Open oharac opened 4 years ago
fantastic walk-through of methods/process and possible paths forward. I really like the 'for each stressor' option as a way to combine things up
I think the CHI by taxonomic group could get a bit wacky, so I'm not sold on that one yet. although presenting results by taxonomic groups is always a very compelling way to show biodiversity results - this can be done either spatially or not. Maybe the non-spatial path offers some options?? Could calculate the cumulative impact for each species (across its range) and combine them up by taxonomic group and present as bar charts (or similar). We'd also have all those individual maps that we could pick a few key ones from to show.
And maybe there's something we could do with categorizing the CHI within each species spatial range into quantiles and then counting the number of species in any pixel with top or bottom quantile? Or something like that?
Two quick notes:
1) all this process is set up for stressor values, but should also work for trends in stressors. Working at the 10 km res, I can create rasts for each stressor layer for each year and calc trend at the stressor level (rather than the impact level as Mel did - the impacts are so potentially variable from spp to spp and taxon to taxon) and then apply those to spp impact weights. (I could also try to do stressor trends at the 1 km res but seems overkill) 2) I like the quantile idea and will have to think of how that will look. The rescaling of stressors is kinda arbitrary - does a 0.01 SST stressor have the same impact as a 0.01 fishing stressor on a species where the weights are the same? But quantiles within each stressor preserves ranking without relying on an assumption that the rescaled stressors are equivalent...
I'll keep plugging away to create a few maps and tables that we can discuss on Thursday to see what we like.
The Allan et al (2019) paper, "Hotspots of human impact on threatened terrestrial vertebrates", looked at terrestrial spp globally comparing their range extents to the presence/absence of threats. For each spp they could show "impacted" area. From the abstract:
The process:
Here I can do the same for marine species, by identifying for each spp which stressors it's sensitive to, i.e. which stressors cause an "impact" - then creating a spp map for impacted range (any of the stressors "present" and overlapping with range - not a cumulative impact on the species, just yes/no impacted in any way) vs. not-impacted range. Then we can map all species impacted/non-impacted ranges to show for each cell how many species are impacted.
BUT! Because the IUCN threats are classified for most species with a "score" from 0-9 indicating low, medium, high impact, we can actually create a CHI at the species level, i.e. species-weighting rather than habitat-weighting. This would communicate not just "impacted/not impacted" but actually quantify the level of impact from the spatial distribution of stressors. The process:
This issue isn't so much about the process but how can we create a map that communicates threatened ranges well - the Allan figure is pretty nice. But quantifying species CHI beyond simple impacted/not-impacted complicates matters. At the level of a single species, this is easy to create a map. But I feel like aggregating all these maps for all species across all stressors would be not helpful - too many things going on to explain easily. Two potential options:
For non-visuals, we can replicate all the same tables in Allan et al and push those farther using the threat weightings...