Landscape Ecology and Quantitative StratigraphyParallel Perspectives on Spatial Heterogeneity

Author(s):  
Roy E. Plotnick
Author(s):  
Kimberly A. With

Heterogeneity is a defining characteristic of landscapes and therefore central to the study of landscape ecology. Landscape ecology investigates what factors give rise to heterogeneity, how that heterogeneity is maintained or altered by natural and anthropogenic disturbances, and how heterogeneity ultimately influences ecological processes and flows across the landscape. Because heterogeneity is expressed across a wide range of spatial scales, the landscape perspective can be applied to address these sorts of questions at any level of ecological organization, and in aquatic and marine systems as well as terrestrial ones. Disturbances—both natural and anthropogenic—are a ubiquitous feature of any landscape, contributing to its structure and dynamics. Although the focus in landscape ecology is typically on spatial heterogeneity, disturbance dynamics produce changes in landscape structure over time as well as in space. Heterogeneity and disturbance dynamics are thus inextricably linked and are therefore covered together in this chapter.


Author(s):  
Jon Moen ◽  
Tarja Oksanen ◽  
Nancy Huntly

Landscape ecology has been very influential in developing tools for describing both structure (e.g. the distribution and sizes of patches) and function (i.e. the flow among patches) of heterogeneous environments (Turner 1989, Turner & Gardner 1991). This approach has shown that spatial heterogeneity on a landscape level may influence many types of ecological processes (Kolasa & Pickett 1991, Wiens et al. 1993). However, it is also clear that landscape structure and function must be described from an organism-centered view (Kolasa & Pickett 1991), which invites the use of population dynamic hypotheses, and presents the challenging task of merging population ecology with landscape ecology. Standard, non-spatial, predator-prey models predict that the grazing pressure in a given area is related to primary productivity (Oksanen et al. 1981). The model assumes that the number of dynamically important trophic levels is dependent on primary productivity and, in its simplest form, it can be outlined as follows: In extremely unproductive areas (e.g. boulder-fields), plant biomass is too low to sustain mammalian herbivores. In undisturbed areas, plants will thus eventually deplete their resources and compete. In moderately productive areas (e.g.arctic and alpine heaths), plant production is high enough to sustain herbivores, albeit at low densities, lower than what is needed for efficient predators to have a positive growth rate. Uncontrolled by predation, these herbivores are predicted to exert a strong grazing pressure on the vegetation. In more productive areas (e.g. tall herb meadows), plant production is high enough to sustain both herbivores and predators. With herbivores controlled by predation, plants will experience a low grazing pressure, and competition will be an important structuring factor for the plants. According to these models, a productivity gradient from extremely barren areas to productive areas should contain a zone of strong grazing pressure at intermediate productivities. A re­analysis using two types of patches with different primary productivity (T. Oksanen 1990) shows that the exact predictions depend on the proportion of these two patches in the habitat. Predation pressure could be high (and thus grazing pressure low) in a patch of intermediate productivity if it is embedded in a matrix of more productive patches, and, reversely, a productive patch might have a high grazing pressure if it is embedded in a matrix of less productive patches. These predictions parallel those of the source-sink model of Pulliam (1988) where a habitat where the consumer has a high growth rate "exports" juveniles to a habitat where the consumer growth rate is lower or even negative, thus creating a higher grazing pressure in the latter habitat than would have been possible without this continuous restocking of individuals. The general conclusion from these models is that grazing pressure may vary between patches both as a consequence of differences in productivity and also because of the spatial arrangements of patches. Any comprehensive understanding of the interactions between herbivores and plants in a heterogeneous environment must thus be based on experiments and observations that explicitly take the spatial heterogeneity of the study area into account.


Science ◽  
1995 ◽  
Vol 269 (5222) ◽  
pp. 331-334 ◽  
Author(s):  
S. T. A. Pickett ◽  
M. L. Cadenasso

Author(s):  
Clélia Sirami

Although the concept of biodiversity emerged 30 years ago, patterns and processes influencing ecological diversity have been studied for more than a century. Historically, ecological processes tended to be considered as occurring in local habitats that were spatially homogeneous and temporally at equilibrium. Initially considered as a constraint to be avoided in ecological studies, spatial heterogeneity was progressively recognized as critical for biodiversity. This resulted, in the 1970s, in the emergence of a new discipline, landscape ecology, whose major goal is to understand how spatial and temporal heterogeneity influence biodiversity. To achieve this goal, researchers came to realize that a fundamental issue revolves around how they choose to conceptualize and measure heterogeneity. Indeed, observed landscape patterns and their apparent relationship with biodiversity often depend on the scale of observation and the model used to describe the landscape. Due to the strong influence of island biogeography, landscape ecology has focused primarily on spatial heterogeneity. Several landscape models were conceptualized, allowing for the prediction and testing of distinct but complementary effects of landscape heterogeneity on species diversity. We now have ample empirical evidence that patch structure, patch context, and mosaic heterogeneity all influence biodiversity. More recently, the increasing recognition of the role of temporal scale has led to the development of new conceptual frameworks acknowledging that landscapes are not only heterogeneous but also dynamic. The current challenge remains to truly integrate both spatial and temporal heterogeneity in studies on biodiversity. This integration is even more challenging when considering that biodiversity often responds to environmental changes with considerable time lags, and multiple drivers of global changes are interacting, resulting in non-additive and sometimes antagonistic effects. Recent technological advances in remote sensing, the availability of massive amounts of data, and long-term studies represent, however, very promising avenues to improve our understanding of how spatial and temporal heterogeneity influence biodiversity.


2014 ◽  
Vol 1014 ◽  
pp. 387-390
Author(s):  
Wei Xiao

Spatial structure of landscape ecology is composed by different ecosystems, the interaction function and dynamics. It is to the entire landscape as the research object, emphasizing the interaction between the protection and management of large areas of population ecology, management of environmental resources and human activities spatial heterogeneity of the maintenance and development, ecosystem and its components on the landscape impact. This paper presents several models of several computer-aided digital design environments, and the depth of the concrete application of various models.


2015 ◽  
Vol 2 (1) ◽  
pp. 50-59
Author(s):  
V. Medvedev

Aim. To consider soil continuality and discreteness as features of heterogeneity manifestation in a soil cover, important for construction of agriculture systems. Methods. Geostatistical research of soil spatial heterogeneity, revealing the contours of a fi eld with various parameters of fertility. Results. The use of principles of precise agriculture and inspection of indicative properties of fi eld soils using a regular grid allowed to divide a fi eld into contours with three levels of fertility: the fi rst one is characterized by optimal or close to optimum properties which allows refusing from (or reducing substantially) tillage, introduction of fertilizers or chemical ameliorates; the second one has average parameters of fertility corresponding to zonal soils and demands the application of zonal technologies; the third one (with the worst parameters of fertility) presupposes regular use of the improved technologies. Conclusions. The introduction of precise agriculture will allow replacing a traditional zonal system with thenew which is soil-protecting and resource-saving one.


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