A fractal model of vegetation complexity in Alaska

A methodology using fractals to measure vegetation complexity in three regions of Alaska is presented. Subjective, binomial (0 = simple, 1 = complex) classifications of the complexity of mapped vegetation polygon patterns within continuous forest inventory plots measured in the regions were made by interpreters of aerial photographs. The fractal dimensions of the vegetation patterns within the plots then were estimated. Subsequently, the subjective classifications of the photo-interpreted plots were regressed against fractal dimension by using logistic regression.Assessment of interobserver agreement among the aerial photo interpreters, by using estimated unweighted Kappa coefficients, indicated substantial classification agreement among observers.Examination of general versus regional applicability of the logistic models provided strong support for applicability of a single model to all three regions. The logistic model provides numerical identification of the division between simple and complex patterns. Possible applications beyond the needs of the study are discussed.     

Landscape patterns in boundary intensity: a case study of mussel beds

This work examines the proposition that positive interactions among neighboring individuals within a population may produce landscape patterns in boundary intensity. The large scale patterns emerge because the interactions favor an aggregated distribution in the face of a potential limiting factor, and the strength of that factor varies over the landscape. The consequences of spatially varying neighborhood processes were explored using cellular automata simulating the structure of mussel beds in 2-dimensional intertidal landscapes, each characterized by a vertical gradient of tidal immersion and a horizontal gradient of wave energy. Running the model with and without the neighborhood processes demonstrated that the facilitating neighborhood processes elevate intensity above that caused by the gradients, and consequently abrupt (high intensity) boundaries emerged in the midst of gradual environmental variation. Trends generated on the 2-D landscape by the model were compared with those in photo-mosaics of intertidal mussel beds, Mytilus californianus on rocky shores of the British Columbia. The analysis involved interpolation of boundary locations using a spatially-constrained cluster algorithm, and then estimation of the corresponding boundary intensities using a landscape index aggregation (CLUMPY). The general similarity between predicted and real trends in intensity over the wave energy gradients suggests that spatially varying neighborhood processes determine much of the landscape scale variation in boundary intensity, while certain discrepancies (e.g. a more rapid rise of observed intensities with increasing wave exposure) suggest modifications of the theory and new empirical work.     

The use of a geographic information system to analyze long-term landscape alteration by beaver

A Geographic Information System (GIS) was used to analyze how beaver (Castor canadensis) have altered the hydrology and vegetation of Voyageurs National Park, Minnesota over a 46-year period. Maps of beaver ponds prepared from 1940, 1948, 1961, 1972, 1981, and 1986 aerial photographs were analyzed with a rasterbased based GIS to determine impoundment hydrology and vegetation distributions for each map date. Overlay and classification techniques were used to quantify hydrologic and vegetation changes between map dates. The GIS was superior to manual methods for some analyses (e.g., area measurement), and indispensible for others (e.g., transition analysis). Total area impounded increased from 1% to 13% of the landscape between 1940 and 1986, as the beaver population increased from near extirpation to a density of 1 colony/km². Most of the impoundment area increase occurred during the first two decades, when 77% of cumulative impoundment area was flooded. Once impounded ≥60% of the area maintained the same water depth or vegetation during any decade. GIS procedures were combined with field data to show that available nitrogen stocks nearly tripled between 1940 and 1986 as a result of beaver impoundment.     

Changes in landscape patterns in Georgia,USA

The objectives of this study were to determine how landscape patterns in Georgia, USA have changed through time and whether the spatial patterns varied by physiographic region. Historical aerial photography was used to analyze spatial patterns of land use from the 1930's to the 1980's. Land use patterns were quantified by: (1) mean number and size of patches; (2) fractal dimension of patches; (3) amount of edge between land uses; and (4) indices of diversity, dominance, and contagion. Forest cover increased in aerial extent and in mean patch size. The mean size of agricultural patches increased in the coastal plain and decreased in the mountains and piedmont. Edges between land uses decreased through time, indicating less dissection of the landscape. Fractal dimensions also decreased, indicating simpler patch shapes. Indices of diversity and dominance differed through time but not among regions; the contagion index differed among regions but not through time. A geographic trend of decreasing diversity and increasing dominance and contagion was observed from the mountains to the lower coastal plain. Landscape patterns exhibited the greatest changes in the piedmont region. Overall, the Georgia landscape has become less fragmented and more connected during the past 50 years. Changing patterns in the landscape may have implications for many ecological processes and resources.     

