Objective 5:To identify the strengths and weaknesses of the model and the strategy/ processes used
The model was expected to show vulnerability hotspots of Eastern Hemlock groves in Canada based on the distance from roads, road size, distance from current HWA distribution, and temperature. The strengths of the MCE model included its ability to incorporate these four different criteria which each affected spread in their own way into one equation. This allowed for a more precise output of susceptibility to spreading through the consideration of more than one factor affecting the risk of spread of HWA. In addition, the model allowed for the prediction of future spread under two different climate scenarios rather than just one, which was favorable for management planning and prevention measures in order to protect Canada’s hemlock groves. The susceptibility to spreading was then applied to Hemlock Density to identify the vulnerability of individual Hemlock groves, and this method was efficient in identifying specific areas of hemlock groves under high vulnerability. Ultimately, the strengths of our model were its ability to consider and incorporate the most important factors influencing the spread of HWA, its potential to predict and compare two different spread scenarios, and its use in identifying areas under the highest vulnerability in order to organize monitoring efforts and prioritize management resources.
However, hemlock data available for Canada was limited, and the layer used is a raster dataset which shows hemlock density per 50 km2. This dataset ranges from 1-50 trees per pixel, so the information was not as specific as was hoped, although it does cover the Eastern Canadian provinces as was required for the research question. It would have been beneficial to have a more complete and detailed hemlock dataset in order to incorporate hemlock hardiness due to shade and slope, as these hemlock trees may be more likely to withstand an HWA invasion (Paradis et al. 2007). Another weakness to the model was the factors that the multi-criteria analysis was based off are limited by the data available. For example, Hemlock Woolly Adelgid is also spread by wind and migratory birds vectors and constrained by habitat heterogeneity (Paradis et al. 2007). However, there was limited data available for these factors, and they would significantly complicate the analysis. Therefore, although the model efficiently incorporated spread by humans through roads as well as spread limitations based on climate change, it missed some factors which facilitate the spread. Finally, the model analyzed at a coarser resolution in order to process the spread and vulnerability at the large scale of Eastern North America. This means that if governments are looking at managing individual hemlock groves rather than general hot spots and areas of high vulnerability in Eastern Canada, the information provided by the model may serve as a general guideline for these purposes rather than a detailed resource.