Scale of heterogeneity of forage production and winter foraging by elk and bison

The relationship between fine-scale spatial patterns of forage abundance and the feeding patterns of large ungulates is not well known. We compared these patterns for areas grazed in winter by elk and bison in a sagebrush-grassland landscape in northern Yellowstone National Park. At a fine scale, the spatial distribution of mapped feeding stations in 30 m × 30 m sites was found to be random where there were no large patches devoid of vegetation. In areas similar to the mapped sites, the underlying spatial distribution pattern of biomass was also determined to be random. At a broad scale, forage biomass differed among communities across the northern range but forage quality did not. These results suggest that ungulates are feeding randomly within forage patches (fine scale) but may select feeding sites based upon forage abundance at broader, landscape scales. Contrary to what has been suggested in other systems, ungulates were not overmatching at finer scales.     

Statistical treatment and comparative analysis of scale-dependent aquatic transect data in estuarine landscapes

Estuarine ecosystem dynamics have evolved around and respond to landscape-level influences that are dynamic in space and time. The estuarine water column is effectively the physical and biologial integrator of these landscape inputs. In this paper, we present a floating window Analysis of Covariance (ANCOVA) technique to statistically compare and contrast aquatic transect data that were taken at different times and under different tidal conditions, yet were geographically parallel and spatially articulate. The floating window ANCOVA compared two transects by testing whether the means of the dependent variable were significantly different while also testing whether the slopes of patterns in the dependent variable were significantly different. By varying the size of the floating window where the ANCOVA was run, we were able to examine how scale affected the magnitude and spatial pattern of that variable. The percentages of total models run, at a given window size, that generated significantly different magnitudes (means) and patterns (slopes) in the dependent variable were referred to as the degree of dissimilarity. Plots of window size versus degree of dissimilarity elucidated temporal and spatial variability in water column parameters at a range of scales. The advantages of this new statistical method in relation to traditional spatial statistics are discussed.We demonstrated the efficacy of the floating window ANCOVA method by comparing chlorophyll and salinity transect data taken at the North Inlet, SC estuary during flooding and ebbing tides in Winter, Spring, and Summer 1991. Chlorophyll concentrations represented the biological characteristics of the estuarine water column and salinity represented the physical processes affecting that water column. We found total dissimilarity in the magnitude of salinity data from one season to the next at all scales, but inter-seasonal similarity in spatial patterns over both short (hourly) and long (monthly) time scales. We also found a large seasonal dissimilarity in the magnitude of chlorophyll levels, as expected. Spatial patterns in phytoplankton biomass (as chlorophyll concentrations) appeared to be largely controlled by the physical processes represented with the salinity data. Often, we observed greater dissimilarity in biological and physical parameters from one tide to the next [on a given day] than from one season to the next. In these cases, the greatest flood-ebb differences were associated with landscape-level influences - from rivers and the coastal ocean - that varied greatly with direction of tidal flow. We are currently using spatially articulate aquatic transect data and the floating window ANCOVA technique to validate spatial simulation models at different scales. By using this variable-scale statistical technique to determine coherence between the actual transect data and model output from simulations run at different scales, we will test hypotheses about the scale-dependent relationships between data resolution and model predictability in landscape analysis.     

Landscape pattern in topographically complex landscapes: issues and techniques for analysis

Ecological research provides ample evidence that topography can exert a significant influence on the processes shaping broad-scale landscape vegetation patterns. Studies that ignore this influence run the risk of misinterpreting observations and making inappropriate recommendations to the management community. Unfortunately, the standard methods for landscape pattern analysis are not designed to include topography as a pattern-shaping factor. In this paper, we present a set of techniques designed to incorporate the topographic mosaic into analyses of landscape pattern and dynamics. This toolbox includes adjustments to classic landscape indices that account for non-uniform landscape topography, indices that capture associations and directionality in vegetation pattern due to topographic structure, and the application of statistical models to describe relationships between topographic characteristics and vegetation pattern. To illustrate these methods, we draw on examples from our own analysis of landscape pattern dynamics in logged and unlogged forest landscapes in southwestern British Columbia. These examples also serve to illustrate the importance of considering topography in both research and management applications.This revised version was published online in May 2005 with corrections to the Cover Date.     

The modifiable areal unit problem of spatial heterogeneity of plant community in the transitional zone between oasis and desert using semivariance analysis

The modifiable areal unit problem has significant implications for ecological research that involve investigating and analyzing the spatial heterogeneity of plant community. In this paper, semivariance analysis was used to evaluate the spatial characteristics of plant community in the␣transitional zone between oasis and desert. The spatial structures of the plant community were characterized using exponent model variogram parameters, including nugget (C ₀) range (A ₀) and sill (C ₀+C). Two methods were employed to determine the scale effect of spatial heterogeneity. (1) A constant grain size (10×10 m²) and variational plot areas have been used to analyze spatial heterogeneity of the plant community. (2) The grain size was only changed to analyze spatial heterogeneity. In addition, the plot of 500×500 m² was clustered into nested units of different shapes and different directions to analyze zoning effect. Finally, using semivariance analysis, we obtained a suitable plot area and zoning approach to weaken the scale and zoning effects. The results showed that the effects of scale on different variogram parameters had significant difference. For example, C ₀ and C ₀+C were very sensitive at small scales, A ₀ was influenced significantly by plot area at larger scales, and C ₀ and A ₀ were relatively sensitive to different zoning approaches. In order to get more representative characteristic of spatial heterogeneity of the plant community, the sampling area should be more than 200×200 m² for Nitraria sphaerocarpa populations, 100×100 m² for Reaumuria soongorica populations, and a grain size from 20×20 m² to 30×30 m² for both populations.     