Estimates of dryland degradation in Argentina with Fourier signatures from low-altitude monochromatic images with high spatial resolution

Most world drylands are used as graziny lands and undergo degradation of their vegetation cover. The plant cover is typically structured in patchy arrangements, inducing fertility islands critical to maintenance of ecosystem properties. The characteristics of patch structure (size of patches, connectivity-continuity of patch units, etc.) are indicators of the degree of dryland deterioration. We characterized changes in patch structure induced by sheep grazing at a landscape scale using monochromatic low-altitude imagery digitized to a spatial resolution of about 1 m with standard techniques of harmonic analysis applied to develop Fourier signatures. The signatures developed on image line transects were tested with ground samples and mathematical models of plant cover in several dryland fields where spatial deterioration gradients existed. The sensitivity and errors associated to long-wave noise introduced by the geometry of the camera-field-sun spatial arrangement and to high frequency noise introduced by the digitizing process were evaluated by applying suitable filters in the frequency domain. Fourier signatures developed on monochromatic low-altitude imagery proved to be indicative of changes in the patching arrangements of plant cover. We concluded that adequately filtered, high spatial resolution monochromatic images can be used to evaluate the degree of deterioration of dryland landscapes through the computation of selected Fourier signatures in their frequency domain. At comparable cost, aerial photography allows inspecting the landscape at higher spatial resolutions than those attainable with satellite imagery. Also, aerial photos of many areas are available for earlier dates than images from remote sensors, which would allow better inspection of long-term ecosystem changes.This revised version was published online in May 2005 with corrections to the Cover Date.     

Testing methods to produce landscape-scale presettlement vegetation maps from the U.S. public land survey records

The U.S. Public Land Survey (PLS) notebooks are one of the best records of the pre-European settlement landscape and are widely used to recreate presettlement vegetation maps. The purpose of this study was to evaluate the relative ability of several interpolation techniques to map this vegetation, as sampled by the PLS surveyors, at the landscape level. Field data from Sylvania Wilderness Area, MI (U.S.A.), sampled at the same scale as the PLS data, were used for this test. Sylvania is comprised of a forested landscape similar to that present during presettlement times. Data were analyzed using two Arc/Info interpolation processes and indicator kriging. The resulting maps were compared to a `correct' map of Sylvania, which was classified from aerial photographs. We found that while the interpolation methods used accurately estimated the relative forest composition of the landscape and the order of dominance of different vegetation types, they were unable to accurately estimate the actual area occupied by each vegetation type. Nor were any of the methods we tested able to recreate the landscape patterns found in the natural landscape. The most likely cause for these inabilities is the scale at which the field data (and hence the PLS data) were recorded. Therefore, these interpolation methods should not be used with the PLS data to recreate pre-European settlement vegetation at small scales (e.g., less than several townships or areas <10⁴ ha). Recommendations are given for ways to increase the accuracy of these vegetation maps.     

Synthetic Aperture Radar (SAR) images improve habitat suitability models

Context

The ability to detect ecological networks in landscapes is of utmost importance for managing biodiversity and planning corridors.

Objectives

The objective of this study was to evaluate the information provided by a synthetic aperture radar (SAR) image for landscape connectivity modeling compared to aerial photographs (APs).

Methods

We present a novel method that integrates habitat suitability derived from remote sensing imagery into a connectivity model to explain species abundance. More precisely, we compared how two resistance maps constructed using landscape and/or local metrics derived from AP or SAR imagery yield different connectivity values (based on graph theory), considering hedgerow networks and forest carabid beetle species as a model.

