MAPPING PRODUCTIVITY AND CLIMATE INTERACTIONS IN FOREST AND AGRICULTURAL ECOSYSTEMS WITH UAV-BASED SENSORS

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: HATCH
• Reporting Frequency: Annual
• Accession No.: 1016265
• Project Start Date: Oct 1, 2018
• Project End Date: Sep 30, 2021
• Program Code: [(N/A)]- (N/A)

Recipient Organization
UNIVERSITY OF NEW HAMPSHIRE
51 COLLEGE RD SERVICE BLDG 107
DURHAM,NH 03824

Performing Department
Natural Resources and the Environment

Non Technical Summary
The ability to map agricultural and forest productivity is important to forest and farm managers and helps scientists better understand how ecosystems are affected by climate. Although Earth-observing satellites can provide useful information over large areas, the images they produce are often too coarse to be useful locally. Recent growth in the availability of drone-based sensors may provide a solution, but most have not been thoroughly tested for these applications. Here, we plan to evaluate the usefulness of several drone-based sensors being marketed to land management practitioners by comparing the data they collect with careful measurements of plant health, leaf chemistry and growth rates.We will accomplish this using new data from plot-level measurements and a local cluster of environmental sensors that monitor carbon and water exchange between ecosystems and the atmosphere, We will seek to extend these measurements spatially by evaluating the degree to which sensors flown on low-cost, unpiloted aerial vehicles (UAVs, or drones) provide information relevant to leaf nitrogen, photosynthesis, and plant growth. Results will be used to map leaf nitrogen concentrations, plant growth rates and other related variables over each site and to determine whether image data can be scaled to larger areas using broad-band satellite sensors.The work we propose will benefit agricultural and forest practitioners by (1) evaluating the utility of inexpensive drone-based sensors that are increasingly being marketed for land management applications and (2) developing methods through which image data can be used to estimate agricultural and forest productivity, surface temperature,and plant stress. Our work will also provide information on how ecosystems respond to and influence climate. This information is of value to society broadly in helping decision makers understand and prepare for the effects of changes in climate. Finally, our work will support the education of next-generation scientists and practitioners by involving undergraduate students in all aspects of the work. The project director's lab has a long history of involving undergraduates directly in research. Nearly all students from the lab have used the experience to design their own independent projects and a number have continued on to graduate school.

Animal Health Component

50%

Research Effort Categories

Basic

50%

Applied

50%

Developmental

(N/A)

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
102	0613	1060	50%
102	1699	1060	50%

Knowledge Area
102 - Soil, Plant, Water, Nutrient Relationships;

Subject Of Investigation
1699 - Pasture and forage crops, general/other; 0613 - Mixed conifer-broadleaf forests;

Field Of Science
1060 - Biology (whole systems);

Keywords

forest productivity

carbon

climate

remote sensing

drones

leaf nitrogen

Goals / Objectives
Forests and agricultural lands provide New Hampshire residents with provisioning services in the form of food, energy, timber products and economic prosperity. Increasingly, they are also looked upon to provide regulating services that contribute to water quality, climate regulation, and other aspects of environmental quality. Striking an acceptable balance between these goals requires advancements in (1) our basic understanding of how ecosystems function and (2) the development of tools that allow us to collect information about relevant variables (e.g. growth, biomass, nitrogen content) at spatial scales that are relevant to working landscapes and broader-scale environmental models.In 2014, we established a local cluster of instrumented towers at several New Hampshire Agricultural Experiment Station (NHAES) research sites that are equipped with sensors that measure carbon, water and energy fluxes between ecosystems and the atmosphere. Data from these sensors have shed new light on how ecosystems respond to drought, land management, and climate variability at daily to interannual time scales and on the mechanisms through which different land use practices influence local climate. Although this kind of information is valuable for both science and land management, the measurements themselves represent a small and poorly defined area (the tower "footprints"), and the cost and complexity of the instruments preventthem from being widely deployed. Here, we plan to address this limitation by testing methods for scaling-up from field plots and tower-based measurements to their surrounding landscapes using low-cost imaging sensors that can be flown on unpiloted aerial vehicles (UAVs, or drones). Specifically, we plan to:1. Conduct field measurements of plant productivity, CO2 exchange, leaf nitrogen concentrations and growing conditions at four sites near Durham, NH, including both agricultural (corn, hay, and pasture) and forested landscapes.2. Evaluate the degree to which leaf and plot-level measurements relate to spectral features in drone-based imagery acquired from research-grade sensors, as well as less expensive sensors being marketed to agricultural and forest management practitioners.3. Examine the degree to which drone-based imagery can be scaled to the broader region using similar spectral bands available from National Aeronautics and Space Administration (NASA)'s Landsat-8 instrument.The unmanned aerial vehicle (UAV) sensors will be used to assess the degree to which leaf chemistry, plant growth rates, drought stress and local surface temperatures can be mapped using inexpensive UAV platforms and related to broader scale imagery from aircraft and satellite remote sensing instruments.The work we propose will help address the gap in spatial resolution between leaf and tower-based measurements and the satellite sensors needed to parameterize global ecosystem and land surface models. It is also designed to offer practical value to land managers because it will involve testing of inexpensive UAV imaging systems that are being rigorously marketed--though less rigorously tested--as tools for precision agriculture and forestry.

