Determining change in distribution and impact of weeds
The current approach to measuring the impact of invasive species is Impact = Abundance x Distribution x Effect. Measuring distribution and abundance is relatively straightforward, but effects are more difficult to quantify or understand.
Effects can be split into two major components: trophic effects (e.g. alteration of food webs, interactions with herbivores, seed dispersers, pollinator networks) and non-trophic effects (e.g. habitat modification, 'ecosystem engineering', biogeochemical effects, alteration of disturbance/fire regime). Improved knowledge of what are the effects and how they should be measured is needed to determine weed impacts in ecosystems. Changes in the distribution and abundance of weeds can be assessed using either permanent vegetation plots or models of invader spread through time. Field-based measurements of weed spread and impact are desirable, but there is a need to forecast future benefits of weed management. We will use both of these approaches to determine changes in the abundance, distribution and effect (i.e. impact) of key weed species.
What we will investigate and how
We will use two interlinked approaches to determine the future impacts of weeds in ecosystems. First, the effects of invaders will be incorporated into spatial models. Models of weed spread exist or are being developed for common weed species in New Zealand (e.g. pines, gorse, broom, hawthorn). These models typically provide information on the distribution and abundance of weeds, but do not include their effects on diversity or ecosystem processes. By linking our field-based research on weed effects or results from long-term vegetation plots w ith spatial models of spread, we can provide a vehicle for forecasting future weed impacts that could be applied over larger scales or paramaterised for additional species. Second, linking measures of weed effects with spatial models of spread will be used to both forecast future impacts and their mitigation through control. This also provides a method for optimising the allocation of resources between weed detection and control.
The central issue addressed in this project is that end-users must make decisions about stopping the spread of invasions or controlling infested sites today within a context of long-term change and preventing future impacts. Weed managers can allocate resources to controlling the distribution or abundance of weeds (but not their effects directly), and hence their impacts. Predicting changes in the distribution and impacts of weeds provides a way of forecasting the future benefits of current weed management. An additional advantage of developing the models above is that effort and economics can be incorporated to evaluate various long-term management scenarios.