Textural Ordination Based on Fourier Spectral Decomposition: A Method to Analyze and Compare Landscape Patterns

We propose an approach to texture characterization and comparison that directly uses the information of digital images of the earth surface without requesting a prior distinction of structural ‘patches’. Digital images are partitioned into square ‘windows’ that define the scale of the analysis and which are submitted to the two-dimensional Fourier transform for extraction of a simplified textural characterization (in terms of coarseness) via the computation of a ‘radial’ power spectrum. Spectra computed from many images of the same size are systematically compared by means of a principal component analysis (PCA), which provides an ordination along a limited number of coarseness vs. fineness gradients. As an illustration, we applied this approach to digitized panchromatic air photos depicting various types of land cover in a semiarid landscape of northern Cameroon. We performed ‘textural ordinations’ at several scales by using square windows with sides ranging from 120 m to 1 km. At all scales, we found two coarseness gradients (PCA axes) based on the relative importance in the spectrum of large (> 50 km⁻¹), intermediate (30–50 km⁻¹), small (10–25 km⁻¹) and very small (<10 km⁻¹) spatial frequencies. Textural ordination based on Fourier spectra provides a powerful and consistent framework to identifying prominent scales of landscape patterns and to compare scaling properties across landscapes.     

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.     

Effects of fragmentation on cattle in African savannas under variable precipitation

Cattle move to access patches that vary in forage quantity and quality. Fragmentation can prevent animals from reaching patches. I used an integrative ecosystem model applied to three African landscapes to explore the sensitivity of cattle populations to fragmentation (here, changes in populations as parcel areas decreased) under different precipitation patterns. I hypothesized that low and high precipitation would yield populations relatively insensitive to fragmentation, intermediate precipitation would yield more sensitive populations, and more variable inter-annual precipitation would reduce sensitivity to fragmentation. Precipitation data were altered to yield averages of 100–1,000 mm year⁻¹ and inter-annual coefficients of variation of 0–60%. A 1,000 km² landscape in each area was divided into progressively smaller parcels and simulations conducted for each parcel. Rainfall at 100 mm year⁻¹ supported low populations that were insensitive to fragmentation. Populations peaked at rainfall levels similar to those observed, and declined under higher precipitation, due in-part to shrub expansion. Fragmenting landscapes caused up to a 62% decline in cattle. High inter-annual variation in precipitation reduced sensitivity to fragmentation when precipitation was above that observed. The pattern was opposite when precipitation was below what was observed. Cattle on the landscape with fine-scale heterogeneity were relatively insensitive to fragmentation, and those on the heterogeneous but coarse-grained landscape were extremely sensitive. Fragmentation in landscapes where populations are sensitive will require more intensive inputs to offset losses, and changes in the frequency of extreme weather associated with climate change will alter the sensitivity of some populations to fragmentation. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Multi-scale factors and long-term responses of Chihuahuan Desert grasses to drought

Factors with variation at broad (e.g., climate) and fine scales (e.g., soil texture) that influence local processes at the plant scale (e.g., competition) have often been used to infer controls on spatial patterns and temporal trends in vegetation. However, these factors can be insufficient to explain spatial and temporal variation in grass cover for arid and semiarid grasslands during an extreme drought that promotes woody plant encroachment. Transport of materials among patches may also be important to this variation. We used long-term cover data (1915–2001) combined with recently collected field data and spatial databases from a site in the northern Chihuahuan Desert to assess temporal trends in cover and the relative importance of factors at three scales (plant, patch, landscape unit) in explaining spatial variation in grass cover. We examined cover of five important grass species from two topographic positions before, during, and after the extreme drought of the 1950s. Our results show that dynamics before, during, and after the drought varied by species rather than by topographic position. Different factors were related to cover of each species in each time period. Factors at the landscape unit scale (rainfall, stocking rate) were related to grass cover in the pre- and post-drought periods whereas only the plant-scale factor of soil texture was significantly related to cover of two upland species during the drought. Patch-scale factors associated with the redistribution of water (microtopography) were important for different species in the pre- and post-drought period. Another patch-scale factor, distance from historic shrub populations, was important to the persistence of the dominant grass in uplands (Bouteloua eriopoda) through time. Our results suggest the importance of local processes during the drought, and transport processes before and after the drought with different relationships for different species. Disentangling the relative importance of factors at different spatial scales to spatial patterns and long-term trends in grass cover can provide new insights into the key processes driving these historic patterns, and can be used to improve forecasts of vegetation change in arid and semiarid areas.     