Project Methods
The overarching approach to this work involves (1) integration of leaf, plot, and ecosystem-level measurements of plant growth and leaf nitrogen concentrations at four sites that span forest and agricultural vegetation types and (2) examining the degree to which these variables can be mapped using drone-based sensors. Relevant methodological details for each aspect of the work are outlined below.Ecosystem carbon (EC) fluxes: We will relocate one of our four environmental sensor towers to a pasture-dominated site and continue measurements at the other sites to quantify CO2 and water fluxes on forest and agricultural land. The EC measurements will provide continuous estimates of whole-ecosystem photosynthesis for comparison with leaf-level measurements across the growing season.Instruments at each of the sites includea CO2/H2O analyzer, a 3-D anemometer, and meteorological sensors that include air and soil temperature/humidity probes, a rain gauge tipping bucket, quantum sensors, and a net radiometer to measure incoming and outgoing radiation. For data processing and quality control, we will continue to use methods established by the Fluxnet program, with local adaptations for our sites derived under prior NHAES research.Leaf measurements: Measurements of leaf physiology will be made on dominant/co-dominant species at 10-15 plots at each of the sites. The timing of sampling will vary among vegetation types and be determined based on either natural patterns of phenology across the growing season (forest) or by timing of management activities (e.g. seeding, harvest or grazing for corn, hay,and pasture). On each sampling date, we will quantify canopy height and leaf area index using an optical canopy sensor.Measurements describing leaf photosynthetic capacity will be made using a portable gas-exchange system purchased through an AES FY17 Research Equipment Competition Award (NIFAaccession 1006997). Once photosynthesis measurements are completed, foliage will be excised and brought back to the lab for further analysis. Determination of foliar nitrogen concentrations by mass will be performed on an elemental analyzer housed at UNH. Leaf size and area will be measured using a leaf area meter and divided into dry leaf mass to determine leaf mass per area. Spectral measurements of leaf reflectance will be made using a portable field spectrometer.Plot-level productivity: Production of aboveground biomass will be measured at plots located in the landscapes surrounding each flux tower. Measurements of biomass production will vary by vegetation type. At the forest, we will conduct annual measurements of wood production via basal area growth and tree turnover, and foliar production via litterfall at five plots surrounding the tower. At the cornfield, we will establish 10-15 plots at each of three sampling dates (early, peak growth, and pre-harvest) and harvest all biomass within the plots by clipping corn stalks at the base. All harvests of corn will be coordinated with UNH Farm Services. Harvested biomass will be dried and weighed for dry biomass estimation. At the hayfield and pasture, we will establish 10-15 plots and non-destructively measure standing aboveground biomass using a disc pasture meter which provides an integrated measure of forage density and forage height.UAV image acquisition and processing: Remotely sensed image data will be collected using rotary and fixed-wing drones equipped with optical sensors and flown by a licensed drone operator. The low-cost, commercially available sensors include an 18 MP digital camera, a Parrot Sequoia multi-band imager, and a Forward looking infrared radiometer (FLIR)vue thermal imager. These instruments will be mounted on a Birdseye view Firefly 6 Pro fixed-wing drone and flown over an approximately 200-acre area at each site an altitude of approximately 200 feet above the vegetation. Images will be stitched together in-house using Photoscan Pro 1.2 by AgiSoft and georectified with deployed ground control points and a high precision GPS. Registration error will be assessed by withholding a subset of ground control points.We will also collect research-grade imaging spectrometer data using a Headwall nanospec hyperspectral imager. Given the greater size of this instrument, it will be flown on a rotary drone (a DJI Matrice 600) which has a suitable payload capacity, but a smaller range. The hyperspectral data represent the most advanced and detailed of the optical images we collect and will be used as a best-case standard for calibration to field data and evaluation of the less expensive broad-band sensor. Image calibration will follow standard methods of PLS calibration developed by our lab. Errors will be assessed with a combined approach involving leave-one-out cross-validation and a more rigorous 70/30 split cross-validation. All flights will be conducted by an FAA-certified operator.In previous work, we have had success using both hyperspectral and broad-band remote sensing to derive spatial estimates of canopy nitrogen in forested ecosystems. We have also derived canopy nitrogen maps from airborne imaging spectroscopy (hyperspectral) in forests and agricultural lands from data collected as part of a previous study for the Lamprey River and Oyster River watersheds. We will extend these approaches to map canopy nitrogen with finer spatial resolution using the proposed UAV system. Using data from the proposed set of UAV sensors we will evaluate the degree to which leaf nitrogen concentrations can be estimated. We will also derive vegetation indices linked to plant biomass and productivity and plant water stress. Mapping and scaling to Landsat: Currently, a gap exists in the spatial resolution between leaf and tower-based measurements and the satellite sensors needed to parameterize global ecosystem and land surface models. Information on the properties of vegetation can be particularly challenging to capture in agricultural settings (e.g. row crops) given the large differences in the reflective and thermal properties of vegetation and bare soil that may only be captured with finer spatial resolution remote sensing data. We will assess the ability of spatially coarser satellite remote sensing platforms to integrate and capture leaf and plant level patterns observed from field and UAV measurements. Specifically, we will acquire and process growing season data (approximately April to October) from the Landsat 8 instrument to compare with imagery data from the UAV systems.

