Carmela Marangi, IAC-CNR, Italy
A review of the ECOPOTENTIAL paper: C.M. Baker, F. Diele, C. Marangi, A. Martiradonna, S. Ragni, Optimal spatiotemporal effort allocation for invasive species removal incorporating a removal handling time and budget,Natural Resource Modeling,31(4), 2018, doi: 10.1111/nrm.12190.
Invasive species management is one of the most important topics in natural resource management, due to the environmental and economic damage that they cause. A recent report from the European commission estimates that invasive species cost the European Union at least 12 billion per year. This figure includes costs for key economic sectors, as agriculture, fisheries, aquaculture, forestry and health sectors as well as damages and management costs. Moreover, invasive species are also a major cause of global biodiversity loss. Hence, enormous benefits for the hosting ecosystems can be obtained by controlling invasive species or even eliminating them, when feasible and advisable. Unfortunately, this is a costly endeavour which requires careful planning to ensure cost-effectiveness, especially in protected areas, where resources are often too scarce to face all the pressures generated by internal and external drivers. Very often, it is necessary to apply control actions of widespread invasive species again and again, since wind and roads are constantly transferring the infection from outside. It is then of outmost importance to develop cost-effective tools for both monitoring and controlling the spread of the invasive species in a variety of scenarios, potentially including also climate change effects.
Within ECOPOTENTIAL, we combined remote sensing techniques and mathematical modelling to support the control of one of the most invasive species in Europe, the so called tree of heaven (Ailanthus altissima).
The approach, which is a result of a collaboration of CNR (IAC, IIA, ISPA) and colleagues of CSIRO and University of Ferrara, has been tested on the Alta Murgia National Park, where an ongoing LIFE project is carrying out an eradication program, providing data and expert knowledge useful to build up the model. The initial map of presence of Ailanthus altissima, as well as the land cover map of the site, which are input to the model, have been generated by CNR-IIA, by applying remote sensing techniques to time series of very high resolution images. The model developed by CNR and CSIRO is based on a differential equation system and produces the optimal allocation of resource in both space and time, needed to dynamically control the spread of the species. A further relevant assumption of the model is the constraint of a maximum available budget to perform the eradication task.
The model has been implemented in open source software, and the workflow is available on the ECOPOTENTIAL Virtual Lab.