PhD GRA Opportunity at Northern Arizona University in Flagstaff, AZ in the School of Forestry’s Quantitative Ecology Lab


Graduate Research Assistantship (PhD) Opportunity at Northern Arizona University in Flagstaff, AZ

Data Fusion for Forest Planning and Implementation: Ecological Restoration, Remote Sensing, and Data Analytics

Are you interested in a PhD program that will provide you an opportunity to work in the frequent fire forests of the American Southwest and influence ecological restoration practices? These forests are in dire need of restoration, mainly due to a century of fire exclusion and subsequent, undesirable changes in forest structure and function. For example, the largest collaborative forest restoration project in the US, the Four Forest Restoration Initiative (4FRI), has a goal of implementing restoration treatments on approximately 1M ha of U.S. Forest Service lands in northern Arizona. Fundamental to these efforts are precise data on the amount and distribution of available resources, knowledge of how resources may change over time, and hazard assessments (e.g., wildfire potential); all of which require costly and resource intensive, spatially explicit data. As a result, managers are using more remote sensing data products (e.g., LiDAR), coupled with advanced forest inventory and data analysis techniques, to quantify existing conditions and support broad-scale analysis of forest ecosystems.

A PhD graduate research assistantship is available in the School of Forestry at Northern Arizona University, Flagstaff, AZ, focused on the development and assessment of data fusion techniques that will allow managers to better capitalize on major advancements in remote sensing to utilize more accurate data and enhance precision of landscape-scale analysis (e.g., >100,000 acres) project areas. Working alongside the Ecological Restoration Institute, the USDA Forest Service, USDI Fish and Wildlife Service, The Nature Conservancy, and Campbell Global; the successful applicant will focus on developing and statistically validating an open source big data, remote sensing, and inventory data fusion platform. This platform will provide enhanced forest structural and compositional information in support of forest resource decision-making.

The selected student will:

  1. Assess and statistically validate algorithms for identifying individual trees and species from remote sensing data of Southwestern forests using new and/or existing stemmapped, area and tree based sample data.
  2. Using these algorithms and data, design and implement a platform that integrates multiple data sources (data fusion) that are typically too large to analyze using traditional methods (big data) to provide detailed forest resource information at the tree-,stand-, and landscape levels.
  3. Assess the accuracy, precision, and statistical properties of forest resource estimates such as bias, consistency, error, spatial uncertainty, and use these to provide improved information for land management decision making.
  4. Apply the platform to Southwestern landscape-scale case studies to; quantify existing conditions, assess low-value biomass product availability, facilitate watershed treatment implementation, and monitor forest restoration treatments.

The position includes a full stipend, tuition waiver, health benefits and field support for 4 years.

Applications from quantitatively minded individuals with a practical approach to solving complex problems are welcome. Experience processing large remote sensing and inventory datasets using C++, R, and/or Python is preferred.


  • Master’s degree in forestry, geography, ecology, computer science, or related fields.
  • Demonstrable research experience, collaboration abilities, and English (written and oral) communication skills.
  • Competitive GRE scores (top 40th percentile).

 Information about NAU’s graduate program, including eligibility requirements, is available at

NAU’s formal application deadline is for Fall 2018 is Feb 15 2018 and preferred start date is Summer 2018. However, interested candidates are encouraged to contact with Dr. Sanchez Meador as soon as possible using the information provided below or submit your CV, written statement of interest, and copies of unofficial degree transcripts to initiate a dialog via e-mail.

Contact Information:

Dr. Andrew Sánchez Meador 
School of Forestry 
Northern Arizona University
Flagstaff, AZ 86011-5018, USA 

Link to announcement PDF


Any media is good media!

Here’s a media piece from Phoenix’s KPNX TV, 12 News on the NAU School of Forestry’s Semester C (Ecosystem Assessment) course from Fall 2016. The piece was produced by Nancy Harrison and featured myself and now NAU alumni and President’s Prize winner, Gold Axe recipient, Cheyenne Adamonis. Fun times.

NAU School of Forestry – Semester C from Andrew Sánchez Meador on Vimeo.


A couple of new wildfire-related publications

Over the past year I have had the opportunity to work a several wildfire-related projects, two of which are now available from their publishers. The first focuses on the effectiveness of fuel treatments following the Wallow  (2011) fire and the second focuses on long-term forest dynamics under alternative climate and management scenarios following the Rodeo-Chediski (2002) fire. These were both great projects and I think collectively they provide quite a bit of insight into the abilities of managers and agencies to mitigate wildfire effects (during and after) and highlight the effects treatments have on resiliency and given different climate scenarios.

Screenshot 2014-10-02 07.12.24 Amy E. M. Waltz, Michael T. Stoddard, Elizabeth L. Kalies, Judith D. Springer, David W. Huffman, and A.J. Sánchez Meador. 2014. Effectiveness of fuel reduction treatments: assessing metrics of forest resiliency and wildfire severity after the Wallow Fire, AZ. Forest Ecology and Management 334(15): 43-52.