Progress 10/01/18 to 09/30/21

Outputs
Target Audience:Our target audience included elementary to graduate level students, teachers, conservation groups, researchers, and land managers. Prior to the start of the Covid-19 pandemic we were more easily able to communicate with elementary, middle, and high school students and teachers. Specifically we formally communicated with students and teachers from Dover Middle School, Dover, NH, Bishop Guertin High, Nashua, NH, Old Town High, Old Town, ME, Portsmouth High, Portsmouth, NH, Newport Middle School, Newport, NH, Cool Spring Hutterite Colony School Grade 5-8, Manitoba, Canada, Edmonton Academy Grade 7, Alberta, Canada, Coleytown Elementary School Kindergarten, Westport, CT, Mountain View High School 7th Grade Science Classroom, Mesa, AZ, The Blue School 8th Grade Science Classroom, New York City, NY, and the Alexander II Magnet School in Macon, Georgia. Several undergraduate and graduate students, as well as two post-docs, and early career scientists participated in research and served as both mentors/mentees on this project. PI Ollinger discussed results of the work and its land management implications with members of several regional conservation and land management groups at invited meetings sponsored by (1) the Society for the of New Hampshire Forests and (2) the Ecologial Landscape Alliance. Steve Eisenhauer, a land manager at the University of New Hampshire also participated in research meetings held at the University of New Hampshire. During the Covid-19 pandemic we have communicated frequently with researchers and forest managers at the US Forest Service, Stanford University, Harvard University, the University of Vermont, the University of Maine, and the University of New Hampshire through small group zoom meetings. We have also presented in-person and virtually to a more global research audience through scientific conferences. Changes/Problems:A portion of our proposed work involved use of drone-based sensors toremotely sense leaf nitrogen and other plant traits related to carbon uptake in forests and agricultural ecosystems. We had success with the forested site (Thompson Farm), but the agricultural site was problematic because crops planted in the footprint of our Kingman Farm flux tower changed from perennial grasses (hay) to a mixture of corn and hay with a dividing line thatmade it impossible to relate carbon uptake measurements to either plant type. As a result, we have deprioritized the maintenance of that site, which requires periodic sensor repair and replacement. We were still able to contrast the response of the forest and grass sites to climate variability, but had to relyon carbon flux data collected before the change in crops. We were also able to include agricultural systems in our broader scale remote sensing work using data from the Landsat satellite. A second challenge was thatavailable funds were insufficient to cover the costs of the planned drone system.To address this, we tookadvantage of drone data acquisitions from other researchers who made data available for our project and supplemented these with additional measurements of leaf and branch-scale reflectance made with a portable spectrometer. These data provided coverage for the Thompson Farm site, whichhelped us examine the effects of two severe drought events that affected productivity in New Hampshire during 2016 and 2020. These efforts led to several collaborations with the US Forest Service and other universities to discuss implications for forest management and strategies such as assisted migration of tree populations and optimal tree densities in agroforestry systems. Lastly, restrictions resulting fromthe COVID-19 pandemic reduced ourability to hire and train undergraduate students and our ability to meet with and outreach to elementary school, middle school, and high school students. Instead, we pursuednew opportunities that arose through small group zoom meetings where we were able to reach a much wider audience of silvicultural and ecological researchers and students. What opportunities for training and professional development has the project provided?Our research group is structured to allow for career development opportunities in training of students and researchers who are at different stages of their career. For example, senior research staff Ouimette formally mentored University of New Hampshire undergraduate Elizabeth Pederson with her senior undergraduate capstone research project. Elizabeth Pederson was trained in the field collection of data by both senior research staff (post doc Sanders DeMott and Ouimette) as well as graduate students (Baillargeon and Hastings). This provided technical training for Elizabeth as well as the development of leadership skills for both graduate students and senior personnel. Elizabeth also worked with collaborators at the US Forest Service and in the UNH Stable Isotope Facility to complete laboratory analyses of samples. Graduate students Jack Hastings, Kaitlyn Baillargeon, Keegan Feero, and Shersingh Joseph Tumber-Davila were responsible from the collection of field data with senior research staff Ouimette. Students operated both high grade research equipment to measure leaf physiology as well as a canopy boom lift to get up above forest canopies and measure leaf temperatures. Post-doctoral researchers Rebecca Sander-Demott and Jessica Gersony were involved in leading outreach activities and fieldwork as well as being important mentors to graduate students. Sanders-Demott also trained middle school and high school students and their teachers in the collection of meteorological and ecological data during winter conditions, a period for which data are often lacking. PI Ollinger, senior research staff, post-docs, graduate students, and undergraduates all collaborated on data analysis, interpretation, presentation of results at scientific conferences, and manuscript preparation. How have the results been disseminated to communities of interest?We communicated our research findings through student workshops, scientific conferences, and focused small group zoom meetings. For example, post-doc Sanders-DeMott co-led and designed materials for multiple workshops from November 2018 through April 2019 on monitoring winter climate (e.g. snow depth and soil frost) and early plant phenology (bud burst, leaf out, leaf expansion) at: Dover Middle School, Dover, NH Bishop Guertin High, Nashua, NH Old Town High, Old Town, ME PortsmouthHigh, Portsmouth, NH Newport Middle School, Newport, NH. These workshops, carried out in collaboration with Elizabeth Burakowski and Alix Contosta (University of New Hampshire) and John Campbell (US Forest Service), involved training students in hands-on data collection, synthesis across multiple school-based citizen science datasets, and teaching about the importance of this data collection using examples from the AES-supported data collection at Thompson Farm forest (Durham, NH) and Kingman Farm grassland (Madbury, NH). Student data was contributed to the GLOBE website and is freely available to the community. Sanders-DeMott and research scientist Ouimette also participated in online classroom visits through the Skype-a-Scientist program with students in the following schools: Cool Spring Hutterite Colony School Grade 5-8, Manitoba, Canada Edmonton Academy Grade 7,Alberta, Canada Coleytown Elementary School Kindergarten, Westport, CT Mountain View High School 7thGrade Science Classroom, Mesa, AZ The Blue School 8th Grade Science Classroom, New York City, NY, Alexander II Magnet School in Macon, Georgia. Research results were presented at various scientific conferences by both senior personnel and students. These included a presentation by undergraduate Elizabeth Pederson at University of New Hampshire's undergraduate research conference, multiple presentations by graduate student Jack Hastings at the American Geophysical Union Conference (2020, 2021), at the Annual Harvard Forest Research Symposium (2021) and Midterm review (2021), and at the University of New Hampshire Graduate Research Conference (2019, 2020, 2021). Stanford doctoral student Shersingh Joseph Tumber-Davila (Stanford University) presented findings from this project at the American Geophysical Union (2021) and included this work as a doctoral thesis chapter (2021). Over the past two years much of our communication with target audiences has taken place through small group zoom meetings. For example, we have held monthly meetings with US Forest Service staff Eric Gustafson, Brian Miranda, Dustin Bronson, and Brian Sturtevant, Harvard Forest scientists Matthew Duveneck, Jonathan Thompson, and Shersingh Tumber-Davila, and Jane Foster, a research faculty from the University of Vermont. We have shared results of NH-AES research, and worked towards incorporating concepts learned into ecosystem models aimed at predicting the impacts of climate change and forest management. We have also shared NH-AES work at larger group NH-EPSCOR meetings with both students and faculty from a diverse range of disciplines including silviculture, ecology, remote sensing, and data science. Lastly, because of the financial support of this program we have been able to maintain infrastructure at Thompson Farm (a local research site near the University of New Hampshire). The continued measurements and infrastructure made possible by AES funding led to the 1st and 2nd annual Thompson Farm Researcher's Meetings, where annually 20+ faculty, research staff, and graduate students from several departments at UNH met to discuss research efforts and potential collaborations. Steve Eisenhauer, a land manager at UNH, also participated and provided valuable insight into land-use at the property. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Impact Statement Our work at Thompson Farm revealed species-specific responses to drought and improved understanding of how individual tree species trees respond to variation in temperature, vapor pressure deficit, light availability and other environmental variables. Specifically, during the severe drought events of 2016 and 2020 wood growth was reduced by 30% compared to more typical years. In response to drought, Northern Red Oak doubled its fine root biomass, accessed water from deeper soil layers, and maintained near-optimum leaf temperatures for growth, while Red Maple showed a minimal root response and experienced growth inhibiting leaf temperatures of over 100oF. In addition, we found distinct differences in the drought resistance of tree species across sites within the northeast region. For example, Northern Red Oak and Red Maple at Thompson Farm can withstand much greater soil moisture deficits than trees of the same species and age class at Harvard Forest in Massachusetts. Preliminary data suggest this may be the result of local genetic adaptation because trees at the ongoing Thompson Farm Drought Experiment showed minimal differences in their wilting point (minimal acclimation) after 6 years of drought treatment compared to control trees. We have communicated these results to forest managers at both sites and are pursuing support to expand this work to other sites across the region. We also took advantage of existing datasets and built new infrastructure to improve our ability to monitor and predict agricultural and forest productivity with remote sensing platforms. Specifically, we compiled existing measurements of leaf nitrogen and constructed a regional map of forest canopy nitrogen concentrations at a fine spatial resolution (30-meter) using the satellite-borne Landsat 8 sensor. Our foliar nitrogen map is actively being used by researchers in New Hampshire, Maine, and Vermont as part of a tri-state National Science Foundation EPSCOR project to drive ecosystem models and predict the future state of New England forests. Our work also led to the development of new infrastructure for measuring vegetation spectral reflectance. Specifically, we constructed a laboratory goniometer and dark room that allows researchers to measure how vegetation reflects light at various wavelengths. UNH graduate student Jack Hastings is using this system to examine underlying drivers of reflectance features that are commonly used to assess plant growth, but for reasons that are poorly understood. Finally, our work at the Thompson Farm eddy covariance tower has helped strengthenThompson Farm as a nationally recognized research station. This has led to new collaborations with investigators at UNH and other institutions, including Stanford University, Harvard University, the University of Vermont, the University of Maine, and the US Forest Service. The eddy covariance infrastructure at our NH-AES Thompson Farm and Kingman farm researchsites also helped initiate annual Thompson Farm Researchers meetings. Accomplishments In addition to the Impact Statement above,accomplishments/activities that were completed over the last 3 years with support from this NH-AES project included: Annual measurement of tree growth on ~1500 trees Continuous operation of an eddy covariance flux tower to continuously measure half-hourly: Net carbon exchange Gross photosynthesis and ecosystem carbon loss (or respiration) Water and energy fluxes Meteorological variables (above and below canopy air temperature, humidity and precipitation, wind speed and direction, soil temperature and moisture, incoming and outgoing solar radiation, air density and pressure, among other variables Carbon, nitrogen, oxygen, and hydrogen isotopic measurements of >800 tree and soil samples to quantify the depth of nutrient and water uptake by various tree species Quantification of fine root biomass and root distribution by species within soils at both drought and control plots Measurement of temperature response functions (rates leaf-level photosynthesis and water loss vary across experimentally altered temperature conditions) for northern red oak, red maple, and eastern white pine Leaf temperature measurements of ~3000 leaves across 10 tree species using a boom lift during the 2020 drought event 700+ measurements of foliar nitrogen, leaf mass and thickness, and photosynthetic capacity Compilation of thousands of foliar nitrogen measurements across >250 forested plots located in the northeastern US (NH, ME, MA, NY) to construct a regional foliar nitrogen database Derivation of a regional forest canopy nitrogen map using our regional foliar nitrogen database and reflectance data from the Landsat 8 satellite platform Construction of a laboratory goniometer measure leaf and branch leaf reflectance Reflectance measurements of ~ 100 leaf and ~100 branch samples across 10 forest tree species using the constructed goniometer Quantification of turgor loss point (wilting point) of 6 tree species at NH-AES Thompson Farm drought and control plots, as well as at the Harvard Forest nitrogen fertilization and control plots Co-led the Second Annual Thompson Farm Cooperator's Meeting - an effort to connect researchers at this NH-AES site, compile datasets, and to create a website to publicize ongoing research

