best disperser B. selene the probability of occurrence was positively related to increasing proportion of wetland on a large spatial scale (radius: 4,000 m), for the medium disperser B. ino on an intermediate spatial scale (2,000 m) and for the poorest disperser B. titania on a small spatial scale (1,000 m). Nearby forest did not negatively affect butterfly species distribution but instead enhanced the probability of occurrence and the population density of B. titania. The fen-specialist B. selene had a higher probability of occurrence and higher population densities on grazed compared to mown fens. The altitude of the habitat patches affected the occurrence of the three species and increasing habitat area enhanced the probability of occurrence of B. selene and B. ino. We conclude that, the surrounding landscape is of relevance for species distribution, but management and habitat fragmentation are often more important. We suggest that butterfly conservation should not focus only on a patch scale, but also on a landscape scale, taking into account species-specific dispersal abilities.     

Are hedgerows the route to increased farmland small mammal density? Use of hedgerows in British pastoral habitats

Linear habitats are becoming increasingly common as a consequence of habitat fragmentation, and may provide the sole habitat for some species. Hedgerows are linear features that can vary substantially in structure and quality. Having surveyed 180 hedgerows, in four locations, and sampled their small mammal communities we examined the effect of physical hedgerow attributes on the abundance of small mammal species. Using three elements of landscape structure, we explored whether variation was best explained by the Random Sample Hypothesis (that small islands represent a random sample of those species populating larger areas), or by the Fragmentation Hypothesis (that species abundance will decrease with a loss of habitat area). We tested the relationship between the relative abundance of small mammals and 1. hedgerow connectivity; 2. total habitat availability and 3. local habitat complexity. We then explored the predictive power of combinations of these habitat variables. Connectivity was a positive predictor of wood mice Apodemus sylvaticus, and hedgerow gappiness was a negative predictor of bank voles Clethrionomys glareolus. The total amount of habitat available (hedgerow width, height and length) was a positive indicator of total small mammal biomass. These results support the Fragmentation Hypothesis that species abundance and distribution decrease with a loss of habitat area. The preservation of linear and associated habitats may therefore be important in maintaining metapopulations of the species we studied.     

An invasive species’ relationship with environmental variables changes across multiple spatial scales

To further our understanding of invasive species?? novel distributions, knowledge of invasive species?? relationships with environmental variables at multiple spatial scales is paramount. Here, we investigate which environmental variables and which spatial scales best explain the invasive mute swan??s (Cygnus olor) distribution in southern Ontario (Canada). Specifically we model mute swan distribution changes according to ecologically-relevant spatial scales: average territory size radius, 140?m; median dispersal distance of cygnets, 3,000?m; and average activity distance of males, 8,000?m. For individual spatial scales, global models using variables measured at each particular scale result in the highest Akaike weights, AUC, and Cohen??s Kappa values. Yet composite models (models combining variables measured at different scales) elicit the best models, as determined by higher Akaike weights and high AUC and Cohen??s Kappa values. Overall, percent water, waterbody perimeter density, temperature, precipitation, and road density are positively correlated with mute swan distribution, while percent forest and elevation are negatively correlated at all scales of analysis. Only percent water and annual precipitation are more influential in determining mute swan distribution at the 3,000 and 8,000?m zone scales than the territory scale. While most species distribution models are performed at a single scale, the results of our study suggest that composite models reflecting a species?? ecological needs provide models of better fit with similar, if not better, predictive accuracy. When analyzing species distributions, we also recommend that ecologists consider the scale of the underlying landscape processes and the effect that this may have on their modelling outcomes.     

Associations of Bird Species Richness and Community Composition with Local and Landscape-scale Environmental Factors in Borneo

A comprehensive understanding of variables associated with spatial differences in community composition is essential to explain and predict biodiversity over landscape scales. In this study, spatial patterns of bird diversity in Central Kalimantan, Indonesia, were examined and associated with local-scale (habitat structure and heterogeneity) and landscape-scale (logging, slope position and elevation) environmental variables. Within the study area (c. 196 km²) local habitat structure and heterogeneity varied considerably, largely due to logging. In total 9747 individuals of 177 bird species were recorded. Akaike's information criterion (AIC) revealed that the best explanatory models of bird community similarity and species richness included both local- and landscape-scale environmental variables. Important local-scale variables included liana abundance, fern cover, sapling density, tree density, dead wood abundance and tree architecture, while important landscape-scale variables were elevation, logging and slope position. Geographic distance between sampling sites was not significantly associated with spatial variation in either species richness or similarity. These results indicate that deterministic environmental processes, as opposed to dispersal-driven stochastic processes, primarily structure bird assemblages within the spatial scale of this study and confirm that highly variable local habitat measures can be effective means of predicting landscape-scale community patterns.     

