John M. Thomas

A comparison of quantitative methods for examining landscape pattern and scale

Ecologists have long recognized the importance of spatial and temporal patterns that characterize heterogeneity in landscapes. However, despite the realization that inferences about ecological phenomena are scale dependent, little attention has been paid to determining appropriate scales of measurement (e.g., plot or grain size) in studies of landscape dynamics or ecosystem change. This paper compares the results from three data sets using several quantitative methods available for characterizing landscape heterogeneity and/or for determining scale of measurement. Methods evaluated include tests of non-randomness, estimation of patch size, spectral analysis, fractals, variance ratio analysis, and correlation analysis. The results showed that no one method provides consistently good estimates of scale. Thus, sampling strategies for landscape studies should be derived from estimates of patch size and/or scale of pattern obtained from more than one of these methods.

Multiple landscape scales: An intersite comparison

Vegetation transect data from three locations were analyzed to determine if multiple scales of pattern could be detected. The sites included a semiarid grassland in New Mexico, a series of calcareous openings in a deciduous forest in Tennessee, and a shrub-steppe system in Washington. The data were explored with four statistical techniques. A scale of pattern was accepted if detected by more than one analytical method or located by a single method in multiple taxa. The analyses indicated 3–5 scales of pattern on all three sites, as predicted by Hierarchy Theory.

Determination of ecological scale

We suggest that ecological processes and physical characteristics possess an inherent scale at which the processes or characteristics occur over the landscape. We propose a conceptual spatial response model that describes the nature of this ecological scale. Based on the proposed spatial model, we suggest methods for estimating the size of study plots or transects and the distance between replicate plots needed to approach statistical independence. Using data on percent cover for Agropyron spicatum, a common arid-land bunchgrass, we demonstrated four relationships that should hold if the spatial response model is appropriate. These relationships are sample variance increases as functions of (1) transect segment length and (2) intersegment length (transect segment dispersal), and correlation decreases as functions of (3) intersegment length and (4) transect segment length. Based on evaluation of these four relationships, cover for A. spicatum is correlated over the landscape on a scale of 400 to 700 m, and a segment length of 64 to 128 m is most appropriate for measuring cover for this species.

Field calibration of soil-core microcosms: Fate of a genetically altered rhizobacterium

Microcosms containing intact soil-cores are a potential tool for assessing the risks of the release of genetically engineered microorganisms (GEMs) to the environment. Before microcosms become a standard assessment tool, however, they must first be calibrated to ensure that they adequately simulate key parameters in the field. Four systems were compared: intact soil-core microcosms located in the laboratory at ambient temperature and in a growth chamber with temperature fluctuations that simulated average conditions in the field, field lysimeters, and field plots. These four systems were inoculated with rifampicin-resistantPseudomonas sp. and planted to winter wheat. Populations of thePseudomonas sp. in soil decreased more rapidly at ambient temperature, but population size at the three-leaf stage of wheat growth was the same in all four systems. Populations of thePseudomonas sp. on the rhizoplane of wheat were the same at the three-leaf stage in all four systems, and colonization with depth at the final boot stage-sampling was also similar. In general, microcosms incubated at ambient temperature in the laboratory or in the growth chamber were similar to those in the field with respect to survival of and colonization of the rhizoplane by the introducedPseudomonas sp.

Field Calibration of Soil-Core Microcosms: Ecosystem Structural and Functional Comparisons

Microcosms containing intact soil-cores are a potential biotechnology risk assessment tool for assessing the ecological effects of genetically engineered microorganisms before they are released to the field; however, microcosms must first be calibrated to ensure that they adequately simulate key field parameters. Soil-core microcosms were compared with the field in terms of ecological response to the introduction of a large inoculum of a rifampicin-resistant rhizobacterium,Pseudomonas sp. RC1. RC1 was inoculated into intact soil-core microcosms incubated in the laboratory at ambient temperature (22°C) and in a growth chamber with temperature fluctuations that mimicked a verage field values, as well as into field lysimeters and plots. The effect of the introduced bacterium on ecosystem structure, including wheat rhizoplane populations of total and fluorescent pseudomonads, total heterotrophic bacteria, and the diversity of total heterotrophic bacteria, was determined. Fluorescent pseudomonads were present on the rhizoplane in significantly lower numbers in soil inoculated with RC1, in both microcosms and the field. Conditions for microbial growth appeared to be most favorable in the growth chamber microcosm, as evidenced by higher populations of heterotrophs and a greater species diversity on the rhizoplane at the three-leaf stage of wheat growth. Ecosystem functional parameters, as determined by soil dehydrogenase activity, plant biomass production, and15N-fertilizer uptake by wheat, were different in the four systems. The stimulation of soil dehydrogenase activity by the addition of alfalfa was greater in the microcosms than in the field. In general, growth chamber microcosms, which simulated average field temperatures, were better predictors of field behavior than microcosms incubated continuously at 22°C.

A Bayesian test of hierarchy theory: scaling up variability in plant cover from field to remotely sensed data

Hierarchy theory predicts that a hierarchy of process rates should be reflected in a hierarchy of spatial and temporal scales observable on the landscape. We will show that multiple scales of pattern for total plant cover measured in the field at 1-m resolution are correlated with scales of vegetative pattern obtained from remotely sensed data with resolutions of 25 m2 and 30 2. Second, using four models based on postulates of hierarchy theory, we will combine the scales of pattern of each individual species within a community to estimate the remotely sensed community scales of pattern. Finally, we will compare the four models using a Bayesian analysis to determine which model best portrays how vegetative patterns of individual species combine to produce remotely observed community patterns. The results of the model comparisons provide an example of how postulates of hierarchy theory can be tested and how individual species patterns can be scaled-up to estimate remotely observed scales of pattern.

Satellite imagery as a tool to evaluate ecological scale

Methods for detecting scale and dispersion of plant cover developed by Carilieet al. (1989,Landscape Ecology 2: 203–213) were adapted to information obtained from satellite imagery. Scales were found to be on the order of 100 m in the shrub-steppe area of southeastern Washington. General agreement between the remotely sensed data and plant cover using the variance and correlation methods of Carlileet al. indicate that remote sensing information can be used in the design of field studies for measuring the processes controlling plant cover in semi-arid areas; the agreement also suggests that the methods have broad applicability in the determination of scale and dispersion.