Publications

• Type: Conference Papers and Presentations Status: Other Year Published: 2021 Citation: Hastings JH, Ouimette AP, Baillargeon KA, Ollinger SV. Can Broad-Band Remote Sensing Provide Regional Estimates of Foliar Nitrogen and Photosynthetic Capacity? Online Poster presented at the Harvard Forest LTER Midterm Review, Petersham, MA. September 20, 2021
• Type: Conference Papers and Presentations Status: Other Year Published: 2021 Citation: Hastings JH, Ollinger SV, Ouimette AP, Lepine L. Can Broad-Band Remote Sensing Provide Regional Estimates of Foliar Nitrogen and Photosynthetic Capacity? Online Poster presented at the University of New Hampshire Graduate Research Conference, Durham, NH. April 19-20, 2021.
• Type: Conference Papers and Presentations Status: Other Year Published: 2021 Citation: Hastings JH, Ollinger SV, Ouimette AP, Lepine L. Can Broad-Band Remote Sensing Provide Regional Estimates of Foliar Nitrogen and Photosynthetic Capacity? Online Poster presented at the Harvard Forest Ecology/LTER Symposium, Petersham, MA. March 16-17, 2021.
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Hastings JH, Ollinger SV, Ouimette AP, Lepine L. Can Broad-Band Remote Sensing Provide Regional Estimates of Foliar Nitrogen and Photosynthetic Capacity? Online Poster presented at the American Geophysical Union Fall Meeting, San Francisco, CA. December 7-11, 2020.
• Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Hastings, JH., Ouimette AP., Baillargeon, KA., van Aardt, J., Krause, K., Ollinger, SV. Examining links between forest structure and function and the influence on reflectance across different scales. Online Poster presented at the American Geophysical Union Fall Meeting, New Orleans, LA. December 13-17, 2021.
• Type: Conference Papers and Presentations Status: Other Year Published: 2021 Citation: Ouimette AP, Ollinger, SV, Hastings J, Baillargeon K. Diversity of tree species traits and associated carbon fluxes. Thompson Farm Annual Cooperators Meeting. April 2021 (virtual).
• Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Tumber-Davila SJ, Ouimette A, Vadeboncoeur MA, Ollinger SV, Asbjornsen H, Jackson RB. Oaks and other hardwoods appear remarkably resilient when facing prolonged drought-stress in a northeastern temperate forest. In AGU Fall Meeting 2021. December 13-17, 2021.
• Type: Conference Papers and Presentations Status: Published Year Published: 2021 Citation: Ollinger S.V. 2021. The role of climate change, biodiversity and invasive pests on ecosystem-climate feedbacks. 27th annual conference of the Ecological Landscape Association.