Spatial variability of soil metabolic rate along a dryland elevation gradient

A general framework of ecosystem hotspots suggests variation in soil metabolic activity can be understood through the relative distribution and intensity of patches of disproportionately high ecosystem process rates. To better understand the causes of soil metabolic spatial variability and the variation in ecosystem hotspots we quantified soil respiration (R) spatial heterogeneity across a network of seven sites spanning a 2,489 m elevation gradient in the Santa Rosa Mountains of Southern California. At each site, soil samples were collected from 0–5 and 5–15 cm soil depths at 2 m intervals along three 100 m transects. Each soil sample was analyzed for organic matter content (SOM) and was incubated at 40% water holding capacity for 20 days. R was measured at days 5 and 20. Strong contrasts were observed between the relationships of soil physical variables and R at scales of individual landscapes and the whole region. Notably, the relationship between SOM and R was positive within individual landscapes and negative across the entire region. Plant canopy microenvironments were associated with elevated SOM and R relative to the interspaces. This microenvironment effect on R was reduced by elevation, incubation interval, and soil depth. Geostatistical analyses conducted individually for each site identified an increasing range of autocorrelation from 2 to 10 m and a decreasing proportion of variation that was included in this range with elevation. These results suggest hotspots increase in size but decrease in intensity with elevation thereby creating a maximum hotspot effect at middle elevations.     

Taxon-dependent Scaling: Beetles,Birds, and Vegetation at Four North American Grassland Sites

Because organisms respond to the environment at different scales, it is important to develop ways of determining the appropriate scales for a specific ecological process and organism. We consider whether the relative importance of different scales is associated with organism mobility, and whether this relationship is independent of landscape characteristics. We observed abundances of particular species for vascular plants, ground-dwelling beetles and breeding birds along eight 2-km transects of 40 sampling stations each, distributed over four sites along the regional gradient from shortgrass steppe in central Colorado to tallgrass prairie in central Kansas. For each transect and taxonomic group, the relative importance of factors measured at the trap scale (1 m; soil texture and hardness, vegetation height, bare ground), at the local scale (10 m; density of shrubs and cacti) and at the landscape scale (30 m; Landsat 7 TM spectral bands, slope and elevation) was assessed using hierarchical canonical variance partitioning with forward selection of explanatory variables. Plant, beetle and bird community composition was explained by environmental factors measured at all three scales. Factor influence was more consistent between transects and between plants and beetles for the more homogeneous landscapes of the shortgrass steppe than for the more heterogeneous landscapes of the tallgrass prairie. We conclude that, independent of the mobility of a taxonomic group, factors at several scales are important in explaining community composition. The importance of different scales shifts along a regional gradient, and the variability between sites is high even for nearby sites.     

Characterising the spatial pattern of phenology for the tropical vegetation of India using multi-temporal MERIS chlorophyll data

The annual growth cycles of terrestrial ecosystems are related to long-term regional/global climatic patterns. Understanding vegetation phenology and its spatio-temporal variation is required to reveal and predict ongoing changes in Earth system dynamics. The study attempts to characterize the phenology of the major tropical vegetation types in India, since such information is not yet available for India. Multi-temporal Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) data were utilized to derive onset of greenness (OG) and end of senescence (ES) for four major tropical vegetation types. The study found that Fourier-smoothed results using the first four components revealed adequately the annual phenological variation of the natural vegetation types in India. From these smoothed data, inflection points were located iteratively through a spatio-temporal search, spanning over 18 months of 8-day composite data, per pixel such as to derive the OG and ES. The median OG and ES was extracted from the available annual results for the years 2003–04, 2004–05, 2005–06 and 2006–07. The GLC2000 land cover map (1 km spatial resolution) was utilized to determine the locations of the major vegetation types. The percentage of each vegetation type falling beneath a MTCI composite pixel (4.6 km spatial resolution) was calculated. MTCI composite pixels with homogeneity of ≥80% vegetative cover were used for examining pattern of phenology in different regions, different years and at different latitudes. The most common dates for the occurrence of OG for the tropical evergreen, semi-evergreen, moist-deciduous, and dry-deciduous vegetation types were found to be during February–April, January–April, March–May, and February–May, respectively. Similarly, for ES the most common dates were in February–April, January–April, February–April, and December–April, respectively. The phenological pattern was uniquely different for each vegetation type, as expected, and also differed with regions and latitudes. A general trend of early occurrence of OG in the lower latitudes was observed.     

