possibly experimental urchin densities??

possibly spear fishing pressure??

possibly, wave stress? KF extent?

the forest is weed, and built on weeds. hence stable state shift = regime change. naturally resilient, but spatially patchy??

anthropogenic? ie: spear fishing use?

patterns of LENGTH and SHRINKAGE.

would this test for the hypothesis that older (longer) individuals are more likely to be shrunken because time is the greater explaining variable over location (locations may not be experiencing as much difference in fishing pressure as the sample distribution leads to believe. i.e. we are sampling the fishery well enough!? yay. (In healthy years would kelp abundance be significantly different among sites? (location significant?) this could indicate that whole system is uniformly ailing?) ..... I think there may be preliminary data that supports the idea that variously sized abalone (visible to divers) recovered or died from starvation over equal intervals. therefore, i'm thinking time, not some metabolic cost of being big, is the explainer for now. this is a well documented, multi-year stressed system.

length and avg shrinkage

matrices

site

occurrences of length and average shrinkage

sites with high average attendance would be more similar than low (fishing pressure maybe significant?)

length and shrinkage.

sites

sample size?

length

catch to be more uniform. whether that means popular clusters aggregate fishing pressure, or scarcity condenses it.

length (maybe shrinkage)

other sites (i.e. our sampling successfully tracks popular sites, and nearness to other popular locations diffuses pressure to length (overharvest). or: if probability dists show that relative to caught data adult abalone pop is low... are abalone less starved b/c fishing pressure significantly reduces the number per k.

length or shrinkage? density would be neat, sampled from the probability distribution, rather than from the data, if that can be a thing??

site

could be done relatively (to scale of fishing blocks) in gis with existing data.

replicate all? and/or: use this as a comparison method against sampyl?