Progress 10/01/19 to 09/30/20

Outputs
Target Audience:Our target audience included elementary, middle, and high school students and teachers, undergraduate and graduate students, as well as other scientists, land managers, and conservation groups. Specifically as part of this project we formally communicated with students and teachers from Dover Middle School, Dover NH; Bishop Guertin High, Nashua, NH; Old Town High, Old Town, ME; Portsmouth High, Portsmouth, NH; Newport Middle School, Newport, NH; Cool Spring Hutterite Colony School Grade 5-8, Manitoba, Canada; Edmonton Academy Grade 7, Alberta, Canada; Coleytown Elementary School Kindergarten, Westport, CT; Mountain View High School 7th Grade Science Classroom, Mesa, AZ; The Blue School 8th Grade Science Classroom, New York City, NY; and the Alexander II Magnet School, Macon, Georgia. University of New Hampshire undergraduate Elizabeth Pederson, and graduate students Kaitlyn Bailargeon, Jack Hastings, and Keegan Feero were also involved in research related to this project and received mentorship from PI Ollinger and other senior personnel on the project. We have communicated formally with researchers both locally through meetings at the University of New Hampshire as well as a more global research audience through scientific conferences. Steve Eisenhauer, a land manager at UNH also participated in a research meeting held at UNH. PI Ollinger discussed results of the work and its landmanagement implications with members of several New Hampshire conservation and Land Management groups at an invited meeting sponsored by the Society for the Protection of New Hampshire Forests Changes/Problems:Our initial work plan involved purchasing a drone sensor setup that would allow us to compare field measurements directly to the type I've reflected state of local land-owners may have access to. We have so far opted not to do this because available funds were insufficient for both purchasing the drone system and having support for personnel to conduct field measurements in data analysis. We have opted to focus on field data collection because relevant drone imagery have become available through collaborations with other UNH researchers (e.g. Palace, Sullivan, Congleton, and Fraser). We are working with these research groups to click both research grade and lower cost drone imagery needed to complete this project. Relying on existing drone systems has allowed us to focus our efforts on the field measurements needed to complete the project which would not be available from other sources building on our existing field data record has also had the secondary benefit of strengthening Thompson farm as a nationally recognized research station and building new collaborations with investigators at UNH and other institutions, including Stanford University, Macalester college, Tartu Observatory (Estonia), in the US for service. Our work at Thompson farmers also played a big role in why there has been a conscious effort among researchers at UNH to make Thompson farm a world class research site and helped initiate the 1st annual (and recurring) Thompson Farm researchers meeting. The COVID-19 pandemic has limited our ability to hire and train undergraduate students as well as our ability to meet with and outreach to elementary school, middle school, and high school students. Moving forward we will look for more virtual approaches to interact with students from all levels. Although we made significant progress over the last reporting, access to laboratory facilities has been limited and cost some delays in sample processing analysis. We have mostly been able to overcome these delays but are still waiting on several analyses that we will use to compare to remote sensing imagery. What opportunities for training and professional development has the project provided?Our research group is structured to allow for career development opportunities in training of students and researchers who are at different stages of their career. For example, on this project undergraduates were trained in the field collection of data both by senior research staff as well as graduate students. Graduate students Jack Hastings, Kaitlyn Baillargeon, and Keegan Feero were responsible from the collection of field data with senior research staff Andrew Ouimette. Students operated both high grade research equipment to measure leaf physiology as well as a canopy boomlift to get up above forest canopy's and measure leaf temperatures. PI Ollinger, senior research staff, and graduate students all collaborated to data analysis, interpretation, presentation of results at scientific conferences, and manuscript preparation. How have the results been disseminated to communities of interest?During the last reporting period results we largely disseminated through peer-reviewed manuscripts and conference presentations (see products). Results have also been shared with local collaborators from New Hampshire, Vermont, and Maine through zoom meetings. In person presentation of results have been restrictedfor much of the year. What do you plan to do during the next reporting period to accomplish the goals?During the next reporting period we will finish processing UAV data collected with both the research grade and low cost sensors and compare these data to our field mesaurements of plant nitrogen and productivity. We will compare UAV data to satellite data over the same areas and assess the ability of coarser resolution satellite data to capture fine scale patterns we see on the ground. Lastly we will continue developing region wide (NH, ME. VT) maps of foliar nitrogen using Landsat 8 satellite imagery.

Impacts
What was accomplished under these goals? Through instrumented research towers, remote sensing data collection and targeted field campaigns we have learned about how forests and agricultural lands interact and respond to variations in climate. For a large part of the summer of 2020 the northeastern US experienced extreme drought conditions. During this time, we measured photosynthetic rates (productivity) and leaf temperatures for a variety of tree species. We found that photosynthesis was drastically reduced (80-100% reduction) at leaf temperatures above 100oF. We also measured large differences in leaf temperatures across tree species with species such as eastern white pine able to maintain cooler leaf temperatures than species such as red maple, in which leaf temperatures often exceeded 100oF on sunny days. From our work it appears that leaf shape and evapotranspiration (or a plant's ability to "sweat") are both important for regulating temperature. Zooming out from leaves to whole ecosystems we have made similar findings about how forests and agricultural lands regulate vegetation temperature. As expected, the albedo (reflectivity) and the rate of transpiration (or "sweating") of plants are important, but an unexpected control is the roughness of the vegetations' surface. Rougher surfaces, as found in natural forests, are very important in regulating the temperature of plants both under warm and cool conditions. This suggests that strategies to increase the roughness of agricultural lands and orchards (such as planting tree breaks) may be an effective strategy to deal with variable climate conditions. We are also developing tools that will help landowners assess vegetation conditions on their own lands and be able to plan for future climate variability. First, we are comparing images collected using both research-grade and low-cost sensors mounted on unmanned aerial vehicles (UAV's or drones) to our field measurements of plant nitrogen (nutrient) content, productivity rates, and temperature. Our goal is to assess the ability of low-cost sensors marketed to landowners to capture information about the water and nutrient status of their lands. We are also working with satellite data to this same end. We have seen success in estimating vegetation properties at 30-meter resolution using data from NASA's Landsat 8 satellite. Specifically, we have seen that the reflectance of near infrared radiation from land surfaces (a freely available, downloadable data product from NASA) correlates strongly to the concentration of nitrogen in vegetation and to growth rates. We are currently compiling maps of nitrogen and productivity for all of New Hampshire, Maine, and Vermont. Lastly, using data we collect, we are continuing to develop ecosystem models that can predict how different vegetation types will respond under future climate and land management scenarios. Goal 1 - Conduct field measurements of plant productivity, leaf nitrogen concentrations, growing conditions, and ecosystem carbon dioxide exchange: Over the first 2 years of this project we have collected a large amount of data on foliar nitrogen, leaf temperature, soil conditions, and other variables affecting plant growth. These measurements were made using research towers with instruments permanently mounted above forest and agricultural vegetation, as well as with targeted field campaigns to measure detailed traits of various plant species. Specific measurements using instrumented towers include ongoing, continuous measurements of the exchange of carbon, water, and energy between vegetation and the atmosphere, as well as the timing of leaf emergence and senescence. With targeted field campaigns we have made 500+ measurements of foliage nitrogen, leaf mass per area (leaf thickness), and detailed leaf physiology (growth, carbon, and water exchange) in 2018, hundreds of soil and tree cores in 2019, and 3000+ measurements of leaf temperature and an additional 200+ foliar nitrogen measurements in 2020. Additionally, we made experimental measurements of plant productivity on leaves of forest trees subjected to a range of temperature (20-40oC or 68-104oF) and humidity conditions. Goal 2 - Collect UAV imagery with research grade and low cost sensors and compare to ground measurements: During the past reporting period, working with collaborators, we collected and have access to unmanned aerial vehicle (UAV) data collected during July and August 2020 from both low-cost and research grade sensors. Graduate student Ben Fraser, working with Dr. Russ Congalton, collected imagery over NHAES field sites where we have collected data, using the SenseFly Ebee+ fixed wing UAV with a natural color camera (SODA or Sensor Optimized for Drone Applications) and with a Sequoia+ (4 band: green, red: Red-Edge, NIR). Both sensors are low-cost sensors similar to those marketed to land managers and would be similar to imagery collected by local landowners. Images from these flights have already been orthomosaiced (stitched together) to make continuous maps over properties where we are working. In collaboration with Frankie Sullivan and Dr. Michael Palace, we also collected imagery using research grade sensors. Specifically, during this reporting period a Headwall Photonics Inc Nano Hyperspec sensor with 273 spectral bands from 400 to 1000 nanometers and a Velodyne VLP-16 lidar sensor with 16 channels, ~300,000 points/sec, a 360° horizontal field of view and a 30° vertical field of view, were flown onboard a DJI Matrice 600 UAV with an upgraded navigation system. Data processing of the imagery has already begun and will provide both spectral (reflectance) of vegetation, as well as 3D point clouds and information about the structure of plants and their position relative to one another. Goal 3 - Examine the degree to which UAV imagery and field measurements can be scaled to the broader region using similar reflectance data available from NASA's Landsat 8 instrument: We have not yet compared UAV imagery two similar data from satellite platforms but will do so as soon as processing of UAV imagery is finished. Graduate student Jack Hastings has worked towards becoming proficient with processing platforms such as Google Earth Engine to work with broad scale satellite data layers. During the last reporting period, he used these platforms to compile reflectance data and derived vegetation indices using wall to wall images of quality filtered Landsat satellite imagery for all of New Hampshire, Maine, and Vermont from the last 10 years (see attached figure of near infrared reflectance). He has already begun deriving maps of foliar nitrogen for these 3 states using field data collected during this project and will continue to refine these maps with the incorporation of additional planned field work.

