Patterns and Processes — Part I, 19 January 2015
Landscape ecology studies the interactions between ecological processes and spatial patterns within landscapes. A landscape is defined as “an area that is spatially heterogeneous in at least one factor of interest (such that spatial patterns influence ecological processes).” Therefore, a homogenous area cannot be a landscape.
Pattern and scale are central problems in landscape ecology. For example, there is no single natural scale at which ecological phenomena should be studied. In order to determine process and pattern, the form of the landscape must first be examined. This will help to describe the processes, as form is a function of process. Once we understand the processes, we can determine patterns.
Processes can be categorized as biotic (e.g. keystone species), abiotic (e.g. climate), and disturbance (e.g. fire). Within this, they can be divided into natural and non-natural, determined by whether the process occurs in nature or as a result of human activity. Analyzing processes can be difficult because multiple processes can occur at different temporal and spatial scales. As well, many systems are complex: there are so many factors that you cannot predict results simply by looking at the parts. The interactions between those parts can include emergent behavior, self-organization, hierarchies, and chaos.
Patterns form as a result of spatial effects. Spatial dependence, scale-dependent response, and spatial autocorrelation all affect the way organisms, environment, and space interact. Patterns can be first-order or second-order. First order processes, such as slope, form in response to some environmental factor. Second-order processes, such as seed dispersal, form in response to interactions with events or objects.
Stationarity is another possible feature of landscapes. Stationarity is the absence of change over space. In first-order stationarity, there is “no variation in the intensity over space.” In second-order stationarity, there is “no interaction between objects/events.” The existence of stationarity implies a lack of directional bias. If there is no directional bias, processes are isotropic. If there is a directional bias, however, processes are anisotropic.