A scaled, contextual perspective of woody structure and dynamics across a savanna riperian landscape
Levick, Shaun Robert
Sound understanding of the influence of scale and context on ecological patternprocess relationships is lacking in many systems. The hierarchical patch dynamics paradigm (HPDP) provides a framework for addressing spatio-temporal heterogeneity, but the range of systems in which, and scales at which, its principles apply are largely unknown. Furthermore, it does not explicitly account for the influence of spatial context. Recent developments in remote sensing science show potential for bridging this gap by enabling the exploration of landscape heterogeneity at multiple scales and across a wide range of systems and contexts, but the ecological application of these new techniques is lagging. The savanna riparian landscapes of the northern Kruger Park, South Africa, provided a unique platform in which to explore the influence of spatial context, and to test the pattern-process-scale and metastability principles of the HPDP, to further its potential as a unifying framework in landscape ecology. LiDAR and high-resolution aerial imagery were integrated through object-based image analysis to create spatial representations of woody structure (canopy height, canopy cover, canopy height diversity and canopy cover diversity) across a portion of the savanna landscape (60 000ha). Temporal change in woody cover and heterogeneity (number and size of woody patches) was assessed from a historical aerial photography record, that spanned 59 years from 1942 to 2001. Spatial relationships between environmental variables and patterns of woody structure and dynamics were tested at broad (100ha), medium (10ha) and fine-scales (1ha) through canonical correspondence analysis (CCA). The relative contribution of different categories of environmental variables, to the total explained variation in woody structure, was assessed at each scale through partial canonical correspondence analysis (PCCA). Spatial variation in environmental variables, and the influence of spatial context on woody structure-environment relationships, was explicitly tested through geographically weighted regression (GWR). LiDAR results provided an unprecedented basis from which to explore spatial patterns of woody structure in an African savanna. Standard approaches to generating normalized canopy models (nCM) from LiDAR suffered interpolation artifacts in the heterogeneous landscape, but an object-based image analysis technique was developed to overcome this shortfall. The fusion of LiDAR with aerial imagery greatly enhanced the structural description of the landscape, and the accuracy of canopy height estimates varied between different vegetation patch types. Woody structure and dynamics displayed distinct spatial trends across the landscape with high diversity and variability occurring in the alluvial riparian zones. Woody canopy height, canopy cover and cover dynamics exhibited scale variance in their relationship with environmental variables, but woody structural diversityenvironment relationships were scale invariant across the analysis patch hierarchy. These findings from different woody attributes both support and contradict the pattern-process-scale principle of the HPDP, which hypothesizes that ecological processes shift with scale, but that spatial variance measures exhibit stepwise patterns of change with scale, along a patch hierarchy. Percentage woody cover was stable over time across the landscape, despite high variability at smaller scales. However the metastability principle cannot be considered generally applicable in this system, as a broader view of the woody component revealed a marked decline in woody heterogeneity over time. Although losses of woody cover on the diverse alluvial substrates were countered by increases of cover in the uplands, analysis of current woody structure in the context of historical change revealed that the increases took place in the form of shrub encroachment and not the replacement of tall trees. The vertical structure of woody vegetation, and therefore both the biodiversity and ecological functioning of the system, has changed over time across the landscape. The metastability principle of theHPDP may not be applicable in spatially heterogeneous systems, where ecological processes act differentially across the landscape, but may apply within specific patch types at certain temporal scales. Spatially localized analysis models revealed significant spatial non-stationarity in the majority of processes correlated with woody structure, and showed that both the magnitude and direction of woody structure-environment relationships varied in different spatial contexts across the landscape. These results have fundamental implications for the manner in which both science and conservation measures are conducted in heterogeneous systems. Global analysis models, that assume stationarity, are widely accepted and employed in ecological research but may greatly misrepresent ecological relationships that are context-dependent. These findings question the level of system understanding that field studies can provide, by revealing the dangers of inferring patterns and relationships from measurements of limited spatial representation. Leveraging the latest remote sensing technologies, that provide large-extent but fine-grain coverage, in a scaled and context conscious manner, will enhance ecological understanding by spatially quantifying the full spectrum of system heterogeneity. The heterogeneous patterns, scaled relationships and context-dependent patterns identified in this study are challenging from both ecological research and biodiversity conservation points of view. Traditional approaches to science and conservation are ill equipped to address these issues. The HPDP provides an excellent conceptual construct for meeting such challenges, but the influence of spatial context needs to be more explicitly incorporated within the framework. A catchment-based hierarchy is suggested for guiding future research and conservation efforts in heterogeneous landscapes, where context-dependency of ecological processes may be the norm.