Scaling and Complexity in Landscape Ecology - Newman, Erica A.; Kennedy, Maureen C.; Falk, Donald A.; McKenzie, Donald (Frontiers in Ecology and Evolution, 2019)
Landscapes and the ecological processes they support are inherently complex systems, in that they have large numbers of heterogeneous interacting components, interact in multiple ways, and exhibit scale dependence, non-linear dynamics, and emergent properties. The emergent properties of landscapes encompass a broad range of processes that influence biodiversity, ecosystem processes, and human environments. These properties, such as nutrient cycling, dispersal, evolutionary adaptation of organisms to their environments, and the focus of this article, ecological disturbance regimes (including wildfire), operate at scales that are relevant to human societies, but these are also often the scales at which ecosystem dynamics are most difficult to understand and predict. Modeling processes and interactions at the landscape scale, including future states of biological communities and their interactions with each other and with processes such as landscape fire, requires quantitative metrics and algorithms that minimize error propagation across scales. We identify three intrinsic limitations to progress in landscape ecology, and ecology in general: (1) the problem of coarse-graining, or how to aggregate fine-scale information to larger scales in a statistically unbiased manner; (2) the middle-number problem, which describes systems with elements that are too few and too varied to be amenable to global averaging, but too numerous and varied to be computationally tractable; and (3) non-stationarity, in modeled relationships or parameter choices that are valid in one environment but may not hold when projected onto future environments such as a warming climate. We illustrate these challenges with examples drawn from the context of landscape ecology and wildfire. Quantitative scaling relationships are the key to moving forward, and we review recent progress and paths to developing scaling laws in landscape ecology. We incorporate concepts of compression of state spaces from complexity theory to suggest ways to overcome the problems presented by coarse-graining, the middle-number domain, and non-stationarity.