Honorable Forum:
Please do not excuse me if my questions or statements are naive or wrongheaded--hit me hard. How else am I to learn and retain? 1. Are all samples foundations for inferences about reality? 2. Is it always a safe assumption that the bigger the sample the more likely it is to reflect reality? 3. What is(are) the most basic rule(s) for sample "adequacy?" 4. How does one determine when and how the inference(s) made from a limited data set are limited and by how much? 5. How does one determine when results are more misleading than leading to a relevant and useful conclusion? For Dr. Quinn (and for comment by the Forum): 1. What are you trying to demonstrate or infer? 2. How did you determine the relevance of "100 km of a city," and to what factors was that considered relevant? 3. How does time figure into your investigation? How are the 1580 records (ca 55 records per species, or how are the species distributed as a fraction of the total) distributed over time? 4. How will the results of your investigation fit into the existing literature on the subject, and how will it advance it? 5. Are there any ArcGIS layers that are not applicable or useful to your data set or investigation? As I have inferred, I tend to believe that "anecdote is the singular of data," so think there must be a "pony" in there somewhere if you keep looking long enough. Just what kind of pony, how big, and how fast--who knows? The important thing, it seems to me, is the quest itself. Even if you find that it is invalid to use herbarium records to interpret distribution, or that the interpretation possibilities are severely limited, you will still have made a significant contribution. Negative results are still results. I hope you will keep the Forum informed as your study progresses. WT ----- Original Message ----- From: "L Quinn" <[EMAIL PROTECTED]> To: <ECOLOG-L@LISTSERV.UMD.EDU> Sent: Monday, July 14, 2008 6:37 PM Subject: [ECOLOG-L] Inferring weed distribution from herbarium records and GIS layers Dear list, I am relatively new to ArcGIS and its ecological applications, so please excuse me if this question seems naive or wrongheaded... I have obtained all of the existing herbarium records for 29 aquatic weed species in Australia (approximately 1580 records total), as well as several GIS layers showing things like land use, dominant vegetation type, cover class, etc. Basically, I would like to be able to demonstrate that the spatial pattern I'm seeing is statistically valid, but I'm not sure how to do that. The principal spatial pattern I see from "selecting by" the various polygon features in my GIS layers is that the density of aquatic weed records is greater in "intensive" land use types (e.g. urban residential areas) than in other types. I derived density values by taking the total number of herbarium records (points) falling within those selected polygons and dividing by the total area (in km2) of the selected polygons. The problem is that this leaves me with only one density value for each land use type, which is, of course, not possibly to analyze statistically. How does one "replicate" when sampling from a map? I also went through the exercise of picking out each individual point (herbarium record, so each point is an individual of a particular species) and characterizing it in terms of the land use type, vegetation type, and cover class it sits in and whether or not it falls within 100 km of a city, but I am not really sure what I can do with that dataset. It is, at least, much bigger than the 5 density data points I have. If you can see an obvious solution to this or know of instructive texts or papers, please let me know. If you think there's nothing I can do with this dataset, I suppose that's good (but depressing) information too. If you have comments about the validity of using herbarium records to interpret distribution, I am somewhat aware of the issue already. Thank you. Lauren Quinn _________________________________________________________________ Making the world a better place one message at a time. http://www.imtalkathon.com/?source=EML_WLH_Talkathon_BetterPlace=