Results

We found that resistance maps using landscape and local metrics derived from SAR imagery improve landscape connectivity measures. The SAR model is the most informative, explaining 58% of the variance in forest carabid beetle abundance. This model calculates resistance values associated with homogeneous patches within hedgerows according to their suitability (canopy cover density and landscape grain) for the model species.

Conclusions

Our approach combines two important methods in landscape ecology: the construction of resistance maps and the use of buffers around sampling points to determine the importance of landscape factors. This study was carried out through an interdisciplinary approach involving remote sensing scientists and landscape ecologists. This study is a step forward in developing landscape metrics from satellites to monitor biodiversity.

     

A multi-scale analysis of landscape statistics

It is now feasible to monitor some aspects of landscapeecological condition nationwide using remotely-sensed imagery andindicators of land cover pattern. Previous research showedredundancies among many reported pattern indicators andidentified six unique dimensions of land cover pattern. Thisstudy tested the stability of those dimensions and representativepattern indicators across different types of land cover maps. Themaps were derived from Landsat Thematic Mapper images of theTennessee River and Chesapeake Bay watersheds, and they differedin resolution, number of attributes, and method of delineatinglandscape unit boundaries. A multivariate analysis of patternmetrics was conducted separately for each map, and the resultswere then compared among types of maps. Measures of land coverdiversity, texture, and fractal dimension were more consistentthan measures of average patch shape or compaction among the landcover maps.     

Analysing land-cover changes in relation to environmental variables in Hesse,Germany

Land-use and land-cover changes affect ecological landscape functions and processes. Hence, landscape ecologists have a central interest in a comprehensive understanding of such changes. Our study focuses on the relationships between environmental conditions and agricultural land-cover changes. We present a method to (i) characterise the major spatial-temporal processes of land-cover changes, (ii) identify the correlations between environmental attributes and land-cover changes and (iii) derive potential environmental drivers of land-cover changes in a German marginal rural landscape. The method was applied to study land-cover dynamics from 1945 to 1998 in the districts of Erda, Steinbrücken and Eibelshausen, situated in the marginal rural landscape of the Lahn-Dill Highlands, Germany. We employed land-cover data gained by the interpretation of multi-temporal aerial photographs. Various environmental variables were introduced into the analyses. We identified physical landscape attributes (elevation, slope, aspect, available water capacity and soil texture) and structural landscape dimensions (patch size, patch shape and distance between patch and nearest settlement). With the aid of GIS, K-means partitioning and canonical correspondence analysis, we investigated land-cover trajectory types, land-cover transitions at individual time intervals and their relationships to these environmental variables. Our results show that, between 1945 and 1998, land-cover changes correlated with the physical attributes of the underlying landscape. On the other hand, the structural landscape dimensions correlated with land cover only in periods of minor land-cover changes (1972–98). Greater diversity of physical landscape attributes is correlated with greater land-cover dynamics. Besides the important influence of socio-economic factors, land-cover changes in the study areas took place within the relatively stable physical constraints of the underlying landscape.This revised version was published online in May 2005 with corrections to the Cover Date.     

Using fractal analysis to assess how species perceive landscape structure

To develop a species-centered definition of landscapes, I suggest using a fractal analysis of movement patterns to identify the scales at which organisms are interacting with the patch structure of the landscape. Significant differences in the fractal dimensions of movement patterns of two species indicate that the species may be interacting with the patch structure at different scales. Fractal analysis therefore permits comparisons of landscape perceptions of different species within the same environment.I tested the utility of this fractal application by analyzing the movement patterns of three species of acridid grasshoppers (Orthoptera) in a grassland mosaic. The largest species moved up to 6 times faster than the two smaller species, and species exhibited different responses to microlandscape structure within 25-m² plots. Further, the largest species exhibited different responses to microlandscape structure in two pastures subjected to different intensities of cattle grazing. This species thus is able to integrate information on landscape structure at broad spatial scales. Fractal analysis of movement patterns revealed that the two small species had significantly more tortuous patterns than the larger species, which suggests that these species are interacting with patch structure at a finer scale of resolution than the large species. Fractal analysis can be used to identify the perceptive resolution of a species; that is, the spatial grain and extent at which they are able to perceive and respond to heterogeneity. Analysis of movement patterns across a range of spatial scale may reveal shifts in fractal dimension that reflect transitions in how species respond to the patch structure of the landscape at different scales.     