The influence of scale and the spatial characteristics of landscapes on land-cover mapping using remote sensing

Statistical analyses provide a means for assessing relationships between landscape spatial pattern and errors in the estimates of cover-type proportions as land-cover data are aggregated to coarser scales. Results from a multiple-linear regression model suggest that as patch sizes, variance/mean ratio, and initial proportions of cover types increase, the proportion error moves in a positive direction and is governed by the interaction of the spatial characteristics and the scale of aggregation. However, the standard linear model does not account for the different directions of scale-dependent proportion error since some classes become larger and others become smaller as the scene is aggregated. Addition of indicator variables representing class-type significantly improves the performance by allowing the model to respond differently to different classes. A regression tree model provides a much simpler fit to the complex scaling behavior through an interaction between patch size and aggregation scale. An understanding of the relationships between landscape pattern, scale, and proportion error may advance methods for correcting land-cover area estimates. Such methods could also facilitate high-resolution calibration and validation of coarse-scale remote-sensing-based land-cover mapping algorithms. Ongoing initiatives to produce global land-cover datasets from remote sensing, such as efforts within the IGBP and the EOS MODIS Land-Team, include significant emphasis on high level calibration and validation activities of this nature.     

Effects of landscape structure on nest predation in roadsides of a midwestern agroecosystem: a multiscale analysis

Nest predation is an important cause of mortality for many bird species, especially in grassland ecosystems where generalist predators have responded positively to human disturbance and landscape fragmentation. Our study evaluated the influence of the composition and configuration of the surrounding landscape on nest predation. Transects consisting of 10 artificial ground nests each were set up in 136 roadsides in six watersheds in south-central Iowa. Nest predation on individual roadside transects ranged from 0 to 100% and averaged 23%. The relationship of landscape structure within spatially-nested landscapes surrounding each roadside transect (within 200, 400, 800, 1200, and 1600 m of the transect line) to nest predation was evaluated by using multiple regression and canonical correlation analyses. The results of this multiscale landscape analysis demonstrated that predation on ground nests was affected by the surrounding landscape mosaic and that nest predators with different-sized home ranges and habitat affinities responded to landscapes in different ways. In general, wooded habitats were associated with greater nest predation, whereas herbaceous habitats (except alfalfa/pasture) either were associated with less nest predation or were not important. Different landscape variables were important at different spatial scales. Whereas some block-cover habitats such as woodland were important at all scales, others such as rowcrops and alfalfa/pasture were important at large scales. Some strip-cover habitats such as gravel roads and paved roads were important at small scales, but others such as wooded roadsides were important at all all scales. Most landscape metrics (e.g., mean patch size and edge density) were important at large scales. Our study demonstrated that the relationships between landscape structure and predator assemblages are complex, thus making efforts to enhance avian productivity in agricultural landscapes a difficult management goal.     

Exploring preferences for biodiversity and wild parks in Chinese cities: A conjoint analysis study in Hangzhou

There has been a transformation of value orientation from an anthropocentric to eco-centric view in Chinese urban park design. Biodiversity enhancement has been increasingly seen as a prioritised park design aim by landscape designers. This promotes the rise of a novel park style with wild, less manicured appearance in cities, which shows strong contrasts to the traditional park style with ornamental, manicured characteristics. However, in this urban park transformation process, people’s opinion has been almost ignored. This research investigated the importance of biodiversity compared with other relevant urban park attributes (i.e., Facilities, Woodlands, Maintenance, and Seasonal views) identified from preliminary focus groups. The research further predicted preferences between wild and traditional urban parks. Conjoint analysis was used to address these questions. Five urban park attributes (i.e., Biodiversity, Facilities, Woodlands, Maintenance, and Seasonal views) were included in the conjoint questionnaire survey. The survey (N = 187) was conducted with the public and ecology/landscape professionals in Hangzhou, China. Results showed that for professionals, biodiversity was the most important attribute relative to others; for the public, both facilities and biodiversity were the most important attributes. Preferences for the two park styles varied between the two groups: professionals preferred wild parks, whereas the public preferred traditional parks. Yet, public preferences for wild parks were enhanced by improving maintenance levels and providing recreation facilities. The study concluded the appreciation of biodiversity among both the public and professionals. Differences in professional preferences for wild parks compared to the public should be considered when professionals design wild parks in the future.