Aspects influencing the selection of representative urbanization measures to quantify urban–rural gradients

The quantification of urban–rural gradients using urbanization measures has become standard practice in many urban ecological studies. Nonetheless, the choice of urbanization measures for a specific urban gradient still remains problematic. Increasing numbers of papers stress the importance of comparative urban ecological research, in an attempt to contribute to an understanding of the ecology ‘of’ cities. This implies that research in diverse urban areas globally should be comparable. This study follows an approach to quantify the urban–rural gradient in Klerksdorp previously followed in Melbourne, Australia with the goal to help elucidate the viability of creating a standard set of urbanization measures that is useful across continents. Satellite imagery and spatial analysis were used to calculate the values of 12 urbanization measures across a 900 km² landscape grid. Principal components analysis is commonly used to identify smaller subsets of measures to quantify urban–rural gradients. The results of this study indicate that factor analysis is more suitable than principal components analysis and ideal in identifying these independent measures of urbanization. The factor analysis revealed that landscape structure and demographic attributes are both essential characteristics of a city that needs to be accounted for in the choice of urbanization measures. Additionally, we identified seven aspects influencing the direct comparison of cities, namely: scale of analysis, spatial resolution, classification typology, accuracy of input data, specific measure equations, the type of statistical analysis and the habitat context. These aspects must be taken into consideration and resolved before effective comparative gradient research between cities can be achieved.     

A multi-scale assessment of human and environmental constraints on forest land cover change on the Oregon (USA) coast range

Human modification of forest habitats is a major component of global environmental change. Even areas that remain predominantly forested may be changed considerably by human alteration of historical disturbance regimes. To better understand human influences on the abundance and pattern of forest habitats, we studied forest land cover change from 1936 to 1996 in a 25000 km² landscape in the Oregon (USA) Coast Range. We integrated historical forest survey data and maps from 1936 with satellite imagery and GIS data from 1996 to quantify changes in major forest cover types. Change in the total area of closed-canopy forests was relatively minor, decreasing from 68% of the landscape in 1936 to 65% in 1996. In contrast, large-conifer forests decreased from 42% in 1936 to 17% in 1996, whereas small-conifer forests increased from 21% of the landscape in 1936 to 39% in 1996. Linear regression models were used to predict changes in the proportion of large conifer forest as a function of socioeconomic and environmental variables at scales of subbasins (mean size = 1964 km², n=13), watersheds (mean size = 302 km², n=83), and subwatersheds (mean size = 18 km², n=1325). The proportion of land in private ownership was the strongest predictor at all three spatial scales (partial R² values 0.57–0.76). The amounts of variation explained by other independent variables were comparatively minor. Results corroborate the hypothesis that differing management regimes on private and public ownerships have led to different pathways of landscape change. Furthermore, these distinctive trajectories are consistent over a broad domain of spatial scales.     

Importance of Wetland Landscape Structure to Shorebirds Wintering in an Agricultural Valley

Only recently has the influence of landscape structure on habitat use been a research focus in wetland systems. During non-breeding periods when food can be locally limited, wetland spatial pattern across a landscape may be of great importance in determining wetland use. We studied the influence of landscape structure on abundances of wintering Dunlin (Calidris alpina) and Killdeer (Charadrius vociferus) observed on wetlands in the agricultural Willamette Valley of Oregon, USA, during two winters (1999–2000, 2000–2001) of differing rainfall. We examined (1) shorebird use within a sample of 100 km² regions differing in landscape structure (hectares of shorebird habitat [wet, unvegetated]) and (2) use of sites differing in landscape context (area of shorebird habitat within a species-defined radius). For use of sites, we also assessed the influence of two local characteristics: percent of soil exposed and area of wet habitat. We analyzed data using linear regression and information-theoretic modeling. During the dry winter (2000–2001), Dunlin were attracted to regions with more wetland habitat and their abundances at sites increased with greater area of shorebird habitat within both the site and the surrounding landscape. In contrast, Dunlin abundances at sites were related to availability of habitat at only a local scale during the wet winter (1999–2000). Regional habitat availability was of little importance in predicting Killdeer distributions, and Killdeer site use appeared unrelated to habitat distributions at both landscape and local scales. Results suggest prioritizing sites for conservation that are located in areas with high wetland coverage.     

