#density series idea notes

Concepts

Do native species density trials at two scale – micro and mesoscale using pots and large plastic buckets. Mix of potting soil and sand best – 50:50.

Consider intra and interspecific competition series – with replacement, i.e. keep net densities per pot consistent.  Finally, perhaps consider competition with an exotic such as red brome.

Designs
with and without shade mimic in greenhouse
umbrella over buckets in mesocosm experiment
natives against brome in density series

Natives

a

b

c

then a*b, a*c, b*c

Or run each out in solo then against red brome.

 

Round 1.
a vs rb
b vs rb
c vs rb
at 1,2, 5, 10, 25 seeds etc or a simple with-replacement density series.
THEN, ready for it…. red brome from cali and red brome from Israel
Round 2. 
a+b vs rb
etc.

 

Scales

 

 

#Carrizo National Monument research update 2018_2

We had a more ambitious set of goals this season.

Goals

  1. Habitat use frequency estimates. Tools: a. telemetry of blunt-nosed leopard lizard with a total at least 1200 relocations split between AM/PM with an estimate of shrub-open and behavior. b. cam traps at shrub-open on still mode.
  2. Behavior estimates. Tools: a. cam traps on video mode at a total of 100 hours recording time. b. direct observation (with recording too) by humans of lizards and grasshoppers at a total of 100hrs.
  3. Shrub-plant-animal interaction estimates. Tools: exclosures at two sites to exclude different taxa in shrub-open mesohabitats. a. cages. b. cams c. vacuums. d. sweeps.
  4. Temperature profile estimates. Tools: a. pulse of collars on lizards b. loggers at microhabitat scales.
  5. Census grasshoppers. Tools: stick, sweep, and vacuum. Also do direct observation to assess whether they are significant consumers.

Teams

1a. Mario and Steph. Goals 1,2,3,5.

1b. Malory and Nargol. Goals 1,2,5.

2. Emily and Kat. Goals 1 & 4.

Extensions

Deploy one set of cam traps on still mode at a total no-shrub zone.

Get a solid handle on behavior by verts and inverts in the context of paired interactions with plants (at micro-scale) and shrubs at mesoscale.

Need an assay of insect diversity.

Animal sampling contrast protocol

Telemetry-scat design

Predictions to test

Do relocations map onto where scat is found too?

Is there scat fidelity from day to day?

Does telemetry relocation or conversely scat presence within a likelihood MCP (polygon estimating 95% percent change animals present within area) correlate with one another?

ie – imagine a telemetry polygon and a scat one too – never been done!! and then we statistically overlay them.

0.png

How to test

1. do relocations this saturday (day #1), enter into usual relocation datasheet attached.  Do morning and afternoon.

Enter data that evening and do a baton handoff to the scat team.

2. On sunday (day #2), scat people ‘check’ all locations where there was certainly a lizard.  In each day 1 relocation, is there scat the next day!!  So, imagine day 1 there were 100 spots where lizards where spotted. On day 2, what proportion of these have scat deposited.

3. On sunday (day #2), team telemetry repeats process and finds another 100 spots or whatever they can where they see lizards.  Same process – enter and hand off to team scat.

4. On Monday (day 3#), same process – team scat check day 2 telemetry relocations for scat – so we are holding as best we can scat scent cones etc to 1-day old and team telemetry repeats and finds new spots for next sampling.

5. On tuesday (day #4), team scat checks team telemetry relocations from the day before (day #3).

DATA OUTCOME

A total of 4 days sampling with 3 statistical days to test for scat detections with a 1-day lag where lizards were spotted. SO POWERFUL.

NOW — -as you can imagine – there are also a few bonus opportunities here…. 🙂

A.  If dogs have time, check back more than 1-day lag – ie on day #4, dogs can check ALL previous days days 3,2,1 – this gets the second main prediction – ie site fidelity. BE amazing to know this.

B. If team telemetry has the people and the receivers, it can also go the other way – team telemetry looks for lizards where there was scat detected – anywhere – the following day – so we pass the baton back and forth.

C. Team scat if they have time daily, checks other sites to fill in the region more – ie the polygon idea – to see how well regional NOT just point sampling works.

 

 

 

 

 

 

 

 

 


Congratulations to Dr. Filazzola

Completing facilitation research and being a facilitator through collaborative mentoring and supporting team science, Alex defended his PhD yesterday. Congratulations!

 

The subes and all of us will miss your open spirit!
So tempting to post a different pic :)!

 

 

 

Posted in fun

Collaborative and open science writing

As we collectively move to platforms that support better reproducibility and open science, a few tiny challenges persist. Reference management. LaTex with BibTex is great, but at times, team members are interested less in reproducibility and more in just sharing the libraries. We recently faced this challenge because we were collaboratively writing a very long white paper and each of us worked in a different management ecosystem in spite of using GitHub to control the versioning and collaboration in the writing.

Here are some resources to support a decision. Anecdotal research similar.

List with satisfaction scores

Refworks, Easbib, Endnote, and Mendeley look promising.

Good contrast here including discussion of Zotero.

Gradhacker review here of offerings.

Writing in google docs collaboratively use paperpile.

Writing in RStudio use Zotero.

Summary

Great lists of pros and cons out there. Based on the various lists, I vote for key criteria as a. cloud storage, b. can use in RStudio easily, c. allows me to share library with collaborators for a given paper.

The three competitors seem to be Refworks, Mendeley, and Zotero.
Now, need to give them a head-to-head test shortly.