Spatial Patterns in European Rabbit Abundance After a Population Collapse

Assessing the associations between spatial patterns in population abundance and environmental heterogeneity is critical for understanding various population processes and for managing species and communities. This study evaluates responses in the abundance of the European rabbit (Oryctolagus cuniculus), an important prey for predators of conservation concern in Mediterranean ecosystems, to environmental heterogeneity at different spatial scales. Multi-scale habitat models of rabbit abundance in three areas of Doñana, south-western Spain, were developed using a spatially extensive dataset of faecal pellet counts as an abundance index. The best models included habitat variables at the three spatial scales examined: distance from lagoons (broad scale), mean landscape shrub coverage and interspersion of pastures (home-range scale), and shrub and pasture cover (microhabitat scale). These variables may well have been related to the availability of food and refuge for the species at the different scales. However, the models’ fit to data and their predictive accuracy for an independent sample varied among the study regions. Accurate predictions in some areas showed that the combination of variables at various spatial scales can provide a reliable method for assessing the abundance of ecologically complex species such as the European rabbit over large areas. On the other hand, the models failed to identify abundance patterns in a population that suffered the strongest demographic collapse after viral epidemics, underlining the difficulty of generalizing this approach. In the latter case, factors difficult to implement in static models such as disease history and prevalence, predator regulation and others may underlie the lack of association. Habitat models can provide useful guidelines for the management of landscape attributes relevant to rabbits and help improve the conservation of Mediterranean communities. However, other influential factors not obviously related to environmental heterogeneity should also be analyzed in more detail.     

A positive response of mountain pine beetle to pine forest-clearcut edges at the landscape scale in British Columbia,Canada

In British Columbia, large-scale salvage harvesting has been underway to recover timber value from forest stands infested by mountain pine beetle during the current outbreak. Understanding the response of beetles to clearcut edges particularly at the landscape scale is crucial to understanding the impacts of increased habitat fragmentation due to salvage harvesting on the spread of the beetle infestations. A novel proximity analysis approach based on null models of complete spatial randomness with three different spatial extents was developed to examine the spatial patterns of infestations in relation to cutblocks. Inhomogeneous Poisson point process models were fitted to predict how intensities of infestations varied with distances to the nearest cutblocks. Marked Poisson point process models were also fitted to evaluate the effects of the variables associated with the nearest cutblocks and adjacent infested pine stands on the edge response of beetles. The results clearly illustrated a significant positive edge response of beetles at the landscape scale. The intensities of infestations decreased non-linearly with distances to the nearest cutblocks. The results also suggested that the quality and distribution of key habitat resources could not fully explain the fundamental mechanisms underlying the edge response. The behavioural change of beetle dispersal at edges may also be an important factor contributing to a positive edge response. The results from this study may be useful in improving the efficacy of mountain pine beetle management efforts.     

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.     

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.     

Landscape ecology of <Emphasis Type="Italic">Phragmites australis</Emphasis> invasion in networks of linear wetlands

The interaction between landscape structure and spatial patterns of plant invasion has been little addressed by ecologists despite the new insights it can provide. Because of their spatial configuration as highly connected networks, linear wetlands such as roadside or agricultural ditches, can serve as corridors facilitating invasion at the landscape scale, but species dynamics in these important habitats are not well known. We conducted a landscape scale analysis of Phragmites australis invasion patterns (1985–2002 and 1987–2002) in two periurban areas of southern Québec (Canada) focusing on the interaction between the network of linear wetlands and the adjacent land-uses. Results show that, at the beginning of the reference period, the two landscapes were relatively non-invaded and populations occurred mostly in roadside habitats which then served as invasion foci into other parts of the landscape. The intrinsic rates of increase of P. australis populations in linear anthropogenic habitats were generally higher than those reported for natural wetlands. Riparian habitats along streams and rivers were little invaded compared to anthropogenic linear wetlands, except when they intersected transportation rights-of-way. Bivariate spatial point pattern analysis of colonization events using both Euclidian and network distances generally showed spatial dependence (association) to source populations. An autologistic regression model that included landscape and edaphic variables selected transportation rights-of-way as the best predictor of P. australis occurrence patterns in one of the landscapes. Given the high invasion rates observed, managers of linear wetlands should carefully monitor expansion patterns especially when roads intersect landscapes of conservation or economic value.