Using this tool, you can create custom models based on a catalog of over 400 metrics that will help address particular conservation and restoration questions. Some key features:
When deciding how to assign weights, it is important to understand that each weight is a multiplier for its coresponding metric. After the tool standardizes the raw units of a metric to a quantile scale (0-1), it then multiplies that new value by the given weight. Any negative weight is flipped to a positive number and multiplied by the inverse of the metric's quantile score (this is to ensure a positive weighted score that is more intuitive for comparison). For more information, click "How does this work?" in the first panel above.
This control limits the display of both the left and right maps. However, because the maps share the same legend, it can be difficult to distinguish them when parts of each are transparent. To avoid confusion, we recommend that this subset control be used when displaying a single map.
Each rank represents the percent of planning units less than or equal to this rank. As a result, for datasets with very small range (e.g. count of restoration practices in a single year) or limited sample size, there may be many planning units that share the same value (e.g., 0). In some of those cases, the minimum percentile rank could be relatively high and the subset controls may not seem to have an effect. If this appears to be happening, try clicking on a planning unit with a low score color to see what its percentile rank is.