Scaling of ‘landscapes’ in landscape ecology,or, landscape ecology from a beetle's perspective

Research performed on microlandscapes embodies the essence of landscape ecology by focusing on the ecological consequences of the mosaic structure of different landscape elements. As an illustration, observations and simulations were used to test whether the fractal structure of grassland microlandscapes affected the movement patterns of tenebrionid beeetles in natural environments. The significant tendency of beetles to avoid 1 m² cells with fractal dimensions of 1.85 to 1.89 (indicating the area-filling tendency of bare ground) demonstrated the role of landscape structure as a modifier of beetle movements or diffusion in heterogeneous landscapes. Experiments in microlandscapes may accelerate the development of quantitative conceptual frameworks applicable to landscapes at all scales.     

Landscape analysis of plant diversity

Studies to identify gaps in the protection of habitat for speciesof concern have been inconclusive and hampered by single-scale orpoor multi-scale sampling methods, large minimum mapping units(MMU's of 2 ha to 100 ha), limited and subjectively selected fieldobservations, and poor mathematical and ecological models. Weovercome these obstacles with improved multi-scale samplingtechniques, smaller MMU's (< 0.02 ha), an unbiased sampling designbased on double sampling, improved mathematical models includingspecies-area curves corrected for habitat heterogeneity, andgeographic information system-based ecological models. We applythis landscape analysis approach to address resource issues inRocky Mountain National Park, Colorado. Specifically, we quantifythe effects of elk grazing on plant diversity, identify areas ofhigh or unique plant diversity needing increased protection, andevaluate the patterns of non-native plant species on thelandscape.Double sampling techniques use satellite imagery,aerial photography, and field data to stratify homogeneous andheterogeneous units and keystone ecosystems (ecosystems thatcontain or support a high number of species or have distinctivespecies compositions). We show how a multi-scale vegetationsampling design, species-area curves, analyses of within- andbetween-vegetation type species overlap, and geographic informationsystem (GIS) models can be used to quantify landscape-scalepatterns of vascular plant diversity in the Park.The new multi-scale vegetation plot techniques quickly differentiated plantspecies differences in paired study sites. Three plots in the OuzelBurn area (burned in 1978) contained 75 plant species, while only17 plant species were found in paired plots outside the burn.Riparian areas contained 109 plant species, compared to just 55species in paired plots in adjacent forests. However, plant speciesrichness patterns inside and outside elk exclosures were morecomplex. One elk exclosure contained more species than its adjacentopen range (52 species inside and 48 species outside). Two elkexclosures contained fewer species inside than outside (105 and 41species inside and 112 and 74 species outside, respectively).However, there was only 26% to 48% overlap (using Jaccard'sCoefficient) of plant species composition inside and outside theexclosures. One elk exclosure had 13% cover of non-indigenousspecies inside the exclosure compared to 4% outside, butnon-indigenous species cover varied by location.We compared plantdiversity patterns from vegetation maps made with 100 ha, 50 ha, 2ha, and 0.02 ha MMU's in the 754 ha Beaver Meadows study area usingfour 0.025 ha and twenty-one 0.1 ha multi-scale vegetation plots.Preliminary data suggested that the 2 ha MMU provided an accurateestimate of the number of plant species (–14%) for a study area,but the number of habitats (polygons) was reduced by 67%, andaspen, a unique and important habitat type, was missed entirely. Wedescribe a hypothesis-driven approach to the design andimplementation of geospatial databases for local resourcemonitoring and ecosystem management.     