Abstract: Landscape-scale wildfire has occurred in higher frequencies across the planet. Fuel reduction treatments to fire-adapted systems have been shown to reduce the impact to human values-at-risk. However, few studies have examined if these treatments contribute to ecosystem resilience, or the capacity of a system to absorb perturbation and return to a similar set of structures or processes. We defined short-term metrics of resiliency to test the hypothesis that fuel reduction treatments in mixed conifer forests increased a fire-adapted system’s resiliency to uncharacteristically severe wildfire. In addition, we tested the hypothesis that fuel reduction treatments reduced burn severity, thereby increasing protection for adjacent human communities. We examined a mixed conifer forested landscape in the southwestern U.S. that was burned by a landscape-scale “mega-fire” in 2011; fuel reduction treatments had been established around communities in the 10 years prior to the fire. Fire effects were highly variable in both treated and untreated forests. However, analysis of resiliency metrics showed that: (a) treated units retained a higher proportion of large trees and had post-fire tree densities within the natural range of variability; (b) the understory herbaceous community had significantly higher cover of native grasses in the treated units, but no significant differences in nonnative cover between treated and untreated units; and (c) high-severity patch sizes were significantly larger in untreated stands and covered a larger proportion of the landscape than historical reference conditions. Fire severity, as defined by overstory mortality and basal area loss, was significantly lower in treated units; on average, trees killed per hectare in untreated units was six times the number of trees killed in treated units. Fuel reduction treatments simultaneously reduced fire severity and enhanced short-term metrics of ecosystem resiliency to uncharacteristically severe fire.

 Screenshot 2014-10-02 07.12.15 Alicia Azpeleta Tarancón, Peter Z. Fulé, Kristen L. Shive, Carolyn H. Sieg, Andrew Sánchez Meador, and Barbara Strom 2014. Simulating post-wildfire forest trajectories under alternative climate and management scenarios. Ecological Applications 24:1626–1637.

Abstract: Post-fire predictions of forest recovery under future climate change and management actions are necessary for forest managers to make decisions about treatments. We applied the Climate-Forest Vegetation Simulator (Climate-FVS), a new version of a widely used forest management model, to compare alternative climate and management scenarios in a severely burned multispecies forest of Arizona, USA. The incorporation of seven combinations of General Circulation Models (GCM) and emissions scenarios altered long-term (100 years) predictions of future forest condition compared to a No Climate Change (NCC) scenario, which forecast a gradual increase to high levels of forest density and carbon stock. In contrast, emissions scenarios that included continued high greenhouse gas releases led to near-complete deforestation by 2111. GCM-emissions scenario combinations that were less severe reduced forest structure and carbon stock relative to NCC. Fuel reduction treatments that had been applied prior to the severe wildfire did have persistent effects, especially under NCC, but were overwhelmed by increasingly severe climate change. We tested six management strategies aimed at sustaining future forests: prescribed burning at 5, 10, or 20-year intervals, thinning 40% or 60% of stand basal area, and no treatment. Severe climate change led to deforestation under all management regimes, but important differences emerged under the moderate scenarios: treatments that included regular prescribed burning fostered low density, wildfire-resistant forests composed of the naturally dominant species, ponderosa pine. Non-fire treatments under moderate climate change were forecast to become dense and susceptible to severe wildfire, with a shift to dominance by sprouting species. Current U.S. forest management requires modeling of future scenarios but does not mandate consideration of climate change effects. However, this study showed substantial differences in model outputs depending on climate and management actions. Managers should incorporate climate change into the process of analyzing the environmental effects of alternative actions.


2-Day Forest Vegetation Simulator Workshop

Yesterday, I completed a 2-day Forest Vegetation Simulator (FVS) workshop for (18) faculty and graduate studFVSWorkshopents here at NAU, and I’m beat. It was attended by four faculty, two postdocs, two manager and 10 graduate students.

Basically, I was approached by Kristen Waring, NAU’s Associate Professor of Silviculture, and asked if I’d be interested in conducting a FVS workshop a few weeks ago and saw it as an opportunity to “spread the love” with respect to FVS and ClimateFVS. The objective of the workshop was to introduce concepts of vegetation growth and yield modeling, specifically using FVS and to provide a brief introduction to ClimateFVS and the science behind these applications. The exercises emphasized the vast capabilities of FVS in simulating forest management alternatives and evaluating their potential impacts on forest structure, fire behavior, carbon accounting and under varying climate scenarios. I had intended to touch on openFVS, since the majority of my student use R, but I just ran out of time.

All in all it was fun and I especially enjoyed the questions and discussion. Feedback thus far has been entirely positive and if asked to do this again, I would.


Advancing Forestry Education by Biting Off More than I Can Chew

DSC_0133It should come as no surprise that there is an ever-increasing demand for competent forestry graduates; especially those who able to address complex economic, ecological, and social issues involving forest resources. However, Forestry is a traditional discipline and often finds itself challenged to educate students using 21st century technology and sciences to solve these new problems.

Last semester, a senior faculty and I proposed providing forestry undergraduate students with a redesigned, senior-level course in Ecosystem Assessment that would maximize the use of mobile technology with the following course objectives: 1) students will have enhanced, forestry-centered learning opportunities in both the field and classroom, 2)these experiences will improve the way students visualize spatial and temporal aspects of a forest resources and landscapes; and 3)ensure NAU’s School of Forestry remains in the forefront of forestry education.

This Fall, in FOR 413 & 414C (Forest Ecosystem Assessment I & II) at NAU, 39 undergraduate students will be let loose carrying 20 Dell Latitude 10 tablets running Windows 8 to collect and analyze forest resource data from a 4-sq. mile area on NAU’s Centennial Forest.  These data will be collected over a five-week period using a FVS-ready Access database for tabular data and ArcPad 10.2 with the tablet’s built-in Global Navigation Satellite System (GNSS) for spatial data.

The students will use this technology to integrate material learned in prior forestry courses while learning and applying new concepts and skills focused on the interpretation of remotely sensed imagery, land records, and ownership limitations; use of geographic information systems (GIS) and field protocols for inventory of biophysical features; and simulation of potential stand development pathways.