Influence of landscape structure and stand age on species density and biomass of a tropical dry forest across spatial scales

Three central related issues in ecology are to identify spatial variation of ecological processes, to understand the relative influence of environmental and spatial variables, and to investigate the response of environmental variables at different spatial scales. These issues are particularly important for tropical dry forests, which have been comparatively less studied and are more threatened than other terrestrial ecosystems. This study aims to characterize relationships between community structure and landscape configuration and habitat type (stand age) considering different spatial scales for a tropical dry forest in Yucatan. Species density and above ground biomass were calculated from 276 sampling sites, while land cover classes were obtained from multi-spectral classification of a Spot 5 satellite imagery. Species density and biomass were related to stand age, landscape metrics of patch types (area, edge, shape, similarity and contrast) and principal coordinate of neighbor matrices (PCNM) variables using regression analysis. PCNM analysis was performed to interpret results in terms of spatial scales as well as to decompose variation into spatial, stand age and landscape structure components. Stand age was the most important variable for biomass, whereas landscape structure and spatial dependence had a comparable or even stronger influence on species density than stand age. At the very broad scale (8,000–10,500 m), stand age contributed most to biomass and landscape structure to species density. At the broad scale (2,000–8,000 m), stand age was the most important variable predicting both species density and biomass. Our results shed light on which landscape configurations could enhance plant diversity and above ground biomass.     

Influence of land use on water quality in a tropical landscape: a multi-scale analysis

There is a pressing need to understand the consequences of human activities, such as land transformations, on watershed ecosystem services. This is a challenging task because different indicators of water quality and yield are expected to vary in their responsiveness to large versus local-scale heterogeneity in land use and land cover (LUC). Here we rely on water quality data collected between 1977 and 2000 from dozens of gauge stations in Puerto Rico together with precipitation data and land cover maps to (1) quantify impacts of spatial heterogeneity in LUC on several water quality indicators; (2) determine the spatial scale at which this heterogeneity influences water quality; and (3) examine how antecedent precipitation modulates these impacts. Our models explained 30–58% of observed variance in water quality metrics. Temporal variation in antecedent precipitation and changes in LUC between measurements periods rather than spatial variation in LUC accounted for the majority of variation in water quality. Urbanization and pasture development generally degraded water quality while agriculture and secondary forest re-growth had mixed impacts. The spatial scale over which LUC influenced water quality differed across indicators. Turbidity and dissolved oxygen (DO) responded to LUC in large-scale watersheds, in-stream nitrogen concentrations to LUC in riparian buffers of large watersheds, and fecal matter content and in-stream phosphorus concentration to LUC at the sub-watershed scale. Stream discharge modulated impacts of LUC on water quality for most of the metrics. Our findings highlight the importance of considering multiple spatial scales for understanding the impacts of human activities on watershed ecosystem services.     

Conservation of northern bobwhite on private lands in Georgia, USA under uncertainty about landscape-level habitat effects

Large-scale habitat enhancement programs for birds are becoming more widespread, however, most lack monitoring to resolve uncertainties and enhance program impact over time. Georgia’s Bobwhite Quail Initiative (BQI) is a competitive, proposal-based system that provides incentives to landowners to establish habitat for northern bobwhites (Colinus virginianus). Using data from monitoring conducted in the program’s first years (1999–2001), we developed alternative hierarchical models to predict bobwhite abundance in response to program habitat modifications on local and regional scales. Effects of habitat and habitat management on bobwhite population response varied among geographical scales, but high measurement variability rendered the specific nature of these scaled effects equivocal. Under some models, BQI had positive impact at both local farm scales (1, 9 km²), particularly when practice acres were clustered, whereas other credible models indicated that bird response did not depend on spatial arrangement of practices. Thus, uncertainty about landscape-level effects of management presents a challenge to program managers who must decide which proposals to accept. We demonstrate that optimal selection decisions can be made despite this uncertainty and that uncertainty can be reduced over time, with consequent improvement in management efficacy. However, such an adaptive approach to BQI program implementation would require the reestablishment of monitoring of bobwhite abundance, an effort for which funding was discontinued in 2002. For landscape-level conservation programs generally, our approach demonstrates the value in assessing multiple scales of impact of habitat modification programs, and it reveals the utility of addressing management uncertainty through multiple decision models and system monitoring.     