Prediction of total and rare plant species richness in agricultural landscapes from satellite images and topographic data

The diversity of future landscapes might depend on our ability to predict their potential species richness. The predictability of patterns of vascular plant species richness in a Finnish agricultural river landscape was studied using generalized linear modeling, floristic records from fifty-three0.25-km grid squares in the “core” study area, and environmental variables derived from Landsat TM images and a digital elevation model. We built multiple regression models for the total number of plant species and the number of rarities, and validated the accuracy of the derived models with a test set of 52 grid squares. We tentatively extrapolated the models from the core study area to the whole study area of 601 km² and produced species richness probability maps using GIS techniques. The results suggest that the local ‘hotspots’ of total flora (grid squares with > 200species) are mainly found in river valleys, where habitat diversity is high and a semi-open agricultural-forest mosaic occurs. The ‘hotspots’ of rare species (grid squares with > 4 rare species) are also found in river valleys, in sites where extensive semi-natural grasslands and herb-rich deciduous forests occur on steep slopes. We conclude that environmental variables derived from satellite images and topographic data can be used as approximate surrogates of plant species diversity in agricultural landscapes. Modeling of biological diversity based on satellite images and GIS can provide useful information needed in land use planning. However, due to the potential pitfalls in processing satellite imagery and model-building procedures, the results of predictive models should be carefully interpreted. This revised version was published online in July 2006 with corrections to the Cover Date.     

Forty-eight years of landscape change on two contiguous Ohio landscapes

This study analyzes the current and historic structure of two contiguous, rural landscapes covering approximately 242 km² in central Ohio, USA: a till plain landscape with relatively homogeneous topography and soils, and a moraine landscape with greater geomorphological diversity and heterogeneity. These landscapes were chosen because they were both heavily dominated by agriculture during 1900–1940 and were both initially surveyed by the metes-and-bounds system. They differed, however, in the temporal pattern of settlement and development and in the inherent agricultural capability of their soils. We combined analysis of aerial photographs from 1940, 1957, 1971, and 1988 with historical archives and other available mapped data in a GIS data base to facilitate analysis of both spatial and temporal patterns of change. On the moraine, the agricultural matrix decreased over time as forest, urban/suburban areas, and industry increased. In contrast, on the till plain agricultural landcover increased through 1988, with concommitant decreases in upland forest and oak savanna. The moraine landscape exhibited greater diversity and equitability than the till plain on each date. The till plain had its greatest diversity and equitability in 1940, whereas the moraine increased in diversity and equitability during each time period. The undulating topography of the moraine encouraged landcover dynamism rather than stability, whereas the more homogeneous till plain exhibited considerable inertia. Patch and matrix shape remained constant and predominantly angular over the 48 year study period. Differences in the physical environment, especially topography and soil capability, and the socioeconomic environment, especially agricultural policies and patterns of urbanization, resulted in these two contiguous landscapes having different trajectories of change. It is clear from this study that socioeconomic factors must be combined with the physical setting to fully understand patterns of change in human-dominated landscapes.     

Fractals and search paths in mammals

The fractal index by Katz and George (1985) for thecharacterization of planar curves is applied to wolf search pathsrecorded by radio-telemetry. All the sets of paths studied showspatial patterns whose complexity is between a straight line anda true random walk. Females fractal dimensions show significantchanges throughout the year, depending on the state of their lifecycle (normal, breeding and wandering). There are alsodifferences between males and females, but not between adults andnon-adults. The results are discussed with regard to wolffood-search strategies.     

Relationships between a terrain-based hydrologic model and patch-scale vegetation patterns in an arctic tundra landscape

Implicit in the relationship between vegetation patterns and landforms is the influence of topography on the water regime at the patch scale. Hence, based on the numerous process-based studies linking plant structure and function to water in the arctic, we hypothesize that the general pattern of arctic landscapes can be explained by a mesotopographic variable such as water drainage. In this paper, we test this hypothesis by examining the spatial relationship between patterns of vegetation and the water regime in a small watershed in northern Alaska. Using gridded elevation data, we develop a model (T-HYDRO) to generate a 2-dimensional water flow field for the watershed and compare this to vegetation patterns as given by 1) a vegetation map developed from aerial photographs in conjunction with extensive field sampling; and 2) a normalized difference vegetation index (NDVI). Our results show that it is possible to account for about 43% of the spatial variance in NDVI, which supports our hypothesis. In spite of its limitations, the correspondence of patterns presented in this paper provides encouraging evidence that we can find simple approaches to stratify landscapes and that it is possible to overcome the frequently made assumption of spatial homogeneity in ecosystems modeling.     

