Detecting Process from Snapshot Pattern: Lessons from Tree Spacing in the Southern Kalahari

Abstract

The spatial distribution of plants is often thought to be an indicator of underlying biotic and abiotic processes. However, there are relatively few examples of spatial patterns being analysed to detect an underlying ecological process. Using the spacing patterns being analysed to detect an underlying ecological process. Using the spacing of savanna trees in the southern Kalahari as an example, we applied methods of computer simulation modelling and point pattern analysis in an evaluation of their potential for identifying relevant pattern generating processes from snapshot pattern. We compared real tree patterns from the southern Kalahari, derived from aerial photographs, with patterns produced from computer simulation experiments in an investigation of the following questions: does the present pattern of tree distributions allow us to characterize (1) the relative importance of the major driving forces (e.g., competition for moisture, grass fire, herbivory), (2) the spatial dimensions and structures of the underlying processes, and (3) the actual dynamic status of the ecological system (a phase of decline, increase or constancy with respect to tree abundance)? The simulation experiments are based on a well established, spatially explicit, grid-based model that simulates the vegetation dynamics of the major life forms under a realistic rainfall scenario of the southern Kalahari and under the impact of grass fires, herbivory and the formation of localized clumps with increased tree seed availability. For a realistic range of parameters the simulation model produces long-term coexistence of trees and grasses with tree densities that correspond with long-term coexistence of trees and grasses with tree densities that correspond with densities observed in the field. Both real tree distributions derived from acrial photographs and tree pattern produced by the model are characterized by a tendency towards even spacing at small scales, clumping at intermediate scales and randomness or clumping at large scales. However, increasing the spatio-temporal correlation in the formation of seed patches in the model caused an increase in the tendency towards clumping in the tree distribution whereas an increase in seed patch numbers led to a decrease in clumping. Within single simulation runs the tree pattern could change in response to the variable rainfall sequences and the corresponding differences in grass fire frequency: periods of slightly increasing tree numbers caused by higher precipitation were characterized by an increase in tree clumping whereas periods of slightly decreasing tree numbers showed a tendency towards random or even tree spacing. Simulating the transition of an open savanna to a savanna woodland showed that the tree pattern in the transitional phase can be diagnostic of the underlying process: If the transition was caused by improved moisture conditions the transitional phase was characterized by increased clumping in the tree pattern. In contrast, a transition caused by an increase in the number of localized tree seed patches led to a characteristic even spacing of trees. Even though the simulated savanna clearly showed non-equilibrium dynamics, simulation results indicate that the tree population in the simulated area of the southern Kalahari is in a state of long-term tree-grass coexistence with the persisting structure of an open savanna system.