Spatial correlates of amphibian use of constructed wetlands in an urban landscape

Many amphibian species rely on both aquatic and terrestrial habitats to complete their life cycles. Therefore, processes operating both within the aquatic breeding habitat, and in the surrounding uplands may influence species distributions and community composition. Moreover, changes in land use adjacent to breeding site may degrade aquatic habitats. To assess land use effects on pond-breeding amphibian assemblages, we investigated relationships between land use, breeding habitat conditions, and breeding amphibian use of constructed wetlands in urban environments of the Baltimore metropolitan area, USA. Forest and impervious surface associations with species richness and occurrence occurred at spatial scales ranging from 50 to 1,000 m, with strongest relationships at 500 m. Forest and impervious surface cover within 1,000 m of ponds were also related to water and sediment quality, which in turn were capable of explaining a proportion of the observed variation in species richness and occurrence. Taken together, our results suggest that forest and other land covers within relatively proximal distances to ponds (i.e., within 50–1,000 m) may be influencing species richness directly via the provisioning of upland habitat, and indirectly via influences on within pond habitat quality. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Applying Local Measures of Spatial Heterogeneity to Landsat-TM Images for Predicting Wildfire Occurrence in Mediterranean Landscapes

In mountainous Mediterranean regions, land abandonment processes in past decades are hypothesized to trigger secondary vegetal succession and homogenization, which in recent years has increased the size of burned areas. We conducted an analysis of temporal changes in landscape vegetal spatial pattern over a 15-year period (1984–1998) in a rural area of 672.3 km² in Eastern Spain to investigate the relationship between local landscape heterogeneity and wildfire occurrence. Heterogeneity was analyzed from textural metrics derived from non-classified remote sensing data at several periods, and was related to wildfire history in the study area. Several neural network models found significant relationships between local spatial pattern and future fire occurrence. In this study, sensitivity analysis of the texture variables suggested that fire occurrence, estimated as probability of burning in the near future, increased where local homogeneity was higher.     

Disentangling habitat and social drivers of nesting patterns in songbirds

Nest locations of breeding birds are often spatially clustered. This tendency to nest together has generally been related to a patchy distribution of nesting habitat in landscape studies, but behavioral studies of species with clustered breeding patterns draw attention to the importance of social and biotic factors. Indeed, it is becoming increasingly apparent that the breeding system of many territorial, migrant birds may be semi-colonial. The reasons for, and extent of, spatial clustering in their breeding systems are not well understood. Our goal was to tease apart the influence of habitat availability and social drivers of clustered breeding in a neotropical migrant species, the hooded warbler (Wilsonia citrina). To test alternative hypotheses related to clustered habitat or conspecific attraction, we combined a habitat classification based on remote sensing with point pattern analysis of nesting sites. Nest locations (n = 150, 1999–2004), collected in a 1213 ha forested area of Southern Ontario (Canada), were analyzed at multiple spatial scales. Ripley’s K and pair-correlation functions g (uni- and bivariate) were used to test whether nests were clustered merely because potential nesting habitat was also clustered, or whether nests were additionally clustered with respect to conspecifics. Nest locations tended to be significantly clustered at intermediate distances (particularly between 240 and 420 m). Nests were randomly distributed within available habitat at larger distance scales, up to 1500 m. A reasonable hypothesis to explain the detected additional clustering, and one that is consistent with the results of several behavioral studies, is that females pack their nests more tightly than the available habitat requires to be situated closer to their neighbors’ mates. Linking spatially explicit, point pattern analysis with strong inference based on Monte Carlo tests may bring us closer to understanding the generality and reasons behind conspecific attraction at different spatial scales. F. Csillag—deceased.     

Aspen persistence near the National Elk Refuge and Gros Ventre Valley elk feedgrounds of Wyoming, USA

We investigated aspen (Populus tremuloides)regeneration in the Gros Ventre River Valley, the National Elk Refuge and a small part of Grand Teton National Park, Wyoming, USA to see if elk (Cervus elaphus) browsing was as damaging as previously thought. We conducted a landscape-scale survey to assess aspen regeneration across gradients of wintering elk concentrations using 68 randomly selected aspen stands in the 1090 km² study area. Forty-four percent of the stands sampled supported some newer regeneration that had reached the canopy. There were no significant differences of regeneration across elk winter range classification (p=0.25) or distance from feedgrounds (p=0.96). However, a multiple linear regression found that the concentration of elk was one of several important predictors of successful aspen regeneration (p=0.005, R ²=0.36). Our results suggest that stand-replacing regeneration occurs across the landscape at a variety of elk densities despite some trends of reduced regeneration under greater elk concentrations. We propose that high spatial and temporal variation and scattered patches of successful aspen regeneration characterize aspen persistence between periods of episodic regeneration and recruitment.     