Grassland songbird occurrence on remnant prairie patches is primarily determined by landscape characteristics

Context

North American grassland songbird populations have declined significantly due to habitat loss and fragmentation. Understanding the influence of the surrounding landscape on prairie fragment occupancy is vital for predicting the fate of grassland birds in these heavily altered landscapes.

Objectives

We examined the relative importance of local and landscape variables on grassland bird occupancy of prairie fragments using a focal-patch study. We also investigated the spatial scale at which landscape variables were most influential.

Methods

We surveyed birds on 29 unplowed prairie fragments in western Minnesota and eastern North and South Dakota. We quantified local habitat on the fragment using vegetation surveys and aerial photographs and the landscape surrounding the fragment out to 4 km using aerial photographs. We analyzed occupancy using multi-model approaches applied to multiple logistic regression.

Results

Of 38 species encountered, nine were neither too rare nor too abundant to be analyzed. Predictors of patch occupancy were unique for each bird species, yet general patterns emerged. For eight species, landscape variables were more important than local variables. Mostly, those landscape variables measured configuration (e.g., edge density) and not composition (e.g., percent cover of a particular matrix element). Landscape effects were mostly from variables measured at the greatest extents from the prairie fragment.

Conclusions

Using a focal-patch study design we demonstrated the importance of the surrounding landscape, often out to 4 km from the fragment edge, on prairie occupancy by grassland birds. Effective management of grassland songbirds will require attention to the landscape context of prairie fragments.

     

Influence of within-field and landscape factors on aphid predator populations in wheat

The influence of prey density, within-field vegetation, and the composition and patchiness of the surrounding landscape on the abundance of insect predators of cereal aphids was studied in wheat fields in eastern South Dakota, USA. Cereal aphids, aphid predators, and within-field vegetation were sampled in 104 fields over a three year period (1988–1990). The composition and patchiness of the landscape surrounding each field were determined from high altitude aerial photographs. Five landscape variables, aggregated at three spatial scales ranging from 2.6 km² to 581 km², were measured from aerial photographs. Regression models incorporating within-field and landscape variables accounted for 27–49% of the variance in aphid predator abundance in wheat fields. Aphid predator species richness and species diversity were also related to within-field and landscape variables. Some predators were strongly influenced by variability in the composition and patchiness of the landscape surrounding a field at a particular spatial scale while others responded to variability at all scales. Overall, predator abundance, species richness, and species diversity increased with increasing vegetational diversity in wheat fields and with increasing amounts of non-cultivated lands and increasing patchiness in the surrounding landscape.     

How is Shrub Cover Related to Soil Moisture and Patch Geometry in the Fragmented Landscape of the Northern Negev desert?

Among the major challenges of landscape ecologists is to develop relatively simple models to quantify ecological processes over large areas. Application of such models can be well demonstrated in fragmented semi-arid ecosystems where competition over resources is intense due to habitat loss, however, only a few studies have done so. Our aim was to model and study the integrated effect of spatial variation in potential soil moisture and patch size and shape on shrub–grass ratio (SGR) in a semi-arid fragmented environment. We specifically ask: (i) what factors most strongly relate to SGR in large remnant patches (> 1.6 ha), and (ii) do different factors more strongly relate to SGR in small patches (< 1.6 ha)? The study was carried out using 60 patches within a semi-arid fragmented environment in the Northern Negev of Israel. Aerial photographs and digital elevation models were used to map six environmental variables: wetness index, aspect, rock cover, rock pattern, patch area, and patch shape. The variables were designed in GIS and were modeled using fuzzy logic procedures to predict SGR, and these predictions were compared to shrub cover maps extracted using maximum likelihood classification of aerial photographs taken in September 2003. We found that in the study area, factors indicating potential soil moisture are most strongly related to SGR in large patches, whereas patch geometric attributes are more strongly relate to SGR in small patches.