MSc or PhD for Canadians to do research in desert ecology or open science in California

Great news, we have had some funding come through for some research in California.

Two options, MSc or PhD.

Desert ecology research

The primary focus of the research is exploring how we might better use positive interactions between plants for restoration and management of arid systems. In particular, we want to examine influences on other taxa such as insects (including pollinators), endangered animal species (such as leopard lizards and kangaroo rats – cute), and on community biodiversity dynamics.


Graduate-level research with The Nature Conservancy in Carrizo National Monument of positive-plant animal interactions.

GPA for YorkU Biology is A-, A.

Need to be able to drive.

Competent in R.

Admission Requirements

Open science research

Graduate-level research on open scientific synthesis. The goal is to explore existing data in high-stress ecosystems such as deserts and do synthesis. Data aggregation, systematic reviews, and meta-analyses to explore the importance of foundation species and biodiversity. This is a unique opportunity because this person can also collaborate with NCEAS to explore teaching open scientific synthesis, develop materials, and do research with the process of doing open science for synthesis.


Excited about open and team science.

Competent in R.

Excited to work with big data, access data repositories, and do synthesis.

Excited to become an educator and contribute to positive change by developing materials (code, packages, guidelines, etc) that use these approaches.

Same admission requirements as first position.

Start date is Sept 1, 2017 for both/either opportunity.

I recommend you pop me an email too if you are interested:

How we use a handheld soil moisture probe to supplement in situ plant ecology sampling

It is best to deploy loggers with appropriate sensors to capture an environmental signal within a set of study sites. Nonetheless, when actively sampling for plant-plant interactions dynamics,  an estimate of soil moisture at that particular point in time and space precisely is useful (at least as a covariate). We use the Delta-T SM-150 handheld unit to complement our long-term logging arrays.

Here is a brief summary of the settings/methodology we use.


  1. Push right button to activate unit.
  2. Repeatedly depress right button to cycle through modes until you reach ‘organic’.
  3. Insert probe into ground and ensure that metal conductors are fully embedded in ground with ceramic/plastic unit flush with ground surface.
  4. Left button to measure. Typically, it should take only 1-2 seconds.
  5. Avoid rocks and voids in the ground when inserting probe.

Comments: Ranges you can expect at least in arid and semi-arid systems we have tested within California are between 1-40% but most frequently < 10%.  The unit is durable, and the control unit is ‘water resistant’. However, when the controller gets wet in the rain, it stops working until it drys out again (typically at least a day later). The cable is not that robust, and to be safe, we insert/push the sensors into the ground using the ceramic casing.


Microenvironmental change in Cuyama Valley 2017.2 goals

In 2016, we deployed micro-environmental data logger arrays to monitor global change dynamics at very fine scales. We also structured measurements to ensure we can infer and link to a biotic interaction signal between common plants within this region.

This is very important region to study for at least two reasons ecologically.

(1) Water issues with people, plants, and agricultural are critical here.

(2) Cuyama Valley is an excellent set of sites or mesocosm for the San Joaquin Valley at large. The San Joaquin Valley is still sinking (NASA report). We need to understand temperature, precipitation, and soil moisture availability patterns at many scales within the region.

This season, 2017, is a relative boom year in terms of precipitation. Here are the immediate sampling goals for this season.

1. April (mid). At peak flowering, count burrows, re-measure shrub sizes, sample annual vegetation, and collect biomass.
2. May (mid). Retrieve all logger units, download data, and check functionality. These data capture two growing seasons – one drought, one wet.
3. May (mid). Re-deploy and re-initialize loggers. Rationale – need data on shrub effects when it matters for animals like lizards and hoppers etc and when it is really hot.
4. Sept (end). Retrieve loggers and sensors, download data, end experiment.
5. Oct. Design and test a missing-data strategy to address missing sensor and logger failures. I will likely implement a within-site, resampling data strategy associated with central tendency measures to fill gaps.