mall unmanned aerial systems (UAS), also known as drones or unmanned aerial vehicles, have a rapidly growing role in research and practice in agriculture and natural resources. Here, we present the parameters and key limitations of the technology, summarize current regulations and cover examples of University of California research enabled by UAS technology. Will Suckow The Inspire 1 drone, made by DJI, flies with an RGB camera over the UC Berkeley Blue Oak Ranch Reserve in Santa Clara County. http://calag.ucanr.edu • JANUARY-MARCH 2017 5 Feature Andreas Anderson, an instructor with the Center for Information Technology Research in the Interest of Society at UC Merced, checks the control systems for a drone-mounted multispectral camera before a research flight in Merced County for a study on water stress in almond trees.

Unmanned aerial vehicles (UAVs) equipped with multispectral sensors present an opportunity to monitor vegetation with on-demand high spatial and temporal resolution. In this study we use multispectral imagery from quadcopter UAVs to monitor the progression of a water manipulation experiment on a common shrub, Baccharis pilularis (coyote brush) at the Blue Oak Ranch Reserve (BORR) ~20 km east of San Jose, California. We recorded multispectral imagery at several altitudes with nearly hourly intervals to explore the relationship between two common spectral indices, NDVI (normalized difference vegetation index) and NDRE (normalized difference red edge index), leaf water content and water potential as physiological metrics of plant water status, across a gradient of water deficit. An examination of the spatial and temporal thresholds at which water limitations were most detectable revealed that the best separation between levels of water deficit were at higher resolution (lower flying height), and in the morning (NDVI) and early morning (NDRE). We found that both measures were able to identify moisture deficit across treatments; however, NDVI was better able to distinguish between treatments than NDRE and was more positively correlated with field measurements of leaf water content. Finally, we explored how relationships between spectral indices and water status changed when the imagery was scaled to courser resolutions provided by satellite-based imagery (PlanetScope).We found that PlanetScope data was able to capture the overall trend in treatments but unable to capture subtle changes in water content. These kinds of experiments that evaluate the relationship between direct field measurements and UAV camera sensitivity are needed to enable translation of field-based physiology measurements to landscape or regional scales.

There is an urgent need to develop climate smart agroecosystems capable of mitigating climate change and adapting to its effects. In California, high commodity prices and increased frequency of drought have encouraged orchard turnover, providing an opportunity to recycle tree biomass in situ prior to replanting an orchard. Whole orchard recycling (WOR) has potential as a carbon (C) negative cultural practice to build soil C storage, soil health, and orchard productivity. We tested the potential of this practice for long term C sequestration and hypothesized that associated co-benefits to soil health will enhance sustainability and resiliency of almond orchards to water-deficit conditions. We measured soil health metrics and productivity of an almond orchard following grinding and incorporation of woody biomass vs. burning of old orchard biomass 9 years after implementation. We also conducted a deficit irrigation trial with control and deficit irrigation (-20%) treatments to quantify shifts in tree water status and resilience. Biomass recycling led to higher yields and substantial improvement in soil functioning, including nutrient content, aggregation, porosity, and water retention. This practice also sequestered significantly higher levels of C in the topsoil (+5 t ha -1 ) compared to burning. We measured a 20% increase in irrigation water use efficiency and improved soil and tree water status under stress, suggesting that in situ biomass recycling can be considered as a climate smart practice in California irrigated almond systems.

Background: Globally, vegetation in riparian zones is frequently the target of restoration efforts because of its importance in reducing the input of eroded sediment and agricultural nutrient runoff to surface waters. Here we examine the potential of riparian zone restoration to enhance carbon sequestration. We measured soil and woody biomass carbon stocks, as well as soil carbon properties, in a long-term chronosequence of 42 streambank revegetation projects in northern California rangelands, varying in restoration age from 1 to 45 years old. Results: Where revegetation was successful, we found that soil carbon measured to 50 cm depth increased at a rate of 0.87 Mg C ha −1 year −1 on the floodplain and 1.12 Mg C ha −1 year −1 on the upper bank landform. Restored sites also exhibited trends toward increased soil carbon permanence, including an increased C:N ratio and lower fulvic acid: humic acid ratio. Tree and shrub carbon in restored sites was modeled to achieve a 50-year maximum of 187.5 Mg C ha −1 in the channel, 279.3 Mg ha −1 in the floodplain, and 238.66 Mg ha −1 on the upper bank. After 20 years of restoration, the value of this carbon at current per-ton C prices would amount to $US 15,000 per km of restored stream. Conclusion: We conclude that revegetating rangeland streambanks for erosion control has a substantial additional benefit of mitigating global climate change, and should be considered in carbon accounting and any associated financial compensation mechanisms.

Unmanned aerial vehicles (UAVs) equipped with multispectral sensors present an opportunity to monitor vegetation with on-demand high spatial and temporal resolution. In this study, we use multispectral imagery from quadcopter UAVs to monitor the progression of a water manipulation experiment on a common shrub, Baccharis pilularis (coyote brush), at the Blue Oak Ranch Reserve (BORR) near San Jose, California. We recorded multispectral data from the plants at several altitudes with nearly hourly intervals to explore the relationship between two common spectral indices, NDVI and NDRE, and plant water content and water potential, as physiological metrics of plant water status, across a gradient of water deficit. An examination of the spatial and temporal thresholds at which water limitations were most detectable revealed that the best separation between levels of water deficit were at higher resolution (lower flying height), and in the morning (NDVI) and early morning (NDRE). We found that both measures were able to identify moisture deficit in plants and distinguish them from control and watered plants; however, NDVI was better able to distinguish between treatments than NDRE and was more positively correlated with field measurements of plant water content than NDRE. Finally, we explored how relationships between spectral indices and water status changed when the imagery was scaled to courser resolutions provided by satellite-based imagery (PlanetScope) and found that PlanetScope data was able to capture the overall trend in treatments but was not able to capture subtle changes in water content. These kinds of experiments that evaluate the relationship between direct field measurements and UAV camera sensitivity are needed to enable translation of field-based physiology measurements to landscape or regional scales.