Publications

• Type: Journal Articles Status: Published Year Published: 2020 Citation: Vadeboncoeur, M.A., Jennings, K.A., Ouimette, A.P., Asbjornsen, H. 2020. Correcting tree-ring ?13C time series for tree-size effects in eight temperate tree species. Tree Physiology. 40(3): 333-349 https://doi.org/10.1093/treephys/tpz138
• Type: Journal Articles Status: Published Year Published: 2020 Citation: Zhang, Quan; Barnes, Mallory; Benson, Michael; Burakowski, Elizabeth; Oishi, A. Christopher; Ouimette, Andrew; Sanders?DeMott, Rebecca; Stoy, Paul C.; Wenzel, Matt; Xiong, Lihua; Yi, Koong; Novick, Kimberly A. 2020. Reforestation and surface cooling in temperate zones: mechanisms and implications. Global Change Biology. 26(6): 3384-3401. https://doi.org/10.1111/gcb.15069
• Type: Journal Articles Status: Published Year Published: 2020 Citation: Deng, J., Xiao, J., Ouimette, A., Zhang, Y., Sanders-DeMott, R., Frolking, S., Li, C. 2020. Improving a biogeochemical model to simulate surface energy, greenhouse gas fluxes, and radiative forcing for different land use types in northeastern United States. Global Biogeochemical Cycles 34(8). https://doi.org/10.1029/2019GB006520
• Type: Conference Papers and Presentations Status: Other Year Published: 2020 Citation: Hastings, J. 2020. Tree Species Traits Determine the Success of LiDAR-based Crown Mapping at the Harvard Forest Megaplot. Harvard Forest LTER Ecology Symposium, Petersham, MA (Online), 22 September (Oral)
• Type: Journal Articles Status: Published Year Published: 2020 Citation: Hastings, J.H.; Ollinger, S.V.; Ouimette, A.P.; Sanders-DeMott, R.; Palace, M.W.; Ducey, M.J.; Sullivan, F.B.; Basler, D.; Orwig, D.A. Tree Species Traits Determine the Success of LiDAR-Based Crown Mapping in a Mixed Temperate Forest. Remote Sens. 2020, 12, 309. doi.org/10.3390/rs12020309
• Type: Conference Papers and Presentations Status: Other Year Published: 2020 Citation: Pederson, E.A., Ouimette, A.P., Sanders-DeMott, R., Hastings, J., Baillargeon, K., Ollinger, S.V. 2020. Using Leaf Chlorophyll and Nitrogen Concentrations of Mixed Species to Evaluate Forest Productivity in New Hampshire Temperate Forests. University of New Hampshire Undergraduate Research Conference, Durham, NH (Online). 11-27 April (Poster)
• Type: Conference Papers and Presentations Status: Other Year Published: 2019 Citation: Sanders-DeMott, R., Ouimette, A., Ollinger, S.V. 2019. Asynchronous Responses of Carbon Uptake and Carbon Loss to Antecedent Winter Conditions in Northern Temperate Ecosystems. American Geophysical Union Annual Meeting. San Francisco, CA., 9-13 December (Oral) B41E-01
• Type: Conference Papers and Presentations Status: Other Year Published: 2019 Citation: Contosta, A., Burakowski, E., Ducey, M.J., Frey, S.D., Ollinger, S.V., Ouimette, A., Sanders-DeMott, R., Varner, R.K. 2019. Going beyond carbon to understand biogeochemical and biophysical climate forcing of forested, agricultural, and residential land cover in a suburbanizing landscape. American Geophysical Union Annual Meeting. San Francisco, CA., 9-13 December (Oral) GC13D-05
• Type: Theses/Dissertations Status: Published Year Published: 2019 Citation: Hastings, John, "Tree Species Traits Determine the Success of LiDAR-based Crown Mapping in a Mixed Temperate Forest" (2019). Master's Theses and Capstones. 1326. https://scholars.unh.edu/thesis/1326
• Type: Journal Articles Status: Published Year Published: 2020 Citation: Finzi, A.C., Giasson, M.-A., Plotkin, A.A.B., Aber, J.D., Boose, E.R., Davidson, E.A., Dietze, M.C., Ellison, A.M., Frey, S.D., Goldman, E., Keenan, T.F., Melillo, J.M., Munger, J.W., Nadelhoffer, K.J., Ollinger, S.V., Orwig, D.A., Pederson, N., Richardson, A.D., Savage, K., Tang, J., Thompson, J.R., Williams, C.A., Wofsy, S.C., Zhou, Z., Foster, D.R., 2020. Carbon budget of the Harvard Forest Long-Term Ecological Research site: pattern, process, and response to global change. Ecological Monographs 90, e01423. https://doi.org/10.1002/ecm.1423
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Burakowski, E.A., Tawfik, A., Ouimette, A., Lepine, L., Zarzycki, C., Novick, K., Ollinger, S., Bonan, G., 2019. Simulating surface energy fluxes using the variable-resolution Community Earth System Model (VR-CESM). Theor. Appl. Climatol. 138, 115133. https://doi.org/10.1007/s00704-019-02785-0

