Areas Important for Ecological Connectivity Throughout Canada

Governments around the world have acknowledged the importance of conserving ecological connectivity to help reverse the decline of biodiversity. In this study we employed recent methodological developments in circuit theory to conduct the first pan-Canadian analysis of multi-species connectivity for all terrestrial regions of the country, at a spatial grain sufficient to support local land-management decisions. We developed a movement cost surface with a limited number of thematic categories using the most recently updated land cover data available for the country. We divided the country into 17 tiles and used a wall-to-wall, omnidirectional mode of Circuitscape on each tile in order to assess ecological connectivity throughout entire landscapes as opposed to strictly among protected areas. The resulting raw current density map of Canada revealed heterogenous patterns of current density across the country, strongly influenced by geography, natural barriers, and human development. We included a validation analysis of the output current density map with independent wildlife data from across the country and found that mammal and herpetofauna locations were predicted by areas of high current density. We believe our current density map can be used to identify areas important for connectivity throughout Canada and thereby contribute to efforts to conserve biodiversity.

Route planning on orienteering maps with least-cost path analysis

The feature categories of an orienteering map are prepared to allow the map reader to estimate the travel time between any two points on the map with a good approximation. This requires not only an accurate map, but also a key that adapts to the speed of travel. Such map key is developed and maintained by the IOF (International Orienteering Federation), and technically all the orienteering maps are compiled by using it. Estimated time also plays an important role in planning the courses of orienteering races. The course setter estimates time based on a route he thinks is ideal, but the speed of travel is basically a non-linear function of terrain, road network and land cover. Because of this, the easiest (ideal) route between the two points and its time cost can be calculated using the least-cost path (LCP) GIS method, which can be prepared to take into account these three map feature categories. This method is based on the calculation of a cost surface, then the analysis of the ideal path from a given point to the destination. The automation can be adapted to any orienteering map due to the similarities of the map keys. This study shows that if the weight corresponding to the different feature categories is given properly, the ideal path between two points on orienteering maps can be calculated. The ideal path, however is still a subjective category, which may depend on the capabilities and preferences of the orienteer. In this study the routes calculated with the LCP method were compared with the suggestions of the ideal routes by orienteering runners of different ages. The results show that the routes given by sportsmen can be simulated with the LCP method and even the time cost of the calculated routes can be calculated. This study can lay the groundwork for a GIS tool helping the course setting process on standard orienteering maps.

On the effects of spatial resolution on effective distance measurement in digital landscapes

Background Connectivity is an important landscape attribute in ecological studies and conservation practices and is often expressed in terms of effective distance. If the cost of movement of an organism over a landscape is effectively represented by a raster surface, effective distances can be equated with the cost-weighted distance of least-cost paths. It is generally recognized that this measure is sensitive to the grid’s cell size, but little is known if it is always sensitive in the same way and to the same degree and if not, what makes it more (or less) sensitive. We conducted computational experiments with both synthetic and real landscape data, in which we generated and analyzed large samples of effective distances measured on cost surfaces of varying cell sizes derived from those data. The particular focus was on the statistical behavior of the ratio—referred to as ‘accuracy indicator’—of the effective distance measured on a lower-resolution cost surface to that measured on a higher-resolution cost surface. Results In the experiment with synthetic cost surfaces, the sample values of the accuracy indicator were generally clustered around 1, but slightly greater with the absence of linear sequences (or barriers) of high-cost or inadmissible cells and smaller with the presence of such sequences. The latter tendency was more dominant, and both tendencies became more pronounced as the difference between the spatial resolutions of the associated cost surfaces increased. When two real satellite images (of different resolutions with fairly large discrepancies) were used as the basis of cost estimation, the variation of the accuracy indicator was found to be substantially large in the vicinity (1500 m) of the source but decreases quickly with an increase in distance from it. Conclusions Effective distances measured on lower-resolution cost surfaces are generally highly correlated with—and useful predictors of—effective distances measured on higher-resolution cost surfaces. This relationship tends to be weakened when linear barriers to dispersal (e.g., roads and rivers) exist, but strengthened when moving away from sources of dispersal and/or when linear barriers (if any) are detected by other presumably more accessible and affordable sources such as vector line data. Thus, if benefits of high-resolution data are not likely to substantially outweigh their costs, the use of lower resolution data is worth considering as a cost-effective alternative in the application of least-cost path modeling to landscape connectivity analysis.

A Hand Motor Skills Rehabilitation for the Injured Implemented on a Social Robot

In this work, we introduce HaReS, a hand rehabilitation system. Our proposal integrates a series of exercises, jointly developed with a foundation for those with motor and cognitive injuries, that are aimed at improving the skills of patients and the adherence to the rehabilitation plan. Our system takes advantage of a low-cost hand-tracking device to provide a quantitative analysis of the performance of the patient. It also integrates a low-cost surface electromyography (sEMG) sensor in order to provide insight about which muscles are being activated while completing the exercises. It is also modular and can be deployed on a social robot. We tested our proposal in two different facilities for rehabilitation with high success. The therapists and patients felt more motivation while using HaReS, which improved the adherence to the rehabilitation plan. In addition, the therapists were able to provide services to more patients than when they used their traditional methodology.