Dynamic connectivity of temporary wetlands in the southern Great Plains

We quantified fluctuations in the status of individual patches (wetlands) in supporting connectivity within a network of playas, temporary wetlands of the southern Great Plains of North America that are loci for regional biodiversity. We used remote sensing imagery to delineate the location of surface waters in >8,000 playa basins in a ~31,900 km² portion of Texas and quantified connectivity in this region from 2007 to 2011. We ranked playas as stepping-stones, cutpoints, and hubs at different levels of environmental conditions (regionally wet, dry, and average periods of precipitation) for dispersal distances ranging from 0.5 to 34 km, representing a range of species’ vagilities, to provide baseline dynamics within an area likely to experience disrupted connectivity due to anthropogenic activities. An individual playa’s status as a stepping-stone, cutpoint, or hub was highly variable over time (only a single playa was a top 20 stepping-stone, cutpoint, or hub in >50 % of all of the dates examined). Coalescence of the inundated playa network usually occurred at ≥10 km dispersal distance and depended on wetland density, indicating that critical thresholds in connectivity arose from synergistic effects of dispersal ability (spatial scale) and wet playa occurrence (a function of precipitation). Organisms with dispersal capabilities limited to <10 km routinely experienced effective isolation during our study. Connectivity is thus a dynamic emergent landscape property, so management to maintain connectivity for wildlife within ephemeral habitats like inundated playas will need to move beyond a patch-based focus to a network focus by including connectivity as a dynamic landscape property.     

Landscape effects on scales of movement by white-tailed deer in an agricultural–forest matrix

Understanding how organisms respond to landscape heterogeneity is foundational to landscape ecology. We characterized seasonal scales of movement of white-tailed deer (Odocoileus viginianus) in an agricultural–forest matrix using first-passage time analysis (FPT) for 62 GPS-collared individuals. We investigated whether those scales were driven by demographic or landscape features. We found FPT for each individual across all seasons was typically dominated by a peak in variance of FPT/area at scales (radii) from 425 to 1,675 m. These peaks occurred at scales consistent with seasonal space use. We observed additional lower magnitude peaks at larger scales (3,000–6,000 m) and small scales (25–150 m). Peaks at larger scales were associated with seasonal migrations and dispersal events. Small scale peaks may represent resting or foraging behavior. Female movements were organized at smaller scales than males in the spring/summer season. Models relating landscape features to movement scales suggest that deer perceive and move within the landscape differently as the roles of dominant land-cover types shift seasonally. During winter, configuration (interspersion/juxtaposition) of land-cover types is more important to deer than during spring/summer and fall. During spring/summer and fall, movement behavior may be dictated by reproductive and harvest activities.     

Influence of fire regimes on lodgepole pine stand age and density across the Yellowstone National Park (USA) landscape

A probabilistic spatial model was created based on empirical data to examine the influence of different fire regimes on stand structure of lodgepole pine (Pinus contorta var. latifolia) forests across a >500,000-ha landscape in Yellowstone National Park, Wyoming, USA. We asked how variation in the frequency of large fire events affects (1) the mean and annual variability of age and tree density (defined by postfire sapling density and subsequent stand density) of lodgepole pine stands and (2) the spatial pattern of stand age and density across the landscape. The model incorporates spatial and temporal variation in fire and serotiny in predicting postfire sapling densities of lodgepole pine. Empirical self-thinning and in-filling curves alter initital postfire sapling densities over decades to centuries. In response to a six-fold increase in the probability of large fires (0.003 to 0.018 year⁻¹), mean stand age declined from 291 to 121 years. Mean stand density did not increase appreciably at high elevations (1,029 to 1,249 stems ha⁻¹) where serotiny was low and postfire sapling density was relatively low (1,252 to 2,203 stems ha⁻¹). At low elevations, where prefire serotiny and postfire lodgepole pine density are high, mean stand densities increased from 2,807 to 7,664 stems ha⁻¹. Spatially, the patterns of stand age became more simplified across the landscape, yet patterns of stand density became more complex. In response to more frequent stand replacing fires, very high annual variability in postfire sapling density is expected, with higher means and greater variation in stand density across lodgepole pine landscapes, especially in the few decades following large fires.