Progress 10/01/18 to 09/30/19

Outputs
Target Audience:Our target audience included elementary, middle and high school students and teachers, undergraduate and graduate students, as well as other scientists, land managers, and conservation groups. Specifically we formally communicated with students and teachers from Dover Middle School, Dover, NH, Bishop Guertin High, Nashua, NH, Old Town High, Old Town, ME, Portsmouth High, Portsmouth, NH, Newport Middle School, Newport, NH, Cool Spring Hutterite Colony School Grade 5-8, Manitoba, Canada, Edmonton Academy Grade 7, Alberta, Canada, Coleytown Elementary School Kindergarten, Westport, CT, Mountain View High School 7th Grade Science Classroom, Mesa, AZ, The Blue School 8th Grade Science Classroom, New York City, NY, and the Alexander II Magnet School in Macon, Georgia. University of New Hampshire (UNH) undergraduate Elizabeth Pederson, and graduate students Kaitlyn Bailargeon and Jack Hasting were also involved in research related to this project and received mentorship from PI Ollinger and other senior personnel on the project. We have communicated formally with researchers both locally through meetings at the University of New Hampshire as well as a more global research audience through scientific conferences. Steve Eisenhauer, a land manager at UNH also participated in a research meeting held at UNH. PI Ollinger discussed results of the work and its land management implications with members of several New Hampshire conservation and land management groups at an invited meeting sponsored by the Society for the Protection of New Hampshire Forests. Changes/Problems:Our initial workplan involved purchasing a drone sensor setup that would allow us to compare field measurements directly to the type of reflectance data local landowners may have access to. We have so far opted not to do this because available funds were insufficient for both purchasing the drone system and having support for personnel to conduct field measurements and data analyses. We opted to focus on field data collection because relevant drone imagery have become available through collaborations with other UNH researchers (e.g. Palace, Sullivan, Congalton, and Fraser). We are working with these research groups to collect both research-grade and lower cost drone imagery needed to complete this project. Relying on existing drone systems has allowed us to focus our efforts on the field measurements needed to complete the project, which would not be available from other sources. Building on our existing field data record has also had the secondary benefit of strengthening Thompson Farm as a nationally recognized research station and building new collaborations with investigators at UNH and other institutions, including Stanford University, Macalaster College, Tartu Observatory (Estonia), and the US Forest Service. Our work at Thompson Farm has also played a big role in why there has been a conscious effort among researchers at UNH to make Thompson Farm a world-class research site and helped initiate the first annual Thompson Farm Researcher's Meeting. What opportunities for training and professional development has the project provided?Our research group is structured to allowfor career development opportunities and training ofstudents and researchers who are at different stages of their career. For example, on this project undergraduate Elizabeth Pederson was trained in the field collection of data by both senior research staff (post doc Sanders DeMott and research scientist Ouimette) as well as graduate students (Bailargeon and Hastings). This provided technical training for Elizabeth as well as the development of leadership skills for both graduate students and senior personnel. Elizabeth also worked with collaborators at the US Forest Service and in the UNH Stable Isotope Facility to complete laboratory analyses of samples. Undergraduate and graduate students, post-docs, research staff, collaborators, and faculty all contributed to data analysis and interpretation through presentations of the data at meetings within our research group. Sanders-Demott also trained middle school and high school students and their teachers in the collection of meteorological and ecological data during winter conditions, a period of time for which data are often lacking. How have the results been disseminated to communities of interest?During the past reporting period we communicated science-based knowledge to students, teachers, researchers, and land managers from UNH and the New Hampshire Forest Society. Outreach to students and teachers Post-doc Sanders-DeMott co-led and designed materials for multiple workshops from November 2018 through April 2019 on monitoring winter climate (e.g. snow depth and soil frost) and early plant phenology (bud burst, leaf out, leaf expansion) at: Dover Middle School, Dover, NH Bishop Guertin High, Nashua, NH Old Town High, Old Town, ME Portsmouth High, Portsmouth, NH Newport Middle School, Newport, NH These workshops, carried out in collaboration with E Burakowski and A Contosta (University of New Hampshire) and J Campbell (US Forest Service) involved training students in hands-on data collection, synthesis across multiple school-based citizen science datasets, and teaching about the importance of this data collection using examples from the AES-supported data collection at Thompson Farm forest (Durham, NH) and Kingman Farm grassland (Madbury, NH). Student data was contributed to the GLOBE website and is freely available to the community. Sanders-DeMott also participated in online classroom visits through the Skype-a-Scientist program with students in the following schools: Cool Spring Hutterite Colony School Grade 5-8, Manitoba, Canada Edmonton Academy Grade 7, Alberta, Canada Coleytown Elementary School Kindergarten, Westport, CT Mountain View High School 7th Grade Science Classroom, Mesa, AZ The Blue School 8th Grade Science Classroom, New York City, NY Research scientist Ouimette formally mentored University of New Hampshire undergraduate Elizabeth Pederson with her senior undergraduate independent research project. Elizabeth conducted field collection of data in collaboration with University of New Hampshire scientists, performed laboratory analyses of leaf chemistry in collaboration with Dr. Rakesh Minocha (US Forest Service), and will present an analysis of her results at UNH's undergraduate research conference in the spring of 2020. Ouimette also formally communicated with two elementary school classes and their teachers at the Alexander II Magnet School in Macon, Georgia through the skype a scientist program. Communication with other scientists and land managers Students, research staff, and faculty all presented our research at several conferences and workshops over the past year. For example, a global audience of scientific researchers and undergraduate/graduate students was reached at the American Geophysical Union (AGU) conference in San Francisco, CA during December 2019. Because of the financial support of this program we have been able to maintain infrastructure at Thompson Farm (a local research site near the University of New Hampshire). Because of the continued measurements and infrastructure this lead to the 1st annual Thompson Farm Researcher's Meeting, where 15+ faculty, research staff, and graduate students from several departments at UNH met to discuss research efforts and potential collaborations. Steve Eisenhauer, a land manager at UNH, also participated and provided valuable insight into land-use at the property. What do you plan to do during the next reporting period to accomplish the goals?During the next reporting period we have 3 main objectives. First, we aim to complete compilation and analysis of the multiple datasets we have collected over the past 6 years relating leaf nitrogen concentrations to leaf photosynthetic capacity. We will use relationships developed from this effort combined with an ecosystem model to assess our ability to estimate carbon fluxes across the northern forest region. Second, we will work with collaborators to continue collection and processing of drone imagery from both research -grade and less expensive sensor designs. We plan to begin comparison of field collected data on foliar nitrogen and productivity to the reflectance of radiation (light) from foliage in the canopy collected using drones. Third, we will work towards developing a spatial map of foliar nitrogen concentration and photosynthetic capacity estimated using reflectance from NASA's Landsat satellite remote sensing platform. This will depend, in part, on the availability of cloud-free imagery during a time that's consistent with data collection. The ultimate goal is an improved ability to estimate foliar nutrient status and productivity of vegetated landscapes across the northeast region at relatively fine grain size.

