#fieldwork takes practice: lost quadrat and #zenmind

Fieldwork takes practice.
I love this pic because the landscape is so spectacular (Cuyama Valley, here is the post on the work our team is doing there), and it ‘looks’ like I am working. A new research associate has joined the team. Chase and I were out in the Cuyama Valley and Carrizo National Monument.  I was hoping to share with him some wisdom, hang out, survey some plots, and check on everything. The best thing about this pic however is that I am missing my quadrat (and my wisdom). I am looking back to Chase for about the tenth time hoping he picked up mine in addition to his own.


I never had to pick up his quadrat.
I also managed to lead us down the wrong dirt road once (only 12 miles), and in another instance, I was positive that this particular slope was the correct one and we ended up on a very pretty but extended detour.

zen mind, beginner’s mind


Cuyama Valley Micronet project 2016

With SB county, California, global change will certainly impact coastal zones. However, dryland ecosystems will also be subject to significant change. To examine the importance of shrubs as a buffer to some of these processes, we are deploying a micro-environmental network to measure the amplitude of several key processes. It turned out to be a real gem of a study site.

So much beauty just over the hill away from the roads.










Big Data for Little Schools: #BD4LS #LTER #openscience

University libraries are increasingly becoming repositories not just for books but for data.  Data are diverse including numbers, text, imagery, videos, and the associated meta-data.  Long-term ecological and environmental data are also important forms of evidence for change, a critical substrate for scientific synthesis, and an opportunity to align methodologies and research efforts nationally and globally (i.e. LTER).  Any school library can participate in this process now with the capacity for distributed cloud storage, the internet of things, and very affordable microenvironmental sensors placed in ecologically meaningful contexts.


Source:  Ignite talk on big data in ecology.

In collecting ecological data about a place, we assign cultural value (it is worthwhile measuring now and for a long time), and we develop a more refined and permanent sense of attachment to this place.  Increased engagement by local individuals within the immediate community is an important first step in promoting ecological education, breaking down the barriers between traditional and citizen science, and producing meaningful big data on the environment and ecology of place.  Consequently, school libraries, at least the elementary level, can engage with big data in ecology.  In the ecology course course I teach to second-year university students, we use flower power sensors to measure soil moisture, temperature, light, and soil nutrient levels.  These sensors are very affordable, have an excellent dashboard, and bluetooth sync with iOS devices.  However, the big data are only server side and need to be extracted using an app from the dashboard data visualizations.  Onset also produces the pendant loggers that measure light and temperature.  These sensors log and store data as well but are not bluetooth enabled.  You must plug them into an optical sensor but then can download all the data your computer.  We use both sensors in this ecology course and deploy them on our university campus.  Elementary schools could absolutely do the same for a nominal investment and engage children with microenvironmental datasets that can be linked to their school gardens, flower patches, or any other habitats within the campus.  We have a profound opportunity to teach big data, ecology, experimental design, and awareness of place.



1. Work with elementary school librarian to set up/select appropriate data repository.

2. Develop a short curriculum with learning materials for teachers on open data, publishing data, meta-data, and micro-instrumentation to measure meaningful attributes associated with the ecology of a campus.

3. Discuss open science and highlight urban ecology research to date.

4. Purchase a set of a dozen sensors to deploy on the school campus.

5. Students work with the librarian to download the data regularly, describe the data, and publish is regularly on a data repository.  The students publish the data.

6. The library highlights and hosts the visualizations associated with these data and archives the photographs, descriptions of the methods, and videos from students.




1. A school protocol for measures the dynamics of the natural environment on campus.

2. Real-time or aggregated descriptions of the ecology of the campus (descriptions of the flower gardens, vegetable gardens, or any greenspace).

3. Datasets in public repositories.

4. Imagery/videos of the greenspaces linked to big data also provided by the students.

5. Data management training and experience within the library context for elementary students.

6. Consider including or working with basic r-code to do statistics or visualizations.