Managers, planners and researchers working with invasive species need maps of the distribution and abundance of the invaders. They use distribution data in different ways to address a wide range of questions. Unfortunately, available distribution data is not always particularly useful. One reason for this is that insufficient thought is given to deciding on the spatial resolution for the initial mapping. New insights have emerged from recent collaborative research involving the C·I·B, South African National Parks, and the South African National Biodiversity Institute.
Few studies have evaluated the processes and patterns of invasion from the initial founder population to the point where all potentially invasible habitats have been “sampled” by the invading species. Furthermore, only a small proportion of invasion studies focus on the initial stages of dispersal; most deal with widespread and advanced invasions. Invading plants also have spatial and temporal dynamics that are difficult to predict, frequently expanding their distribution from extremely low numbers in source populations, often through rare dispersal events. Our ability to predict ecological phenomena such as patterns of alien plant distribution, and thus infer ecological processes, depends on the relationship between spatial and temporal scales of variation. With an increase in spatial scale (increasing coarseness of grain), important processes operate at longer time scales, time lags are longer, and indirect effects become increasingly important. Also, understanding patterns of invasions is also a function of both the extent (the overall area of the investigation) and the grain of the investigation. Various components of scale (time, extent and grain) of the investigation therefore determine the range of patterns that we detect and the explanations we can derive from them. Studies on biological invasions that integrate across different scales are rare because of the difficulties of collecting enough data over a sufficiently large area, and capturing infrequent, long-distance dispersal events, with which to explore these problems. Invasive species rarely disperse across the landscape in a continuous front, and opportunistic dispersal events, or secondary invasion foci, are frequently disproportionally important in driving spatial expansion. If distributions are mapped at a fine grain, such small outlying patches, which may be crucial invasion foci, can be identified, whereas such essential information is lost at a coarse grain. Different types of information are captured in data recorded at different spatial scales, and scaling up or down for specific purposes is problematical. Fine-scale mapping is expensive, so a key question is: at what scale should mapping be done to provide data that can be used for multiple purposes at a reasonable cost?
The above issues were addressed using a unique database of occurrence records mapped at a very fine scale in South Africa’s flagship protected area. With 27,000 spatially-explicit records, this data set for the Kruger National Park (KNP; > 20,000 km2 in extent), is probably the most detailed distribution data for invasive plants for any large protected area anywhere in the world. Most of the data were collected using an innovative system called CyberTracker. This system comprises customised software used in conjunction with a personal digital assistant (PDA) and the Global Positioning System (GPS). Rangers capture spatially-explicit data during routine patrols in the park, ensuring very thorough coverage.
Interesting patterns emerged when species richness of invasive plants was assessed at nine different scales of resolution. Almost identical results were obtained when maps were generated from data aggregated to the quarter-degree grid and quaternary watershed (the fourth level category in South Africa’s river-basin classification system) scale. Patterns produced when working at resolutions of 0.1–0.5 km and 1–5 km cells were also similar. An important finding was that at a scale of 0.1 x 0.1 km cells only 0.4% of the Kruger National Park is invaded, whereas > 90% of the park is invaded when mapped at the quarter-degree cell resolution.
Although there was a difference in the effort expended on mapping different species, assessing the distribution of the most abundant species provides interesting insights. For example, when assessed at a fine scale, the distribution of Opuntia stricta (an invasive alien cactus, widespread around Skukuza) can be clearly related to the Skukuza village, allowing for informative reconstruction of the invasion trajectory [read about this work]. Parthenium hysterophorus (an invasive alien herb, widespread in the south-western region of KNP) is clearly associated with roads at a fine scale, but the strength of this association, which is crucial for understanding and managing the species, is lost at coarser scales. The close association between the distribution of Lantana camara (invasive alien woody shrub) and the location of rivers in KNP is another example.
Selecting the appropriate scale of resolution is crucial when evaluating the distribution and abundance of alien plant invasions, understanding ecological processes, and operationalizing management applications and monitoring strategies. Data at quarter-degree or quaternary-watershed resolution are adequate for generating regional- or national-scale maps that are useful for strategic planning. Grid cells of 1 to 25 km2 are generally adequate for establishing priorities for and planning management interventions. Fine-scale data are, however, required for informing management in areas which are small in extent; they also provide the detail required for determining patterns and rates of invasion.
The fine-scale data from the CyberTracker system provide the flexibility to map distributions at multiple scales, each of which can be utilized to address particular questions.
Foxcroft, L.C., Richardson, D.M., Rouget, M. & MacFadyen, S. (2009) Patterns of alien plant distribution at multiple spatial scales in a large national park: implications for ecology, management and monitoring. Diversity and Distributions 15: 367–378.