Impacts
What was accomplished under these goals? The ability to map agricultural and forest productivity is important to forest and farm managers and helps scientists better understand how ecosystems are affected by climate. Although Earth-observing satellites can provide useful information over largeareas, the images they produce are often too coarse to be useful locally. Recent growth in the availability of drone-based sensors may provide a solution, but most have not been thoroughly tested for these applications. Here, we plan to evaluate the usefulness of several drone-based sensors being marketed to land management practitioners by comparing the data they collect with careful measurements of plant health, leaf chemistry, and growth rates. We had 3 primary goals at the start of this project: (1) Conduct field measurements of plant productivity, leaf nitrogen concentrations, growing conditions, and ecosystem carbon dioxide exchange; 2) evaluate the degree to which measurements of leaf nutrient concentration (nitrogen) and productivity relate to spectral features (reflectance of light) in drone-based imagery acquired from research-grade sensors, as well as less expensive sensors being marketed to agricultural and forest management practitioners; 3) Examine the degree to which drone-based imagery and field measurements can be scaled to the broader region using similar reflectance data available from the National Aeronautics and Space Administration (NASA)'s Landsat-8 instrument. To date, we have made significant progress on Goals 1 and 2, with plans to expand work on both and to begin to work towards Goal 3. Goal 1: Between 2018-2019 we held an intensive field campaign to measure leaf nitrogen concentration and plant productivity, as well as ecosystem measurements of carbon exchange and growing conditions. Our efforts were focused at the Thompson Farm forest and resulted in roughly 500 leaf-level growth measurements across various conditions throughout the growing season. Additionally, we continued ecosystem measurements of carbon exchange at this site and have completed all data processing involved in producing high-quality carbon exchange data at a range of time scales. This effort along with previous work from other experimental forests in New Hampshire provided us with a rich dataset of leaf-level nitrogen and productivity to compare with remotely sensed observations. Goal 2: Through collaboration with other researchers at UNH, drone imagery measuring spectral features of the forest canopy has been and continues to be acquired at local research sites using both research-grade and less-expensive sensors. Specifically, in collaboration with Dr. Michael Palace and Frankie Sullivan drone imagery was collected during the past year using research-grade sensors (a Headwall Photonics, Inc. Nano Hyperspec sensor with 273 spectral bands from 400-1000nm, flown on board a DJI Matrice 600 unpersoned aerial vehicle). Due to georeferencing issues, these data have not been used for analysis. An upgraded inertial navigation system was purchased in spring 2019, and the hyperspectral sensor is tasked for monthly flights at Thompson Farm from May-September 2020. In addition, a UAV-mounted lidar sensor, the Velodyne VLP-16, has been flown at monthly at Thompson Farm from November 2019 through February 2020, primarily over agricultural fields. The sensor is tasked for flights over the forest prior to leaf-out at Thompson Farm in April 2020, with follow-up flights in June-July 2020. In collaboration with Dr. Russ Congalton and PhD. student Benjamin Fraser, we plan to use imagery collected by their research group collected over Thompson Farm (and other UNH properties) using less expensive sensors. Specifically, natural color imagery was captured with the SenseFly eBee+ fixed-wing UAV and the Sensor Optimized for Drone Applications. Upcoming flights are also planned using Sequoia+ drone with a multispectral sensor that comprises 5 lenses (Green Band, Red Band, Red-Edge, Near Infra-red, and a natural color sensor). This is similar to imagery that could be collected by local landowners. Goal 3: We have not yet compared drone imagery to similar spectral bands available from National Aeronautics and Space Administration (NASA)'s Landsat-8 instrument. However, with the rich datasetwe have collected and compiled as part of Goal 1, we are currently assessing the relationship between the concentration of nitrogen in foliage and the photosynthetic capacity (productivity) of those leaves. Previous work by our group has been successful in estimating foliar nitrogen concentrations using reflectance data from satellite and airborne remote sensing platforms. The aim is to be able to then use remotely sensed reflectance data to estimate productivity at various spatial and temporal scales.

Publications

• Type: Journal Articles Status: Published Year Published: 2019 Citation: Sanders-DeMott, R., Ouimette, A.P., Lepine, L.C., Fogarty, S.Z., Burakowski, E.A., Contosta, A.R., Ollinger, S.V. 2019. Divergent carbon cycle response of forest and grass-dominated northern temperate ecosystems to record winter warming. Global Change Biology, 2019, 00:113, DOI: 10.1111/gcb.14850
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Burakowski, E.A., Tawfik, A., Ouimette, A., Lepine, L., Zarzycki, C., Novick, K., Ollinger, S., Bonan, G., 2019. Simulating surface energy fluxes using the variable-resolution Community Earth System Model (VR-CESM). Theor. Appl. Climatol. 138, 115133.
• Type: Journal Articles Status: Published Year Published: 2019 Citation: Ouimette, A.P., S.V. Ollinger, L.C. Lepine, R.B. Stephens, R.J. Rowe, M.A. Vadeboncoeur, S.J. Tumber-Davila, E.A. Hobbie. 2019. Accounting for carbon flux to mycorrhizal fungi may resolve discrepancies in forest carbon budgets. Ecosystems, 9/2019, doi.org/10.1007/s10021-019-00440-3
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2019 Citation: Ouimette A, Ollinger SV, Sanders-DeMott R, Zhou Z, Hastings J, Baillargeon K. Does Diversity in Species Specific Leaf Traits and Resource Use Promote Stability of Forest Ecosystem Carbon and Water Fluxes?. InAGU Fall Meeting 2019 2019 Dec 13. AGU.