For this end, Kuuluvainen (2009) suggested a relatively simple conceptual model of forest dynamics, which separates three major modes of forest dynamics, and incorporates state changes and transitions between the forest dynamics modes depending on changes in disturbance regime.
Key features of the conceptual model illustrated in Fig. 5 are coverage of a wide range of different kinds of forest dynamics and flexibility of state changes between modes of forest dynamics, which can take place when the driving disturbance regime type changes.
Kuuluvainen (2009) introduced a simple conceptual model that is based on distinguishing three main categories or modes of forest dynamics (see also Angelstam and Kuuluvainen 2004, Fig. 5): (1) Even-aged dynamics, driven by repeated stand-replacing disturbances, (2) Cohort dynamics, driven by partial disturbances, and (3) Gap dynamics, driven by tree mortality at fine scale.
Concerning boreal forests, this development led to an adoption of a simple dichotomic concept of two distinct and in space and time alternating cyclic modes of forest dynamics (Fig. 3).
A novel approach is presented for the physical interpretation of the slow and fast modes of process dynamics and the synthesis of multivariable and (or) nonlinear control structures by the use of extensive thermodynamic variables.
It is shown that the occurrence of energy pumping can be identified by studying the dominant K L modes of the dynamics, as well as, the energy distribution among them.
During the Holocene, two primary modes of landscape dynamics have shaped terrestrial Pacific salmon habitats: i) long-term processes as sea levels rose and land rebounded after glacial recession and ii) periodic disturbances of varying frequency and magnitude.
The segmentation gene network produces very robust and conserved output patterns despite fast-evolving upstream inputs through maternal gradients and vastly different modes of segmentation dynamics in different insect taxa (Sander, 1976; Davis and Patel, 2002).
Several research groups are now focused on developing protocols to systematically cross-validate the MSM predictions and obtain MSM parameters using an optimization protocol that produces the best estimate of the few slowest dynamics modes of the protein dynamics.
